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IBM Analytics test format
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Understanding complex events in today’s business world is critical. The explosion of data analytics—and the desire for insights and knowledge—represents both an opportunity and a challenge.

At the center of this effort is predictive analytics. The ability to transform raw data into insights and make informed business decisions is crucial. Today, predictive analytics plays a role in almost every corner of the enterprise, from finance and marketing to operations and cybersecurity. It involves pulling data from legacy databases, data lakes, clouds, social media sites, point of sale terminals and IoT on the edge.

It’s critical to select a predictive analytics platform that generates actionable information. For example, financial institutions use predictive analytics to understand loan and credit card applications, and even grant a line of credit on the spot. Operations departments use predictive analytics to understand maintenance and repairs for equipment and vehicles, and marketing and sales use it to gauge interest in a new product.

Top predictive analytics platforms deliver powerful tools for ingesting and exporting data, processing it and delivering reports and visualizations that guide enterprise decision-making. They also support more advanced capabilities, such as machine learning (ML), deep learning (DL), artificial intelligence (AI) and even digital twins. Many solutions also provide robust tools for sharing visualizations and reports. 

Types of Predictive Models

Predictive models are designed to deliver insights that guide enterprise decision-making. Solutions incorporate techniques such as data mining, statistical analysis, machine learning and AI. They are typically used for optimizing marketing, sales and operations; improving profits and reducing costs; and reducing risks related to things like security and climate change.

Also see: Best Data Analytics Tools 

Four major types of predictive models exist:

Regression models

A regression model estimates the relationship between different variables to deliver information and insight about future scenarios and impacts. It is sometimes referred to as “what if” analysis.

For example, a food manufacturer might study how different ingredients impact quality and sales. A clothing manufacturer might analyze how different colors increase or decrease the likelihood of a purchase. Models can incorporate correlations (relationships) and causality (reasons).

Classification models

These predictive models place data and information in categories based on past histories and historical knowledge. The data is labeled, and an algorithm learns the correlations. The model can then be updated with new data, as it arrives. These models are commonly used for fraud detection and to identify cybersecurity attacks.

Clustering models

A cluster model assembles data into groups, based on common attributes and characteristics. It often spots hidden patterns in systems. In a factory, this might mean spotting misplaced supplies and equipment and then using the data to predict where it will be during a typical workday. In retail, a store might send out marketing materials to a specific group, based on a combination of factors such as income, occupation and distance.

Time-Series models

As the name implies, a time-series model looks at data during a given period, such as a day, month or year. Using predictive analytics, it’s possible to estimate what the trend will be in an upcoming period. It can be combined with other methods to understand underlying factors. For instance, a healthcare system might predict when the flu will peak—based on past and current time-series models.

In more advanced scenarios, predictive analytics also uses deep learning techniques that mimic the human brain through artificial neural networks. These methods may incorporate video, audio, text and other forms of unstructured data. For instance, voice recognition or facial recognition might analyze the tone or expression a person displays, and a system can then respond accordingly.

Also see: Top Business Intelligence Software 

How to Select a Predictive Analytics Platform

All major predictive analytics platforms are capable of producing valuable insights. It’s important to conduct a thorough internal review and understand what platform or platforms are the best fit for an enterprise. All predictive analytics solutions generate reports, charts, graphics and dashboards. The data must also be embedded into automation processes that are driven by other enterprise applications, such as an ERP or CRM system.

Step 1: Understand your needs and requirements

An internal evaluation should include the types of predictive analytics you need and what you want to do with the data. It should also include what type of user—business analyst or data scientist—will use the platform. This typically requires a detailed discussion with different business and technical groups to determine what types of analytics, models, insights and automations are needed and how they will be used.

Step 2: Survey the vendor landscape

The capabilities of today’s predictive analytics platforms is impressive—and companies add features and capabilities all the time. It’s critical to review your requirements and find an excellent match. This includes more than simply extracting value from your data. It’s important to review a vendor’s roadmap, its commitment to updates and security, and what quality assurance standards it has in place. Other factors include mobile support and scalability, Internet of Things (IoT) functionality, APIs to connect data with partners and others in a supply chain, and training requirements to get everyone up to speed.

Step 3: Choose a platform

Critical factors for vendor selection include support for required data formats, strong data import and export capabilities, cleansing features, templates, workflows and embedded analytics capabilities. The latter is critical because predictive analytics data is typically used across applications, websites and companies.

A credit card check, for example, must pull data from a credit bureau but also internal and other partner systems. The APIs that run the task are critical. But there are other things to focus on, including the user interface (UI) and usability (UX). This extends to visual dashboards that staff uses to view data and understand events. It’s also vital to look at licensing costs and the level of support a vendor delivers. This might include online resources and communities as well as direct support.

Top Predictive Analytics Platforms

Here are 10 of the top predictive analytics solutions:

Google Looker

Key Insight: The drag-and-drop platform is adept at generating rich visualizations and excellent dashboards. It ranks high on flexibility, with support for almost any type of desired chart or graphics. It can generate valuable data for predictive analytics by connecting to numerous other data sources, including Microsoft SQL and Excel, Snowflake, SAP HANA, Salesforce and Amazon Redshift. It also includes powerful tools for selecting parameters, filtering data, building data-driven workflows and obtaining results. While the platform is part of Google Cloud and it is optimized for use within this environment, it supports custom applications.

Pros

  • The highly flexible platform runs on Windows, Macs and Linux. It offers strong mobile device support.
  • Generates strong data-driven workflows and supports custom applications.
  • Users deliver the platform Good Score for its interface and ease of use.

Cons

  • Lacks some customization features found in other analytics solutions.

IBM SPSS Modeler

Key Insight: The predictive analytics platform is designed to put statistical data to work across a wide array of industries and use cases. It includes powerful data ingestion capabilities, ad hoc reporting, predictive analytics, hypothesis analysis, statistical and geospatial analysis and 30 base machine learning components. IBM SPSS Modeler includes a rich set of tools and features, accessible through sophisticated dashboards.

Pros 

  • Offers excellent open-source extensibility through R and Python, along with support for numerous data sources, including flat files, spreadsheets, major relational databases, IBM Planning Analytics and Hadoop.
  • Visual drag-and-drop interface speeds tasks for data analysts and data scientists.
  • Works on all major operating systems, including Windows, Linux, Unix and Mac OS X.

Cons

  • Not as user friendly as other platform analytics platforms. Typically requires training to use it effectively.

Qlik Sense

Key Insight: Qlik Sense is a cloud-native platform designed specifically for business intelligence and predictive analytics. It delivers a robust set of features and capabilities, available through dashboards and visualizations. Qlik Sense includes AI and machine learning components; embedded analytics that can be used for websites, business applications and commercial software; and strong support for mobile devices. The solution supports hundreds of data types, and a broad array of analytics use cases.

Pros

  • Offers powerful drag-and-drop interface to enable fast modeling.
  • A “Smart Search” feature aids in uncovering and connecting complex data relationships.
  • Provides rich visualizations along with highly interactive and powerful dashboard features.

Cons

  • Can be pricy, particularly with additional add-ons.

Salesforce

Key Insight:  The widely used CRM and sales automation platform includes powerful analytics and business intelligence tools, including features driven by the company’s AI-focused Einstein Analytics. It delivers insights and suggestions through specialized AI agents. A centralized Salesforce dashboard offers charts, graphs and other insights, along with robust reporting capabilities. There’s also deep integration with the Tableau analytics platform, which is owned by Salesforce.

Pros

  • Powerful features and highly customizable views of data.
  • Integrates with more than 1,000 platforms. Strong data ingestion capabilities.
  • A generally intuitive UI and strong UX make the platform powerful yet relatively easy to use.

Cons

  • No trial or free version available.

SAP Analytics Cloud

Key Insight: Formerly known as BusinessObjects for cloud, SAP Analytics Cloud can pull data from a broad array of sources and platforms. It is adept at data discovery, compilation, ad-hoc reporting and predictive analytics. It includes machine learning and AI functions that can guide data analysis and aid in modeling and planning. A dashboard offers flexible options for displaying analytics data in numerous ways.

Pros

  • Accommodates large data sets from a diverse range of sources.
  • Offers highly customizable, interactive charts and other graphics.
  • Includes powerful ML and AI components.

Cons

  • Not as visually rich as other platforms.

SAS Visual Analytics

Key Insight: The low-code cloud solution is designed to serve as a “single application for reporting, data exploration and analytics.” It imports data from numerous sources; supports rich dashboards and visualizations, with strong drill-down features; includes augmented analytics and ML; and includes robust collaboration and data sharing features. The platform also includes natural language chatbots that aid business users and other non-data scientists in content creation and management.

Pros

  • Delivers fast performance, even with large data volumes.
  • Supports a wide array of predictive analytics use cases.
  • Includes smart algorithms that accommodate predictive analytics without the need for programming skills.

Cons

  • Expensive, particularly for smaller organizations.

Tableau Desktop

Key Insight: The enormous popularity of Tableau is based on the platform’s powerful features and its ability to generate a wide range of appealing and useful charts, graphs, maps and other visualizations through highly interactive real-time dashboards. The platform offers support for numerous predictive analytics frameworks, including regression models, classification models, clustering models, time-series models. Non data scientists typically find its user interface accommodating and easy-to-learn.

Pros

  • Excellent UI and UX. Most users find it easy to generate useful analytics models and visualizations.
  • Supports flexible, scalable and highly customizable predictive analytics use cases.
  • Tight integration with Salesforce CRM. Generates excellent visualizations.

Cons

  • Sometimes pulls considerable compute resources, including CPUs and RAM. It can also perform slowly on mobile devices.

Teradata Vantage

Key Insight: Teradata Vantage delivers powerful predictive analytics capabilities, including the ability to use data from both on-premises legacy hardware sources and multicloud public frameworks, including AWS, Azure and Google Cloud. The solution also works across virtually any data source, including data lakes and data warehouses. It supports sophisticated AI and ML functionality and includes no-code and low-code drag and drop components for building models and visuals. The company is especially known for its fraud prevention analytics tools, though it offers numerous other predictive tools and capabilities.

Pros

  • Highly flexible. Powerful SQL engine supports broad, deep and complex queries.
  • Accommodates huge workloads, almost any type of query, and delivers fast and efficient data processing.
  • Generates dynamic visualizations and an easy-to-use yet powerful interface.

Cons

  • Some users complain about a lack of documentation and training materials.

TIBCO Spotfire

Key Insight: TIBCO Spotfire offers a powerful platform for performing predictive analytics. It connects to numerous data sources and includes real-time feeds that can be highly filtered and customized. The solution is designed for both business users and data scientists. It includes rich visualizations and supports customizations through R and Python.

Pros:

  • TIBCO offers a strong API management framework.
  • Delivers rich visualizations and immersive interactive visual analytics.
  • Strong support for real-time decision making across multiple industries and use cases.

Cons:

  • Customizations can be time consuming and difficult.

ThoughtSpot

Key Insight: The analytics cloud delivers highly flexible self-service predictive analytics. The query engine is designed to search on virtually any data format and understand complex table structures over billions of rows. It offers powerful search and filtering capabilities that extend to natural language queries. ThoughtSpot also provides a powerful processing engine that generates a range of visualizations, including social media intelligence. The solution includes a machine learning component that ranks the relevancy of results.

 Pros

  • The platform gets Good Score from users for its user interface and ease of use.
  • ThoughtSpot delivers a high level of flexibility, including an ability to search Snowflake, BigQuery and other cloud data warehouses in real time.
  • Natural language search reduces the need for complex SQL input.

Cons

  • Users complain that data source connectivity isn’t as robust as other analytics platforms.

Also see: Top Cloud Companies

Predictive Analytics Vendor Comparison Chart

Company Key Product Pros Cons
Google Looker Excellent drag-and-drop interface with appealing visualizations and a high level of flexibility Support is almost entirely online
IBM SPSS Modeler Excellent open-source extensibility; strong drag-and-drop functionality Not as user friendly as other analytics solutions
Qlik Qlik Sense Powerful and versatile platform with strong modeling features Some complaints about customer support
Salesforce Salesforce Highly customizable; strong integration with other platforms and data sources Expensive
SAP Analytics Cloud Supports extremely large datasets and has powerful capabilities Visualizations are not always as appealing as other platforms
SAS Visual Analytics High performance platform that supports numerous data types and visualizations May require customization
Tableau Tableau Desktop Outstanding UI and UX, with deep Salesforce/CRM integration Can drain CPUs and RAM
TIBCO Spotfire Powerful predictive analytics platform with excellent visual output Steep learning curve
Teradata Advantage Highly flexible with a powerful SQL engine; generates rich visualizations Some users complain about an aging UI.
ThoughtSpot ThoughtSpot Flexible, powerful capabilities with a strong UI and UX Visualizations sometimes lag behind competitors
Sun, 25 Sep 2022 06:33:00 -0500 en-US text/html https://www.eweek.com/cloud/predictive-analytics-solutions/
Killexams : Analytics as a Service(AaaS) Market Overview 2022 to 2030, Future Trends and Forecast | By -IBM, Oracle, Computer Science Corporation(CSC)

The MarketWatch News Department was not involved in the creation of this content.

Oct 06, 2022 (Heraldkeepers) -- New Jersey, United States-This Analytics as a Service(AaaS) market examines the regional and global markets as well as the overall development opportunities in the industry. Additionally, it provides insight into the entire serious scene of the global Analytics as a Service(AaaS) industry. The research also includes a dashboard summary of the leading companies, outlining their successful marketing strategies, market commitment, and ongoing improvements in both historical and contemporary contexts.

The Global Analytics as a Service(AaaS) Market investigation report contains Types (Predictive, Prescriptive, Diagnostic, Descriptive), Segmentation & all logical and factual briefs about the Market 2022 Overview, CAGR, Production Volume, Sales, and Revenue with the regional analysis covers North America, Europe, Asia-Pacific, South America, Middle East Africa & The Prime Players & Others.

Download sample Analytics as a Service(AaaS) Market Report 2022 to 2030 here:

The Worldwide Analytics as a Service(AaaS) market size is estimated to be worth USD million in 2022 and is forecast to a readjusted size of USD million by 2030 with a CAGR of % during the review period.

The Analytics as a Service(AaaS) market research provides a detailed analysis of the industry by providing information on a variety of angles, including drivers, constraints, opportunities, and risks. This information can help partners make wise decisions before contributing by guiding them. Beginning with the approval of the data handled in the auxiliary investigation is the crucial examination.

Analytics as a Service(AaaS) Market Segmentation & Coverage:

Analytics as a Service(AaaS) Market segment by Type: 
Predictive, Prescriptive, Diagnostic, Descriptive

Analytics as a Service(AaaS) Market segment by Application: 
BFSI, Retail and Wholesale, Government, Healthcare and Life Sciences, Manufacturing, Telecommunication and IT, Others

The years examined in this study are the following to estimate the Analytics as a Service(AaaS) market size:

History Year: 2015-2019
Base Year: 2021
Estimated Year: 2022
Forecast Year: 2022 to 2030

Cumulative Impact of COVID-19 on Market:

More than 20 million COVID-19 cases would have been confirmed as of the study’s start date, and the pandemic had not been effectively controlled. We predict that the global Analytics as a Service(AaaS) market will reach million USD by the end of 2021 with a CAGR of between 2022 and 2030 and that the entire pandemic will have been largely contained by then.

Access a sample Report Copy of the Analytics as a Service(AaaS) Market: https://www.infinitybusinessinsights.com/request_sample.php?id=1013628

Regional Analysis:

The APAC (Asia Pacific) district is anticipated to experience the greatest rate of growth in the Analytics as a Service(AaaS) Market among all geographical areas. One explanation for this development could be the widespread advancement in countries like South Korea, China, Japan, and India. The rate of improvement in China is stabilizing as it considers various evened-out measures, stock charges, and current yield.

The Key companies profiled in the Analytics as a Service(AaaS) Market:

The study examines the Analytics as a Service(AaaS) market’s competitive landscape and includes data on important suppliers, including IBM, Oracle, Computer Science Corporation(CSC), Hewlett-Packard Enterprise(HPE), SAS Institute, Google, Amazon Web Services(AWS), EMC, Gooddata, Microsoft,& Others

Table of Contents:

List of Data Sources:

Chapter 2. Executive Summary
Chapter 3. Industry Outlook
3.1. Analytics as a Service(AaaS) Global Market segmentation
3.2. Analytics as a Service(AaaS) Global Market size and growth prospects, 2015 – 2026
3.3. Analytics as a Service(AaaS) Global Market Value Chain Analysis
3.3.1. Vendor landscape
3.4. Regulatory Framework
3.5. Market Dynamics
3.5.1. Market Driver Analysis
3.5.2. Market Restraint Analysis
3.6. Porter’s Analysis
3.6.1. Threat of New Entrants
3.6.2. Bargaining Power of Buyers
3.6.3. Bargaining Power of Buyers
3.6.4. Threat of Substitutes
3.6.5. Internal Rivalry
3.7. PESTEL Analysis
Chapter 4. Analytics as a Service(AaaS) Global Market Product Outlook
Chapter 5. Analytics as a Service(AaaS) Global Market Application Outlook
Chapter 6. Analytics as a Service(AaaS) Global Market Geography Outlook
6.1. Analytics as a Service(AaaS) Industry Share, by Geography, 2022 & 2030
6.2. North America
6.2.1. Analytics as a Service(AaaS) Market 2022 -2030 estimates and forecast, by product
6.2.2. Analytics as a Service(AaaS) Market 2022 -2030, estimates and forecast, by application
6.2.3. The U.S.
6.2.4. Canada
6.3. Europe
6.3.3. Germany
6.3.4. the UK
6.3.5. France
Chapter 7. Competitive Landscape
Chapter 8. Appendix

Get Full INDEX of Analytics as a Service(AaaS) Market Research Report. Stay tuned for more updates @

FAQs:
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Wed, 05 Oct 2022 17:08:00 -0500 en-US text/html https://www.marketwatch.com/press-release/analytics-as-a-serviceaaas-market-overview-2022-to-2030-future-trends-and-forecast-by--ibm-oracle-computer-science-corporationcsc-2022-10-06 Killexams : Best Database Certifications for 2020

Savvy, talented and knowledgeable database professionals are always in demand. This article covers some of the best, most in-demand certifications for database administrators, database developers and anyone else who works with databases. 

During the past three decades, we’ve seen a lot of database platforms come and go, but there’s never been any question that database technology is a crucial component for all kinds of applications and computing tasks. 

Database certifications may not be as sexy or bleeding-edge as cloud computing, storage, or computer forensics. That said, there has been and always will be a need for knowledgeable database professionals at all levels and in a plethora of database-related job roles. 

To get a better grasp of the available database certifications, it’s useful to group these certs around job responsibilities. In part, this reflects the maturity of database technology and its integration into most aspects of commercial, scientific and academic computing. As you read about the various database certification programs, keep these job roles in mind: 

  • Database administrator (DBA): Responsible for installing, configuring and maintaining a database management system (DBMS). Often tied to a specific platform such as Oracle, MySQL, DB2 or SQL Server. 
  • Database developer: Works with generic and proprietary APIs to build applications that interact with a DBMS (also platform-specific, like DBA roles).
  • Database designer/database architect: Researches data requirements for specific applications or users, and designs database structures and application capabilities to match.
  • Data analyst/data scientist: Responsible for analyzing data from multiple disparate sources to discover previously hidden insight, determine meaning behind the data and make business-specific recommendations.
  • Data mining/business intelligence (BI) specialist: Specializes in dissecting, analyzing and reporting on important data streams, such as customer data, supply chain data, and transaction data and histories.
  • Data warehousing specialist: Specializes in assembling and analyzing data from multiple operational systems (orders, transactions, supply chain information, customer data, etc.) to establish data history, analyze trends, generate reports and forecasts, and support general ad hoc queries. 

Careful attention to these database job roles highlights two important technical issues for would-be database professionals to consider. 

First, a good general background in relational database management systems, including an understanding of Structured Query Language (SQL), is a basic prerequisite for database professionals of all stripes. 

Second, although various efforts to standardize database technology exist, much of the whiz-bang capability that databases and database applications deliver come from proprietary, vendor-specific technologies. Serious, heavy-duty database skills and knowledge are tied to specific platforms, including various Oracle products (such as the open-source MySQL environment and Oracle itself,) Microsoft SQL Server and IBM DB2. That’s why most of these certifications relate directly to those enormously popular platforms. 

It’s important to note that NoSQL databases – referred to as “not only SQL” and sometimes “non-relational” databases – handle many different types of data, such as structured, semi-structured, unstructured and polymorphic. NoSQL databases are increasingly used in big data applications, which tend to be associated with certifications for data scientists, data mining and warehousing, and business intelligence. Although there is some natural overlap, for the most part, we cover those certs in our annually updated “Best Big Data Certifications.” 

Before you look at our featured certifications in detail, consider their popularity with employers. The results of an informal search on several high-traffic job boards show which database certifications employers look for most when hiring. Though these results vary from day to day (and by job board), such numbers provide a useful perspective on database certification demand in current job listings.

Job board search results (in alphabetical order by certification)*

Certification

SimplyHired 

 Indeed 

 LinkedIn Jobs 

 LinkUp 

Total

IBM Certified Database Administrator – DB2

463

607

845

747

2,662

Microsoft SQL Server database certifications**

1,661

1,955

1,259

1,373

6,248

Oracle Certified Professional, MySQL Database Administrator

205

342

182

142

871

Oracle Database 12c Administrator

235

295

695

214

1,439

SAP HANA

101

150

84

80

415

*See our complete methodology for selecting top five certifications in the “Best Certifications” series.

**Combined totals for MCSA: SQL Database Administration (540), MCSA: SQL Database Development (569), MCSE: Data Management and Analytics (640) and MTA: Database (503).

If the sheer number of available database-related positions isn’t enough motivation to pursue a certification, consider average salaries for database administrators. SimplyHired reports $86,415 as the national average in the U.S., in a range from $60,960 to over $128,000. Glassdoor’s reported average is somewhat higher at $93,164, with a top rung for experienced, senior DBAs right around $135,000.

Top 5 database certifications

Now let’s look at the details of our top five database certification picks for 2020.

1. IBM Certified Database Administrator – DB2

IBM is one of the leaders in the worldwide database market by any objective measure. The company’s database portfolio includes industry standard DB2, as well as IBM Compose, Information Management System (IMS), lnformix, Cloudant and IBM Open Platform with Apache Hadoop. IBM also has a long-standing and well-populated IT certification program, which has been around for more than 30 years and encompasses hundreds of individual credentials. 

After redesigning its certification programs and categories, IBM’s major data-centric certification category is called IBM Data and AI, which includes a range of database credentials: Database Associate, Database Administrator, System Administrator, Application Developer and more. It’s a big and complex certification space, but one where particular platform allegiances are likely to guide readers straight to the handful of items that are relevant to their interests and needs. 

Database professionals who support DB2 (or aspire to) on Linux, Unix or Windows should check out the IBM Certified Database Administrator – DB2 certification. It’s an intermediate credential that addresses routine administration, basic SQL, and creation of databases and database objects, as well as server management, monitoring, availability and security. 

This certification requires candidates to pass two exams. Pre-exam training is recommended but not required.

IBM Certified Database Administrator – DB2 facts and figures

Certification name

IBM Certified Database Administrator – DB2 11.1 (Linux, UNIX and Windows)

Prerequisites and required courses

None required; recommended courses available

Number of exams

Two exams: IBM DB2 11.1 DBA for LUW (exam C2090-600) (60 questions, 90 minutes)

plus

DB2 11.1 Fundamentals for LUW (exam C2090-616) (63 questions, 90 minutes)

Cost per exam

$200 (or local currency equivalent) per test ($400 total). Sign up for exams at Pearson VUE.

URL

https://www.ibm.com/certify/cert?id=08002109

Self-study materials

Each test webpage provides test objectives, suggested training courses and links to study guides for sale through MC Press. Click the test Preparation tab for detailed information. You can also visit the Prepare for Your Certification Exam webpage.

2. Microsoft SQL Server database certifications 

SQL Server offers a broad range of tools and add-ons for business intelligence, data warehousing and data-driven applications of all kinds. That probably explains why Microsoft offers database-related credentials at every level of its certification program. 

Microsoft has taken significant steps over the last year to change its certification program from technology-focused to role-centric, centered on the skills one needs to be successful in specific technology jobs. With these changes in mind, Microsoft now identifies four job tracks in its certification program: Developers, Administrators, Solution Architects and Functional Consultants. You will find a wide variety of skills and technologies within each of those categories, but we’ll concentrate below on the company’s SQL Server certifications.

MTA: Database Fundamentals

The MTA program includes a single database-related exam: Database Fundamentals (98-364). This credential is ideal for students or as an entry-level cert for professionals looking to segue into database support.

MCSA

Microsoft offers several SQL-related credentials at the Microsoft Certified Solutions Associate (MCSA) level:

  • MCSA: SQL Server 2012/2014 (three exams)
  • MCSA: BI Reporting (two exams)
  • MCSA: SQL 2016 BI Development (two exams)
  • MCSA: SQL 2016 Database Administration (two exams)
  • MCSA: SQL 2016 Database Development (two exams)

MCSE

There is one SQL database credential at the Microsoft Certified Solutions Expert level: Data Management and Analytics. This certification has the MCSA as a prerequisite (a list of valid items follows in the table) and then requires passing one elective exam.

Microsoft SQL Server database certification facts and figures

Certification name

MTA: Database Fundamentals

MCSA: SQL Server 2012/2014

MCSA: BI Reporting 

MCSA: SQL 2016 BI Development

MCSA: SQL 2016 Database Administration

MCSA: SQL 2016 Database Development

MCSE: Data Management and Analytics

Prerequisites and required courses  

No prerequisites:

MTA: Database Fundamentals

MCSA: SQL Server 2012/2014

MCSA: BI Reporting

MCSA: SQL 2016 BI Development

MCSA: SQL 2016 Database Administration

MCSA: SQL 2016 Database Development

MCSE Data Management and Analytics prerequisites (only one required):

MCSA: SQL Server 2012/2014

MCSA: SQL 2016 BI Development

MCSA: SQL 2016 Database Administration

MCSA: SQL 2016 Database Development

MCSA: Machine Learning

MCSA: BI Reporting

MCSA: Data Engineering with Azure

Training courses are available and recommended for all certifications but not required.

Number of exams

MTA: Database Fundamentals: One exam

  • Database Fundamentals (98-364)

MCSA: BI Reporting: Two exams

  • Analyzing and Visualizing Data with Power BI (70-778)
  • Analyzing and Visualizing Data with Microsoft Excel (70-779)

MCSA: SQL Server: Three exams

  • Querying Microsoft SQL Server 2012/2014 (70-461)
  • Administering Microsoft SQL Server 2012/2014 Databases (70-462)  
  • Implementing a Data Warehouse with Microsoft SQL Server 2012/2014 (70-463

MCSA: SQL 2016 BI Development: Two exams

  • Implementing a SQL Data Warehouse (70-767)
  • Developing SQL Data Models (70-768) 

MCSA: SQL 2016 Database Administration: Two exams

  • Administering a SQL Database Infrastructure (70-764)
  • Provisioning SQL Databases (70-765) 

MCSA: SQL 2016 Database Development: Two exams

  • Querying Data with Transact-SQL (70-761)
  • Developing SQL Databases (70-762) 

MCSE: Data Management and Analytics: One test (from the following)

  • Developing Microsoft SQL Server Databases (70-464)
  • Designing Database Solutions for Microsoft SQL Server (70-465)
  • Implementing Data Models and Reports with Microsoft SQL Server (70-466)
  • Designing Business Intelligence Solutions with Microsoft SQL Server (70-467)
  • Developing SQL Databases (70-762)
  • Implementing a Data Warehouse Using SQL (70-767)
  • Developing SQL Data Models (70-768)
  • Analyzing Big Data with Microsoft R (70-773)
  • Implementing Microsoft Azure Cosmos DB Solutions (70-777

All exams administered by Pearson VUE.

Cost per exam

MTA: $127 (or equivalent in local currency outside the U.S.)

MCSA/MCSE: $185 (or equivalent) per exam

URL

www.microsoft.com/learning/en-us/certification-overview.aspx

Self-study materials

Microsoft offers one of the world’s largest and best-known IT certification programs, so the MTA, MCSA and MCSE certs are well supported with books, study guides, study groups, practice exams and other materials.

3. Oracle Certified Professional, MySQL 5.7 Database Administrator 

Oracle runs its certifications under the auspices of Oracle University. The Oracle Database Certifications page lists separate tracks for Database Application Development (SQL and PL/SQL), MySQL (Database Administration and Developer) and Oracle Database (versions 12c, 12c R2, and 11g, and Oracle Spatial 11g). 

MySQL is perhaps the leading open-source relational database management system (RDBMS). Since acquiring Sun Microsystems in 2010 (which had previously acquired MySQL AB), Oracle has rolled out a paid version of MySQL and developed certifications to support the product. 

A candidate interested in pursuing an Oracle MySQL certification can choose between MySQL Database Administration and MySQL Developer. The Oracle Certified Professional, MySQL 5.7 Database Administrator (OCP) credential recognizes professionals who can install, optimize and monitor MySQL Server; configure replication; apply security; and schedule and validate database backups. 

The certification requires candidates to pass a single test (the same test can be taken to upgrade a prior certification). Oracle recommends training and on-the-job experience before taking the exam.

Oracle Certified Professional, MySQL 5.7 Database Administrator facts and figures

4. Oracle Database 12c Administrator

Most Oracle DBMS credentials require candidates to attend authorized training classes to qualify for the related exam, but MySQL (and Sun-derived) credentials often do not. Oracle certifications also represent a true ladder, in that it is generally necessary to earn the associate-level credentials first, professional-level credentials second and master-level credentials third, culminating with the expert level. 

Oracle Database 12c R2 is the latest version, which includes enhancements to Oracle Database 12c. Oracle 12c certifications are currently offered at the associate, professional and master levels. 

A Foundations Junior Associate certification (novice level) is also available for Oracle Database 12c, as are three specialist designations: the Implementation Specialist, the Oracle Database Performance and Tuning 2015 Certified Implementation Specialist, and the Oracle Real Application Clusters 12c Certified Implementation Specialist. 

Available expert-level credentials include the Oracle Certified Expert; Oracle Database 12c: RAC and Grid Infrastructure Administrator; Oracle Database 12c Maximum Availability Certified Expert; Oracle Certified Expert; Oracle Database 12c: Data Guard Administrator; Oracle Certified Expert; and Oracle Database 12c: Performance Management and Tuning. Oracle still offers 11g certifications as well. 

NoteAlthough premium support for Oracle 11g Database ended on Dec. 31, 2014, extended support lasts until December 2020, so it’s probable that Oracle Database 11g will remain in use for the short term. 

We focused on requirements for Oracle Database 12c certifications. One important consideration is that Oracle 11g is forward-compatible with Oracle 12c, but Oracle 12c is not backward- compatible with the prior version. Because Oracle 12c is a newer version, IT professionals with Oracle 11g certifications should consider upgrading their 11g credentials.

Oracle Database 12c Administrator facts and figures

Certification name

Oracle Database 12c Administrator Certified Associate (OCA 12c)

Oracle Database 12c Administrator Certified Professional (OCP 12c)

Oracle Database 12c Administrator Certified Master (OCM 12c)

Oracle Database 12c Maximum Availability Certified Master

Prerequisites and required courses

OCA 12c: Training recommended but not required

OCP 12c: OCA 12c credential and one training course required; complete course submission form

OCM 12c: OCP 12c or 12c R2 credential and two advanced training courses (must be different from the course used to achieve the OCP); complete course submission form; submit fulfillment kit request

Oracle Database 12c Maximum Availability Certified Master: Three credentials

  • Oracle Database 12c Administrator Certified Master
  • Oracle Certified Expert, Oracle Database 12c: RAC and Grid Infrastructure Administration
  • Oracle Certified Expert, Oracle Database 12c: Data Guard Administration

Oracle training: Classes typically run 2-5 days; costs range from $1,360 to over $5,580.

Number of exams

 OCA 12c: Choose one test from the following:

  • Oracle Database 12c SQL (1Z0-071) (73 questions, 100 minutes)
  • Oracle Database 12c: Installation and Administration (1Z0-062) (67 questions, 120 minutes)

OCP 12c: One exam: Oracle Database 12c: Advanced Administration (1Z0-063) (80 questions, 120 minutes)

OCM 12c: One exam: Oracle Database 12c Certified Master (12COCM), a two-day, performance-based exam

Oracle Database 12c Maximum Availability Certified Master: None

Cost per exam

OCA 12c: 1Z0-071and 1Z0-062 cost $245 each.

OCP 12c: 1Z0-063, 1Z0-082 and 1Z0-083 cost $245 each

OCM 12c: 12COCM costs $2,584; contact Oracle for pricing/availability of upgrade exam.

Oracle Database 12c Maximum Availability Certified Master: None

Note: Prices vary by geography.

URL

https://education.oracle.com/pls/web_prod-plq-dad/ou_product_category.getFamilyPage?p_family_id=32&p_mode=Certification

Self-study materials

Each Oracle certification test webpage lists test subjects as well as recommended training courses, seminars and practice tests. A variety of self-study guides are available on Amazon. Oracle Database certification candidates benefit from student manuals, labs and software provided as part of class offerings.

5. SAP HANA: SAP Certified Technology Associate – SAP HANA (Edition 2016)

SAP SE has a large portfolio of business application and analytics software, including cloud infrastructure, applications, and storage. The foundation of the SAP HANA platform is an enterprise-grade relational database management system, which can be run as an appliance on premises or in the cloud. The cloud platform enables customers to build and run applications and services based on SAP HANA. 

SAP offers a comprehensive certification program, built to support its various platforms and products. We chose to feature the SAP Certified Technology Associate – SAP HANA cert because it aligns closely with other certifications in this article and is in high demand among employers, according to our job board surveys. This certification ensures that database professionals can install, manage, monitor, migrate and troubleshoot SAP HANA systems. It covers managing users and authorization, applying security, and ensuring high availability and effective disaster recovery techniques. 

SAP recommends that certification candidates get hands-on practice through formal training or on-the-job experience before attempting this exam. The SAP Learning Hub is a subscription service that gives certification candidates access to a library of learning materials, including e-learning courses and course handbooks. The annual subscription rate for individual users on the Professional certification track is $3,048. This online training program is designed for those who run, support or implement SAP software solutions. Though this may seem like a steep price for online training, you will likely be able to pass any SAP certification exams you put your mind to by leveraging all of the learning resources available to SAP Learning Hub Professional subscribers. 

Typically, SAP certifications achieved on one of the two most recent SAP solutions are considered current and valid. SAP contacts professionals whose certifications are nearing end of life and provides information on maintaining their credentials.

SAP Certified Technology Associate facts and figures

Certification name

SAP Certified Technology Associate – SAP HANA (Edition 2016)

Prerequisites  and required courses        

 None required

 Recommended: SAP HANA Installation & Operations SPS12 (HA200) course ($3,750)

Number of exams

One exam: SAP Certified Application Associate – SAP HANA (Edition 2016), test code C_HANATEC_12 (80 questions, 180 minutes)

Cost per exam

$552

URL

https://training.sap.com/certification/c_hanatec_12-sap-certified-technology-associate—sap-hana-edition-2016-g/

Self-study materials

The certification webpage includes a link to sample questions. SAP HANA trade books and certification guides are available on Amazon. The SAP Help Center offers product documentation and a training and certification FAQs page. The SAP Learning Hub (available on a subscription basis) provides access to online learning content.

Beyond the top 5: More database certifications

Besides the ones mentioned in this article, other database certification programs are available to further the careers and professional development of IT professionals who work with database management systems. 

While most colleges with computer science programs offer database tracks at the undergraduate, master and Ph.D. levels, there are few well-known vendor-neutral database certifications. The Institute for the Certification of Computing Professionals (ICCP) is part of this unique group, offering its Certified Data Professional and Certified Data Scientist credentials. Find out more about ICCP certifications here

EnterpriseDB administers a small but effective certification program, with two primary certs: the EDB Certified Associate and the EDB Certified Professional. PostgreSQL was the fourth-ranked relational database management system in October 2019, according to DB-Engines

Credentials from GoogleMarkLogicTeradata and SAS may also be worth considering. All of these credentials represent opportunities for database professionals to expand their skill sets – and salaries. However, such niches in the database certification arena are generally only worth pursuing if you already work with these platforms or plan to work for an organization that uses them. 

Ed Tittel

Ed is a 30-year-plus veteran of the computing industry, who has worked as a programmer, a technical manager, a classroom instructor, a network consultant, and a technical evangelist for companies that include Burroughs, Schlumberger, Novell, IBM/Tivoli and NetQoS. He has written for numerous publications, including Tom’s IT Pro and GoCertify, and is the author of more than 140 computing books on information security, web markup languages and development tools, and Windows operating systems. 

Earl Follis

Earl is also a 30-year veteran of the computer industry, who has worked in IT training, marketing, technical evangelism, and market analysis in the areas of networking and systems technology and management. Ed and Earl met in the late 1980s when Ed hired Earl as a trainer at an Austin-area networking company that’s now part of HP. The two of them have written numerous books together on NetWare, Windows Server and other topics. Earl is also a regular writer for the computer trade press, with many e-books, whitepapers and articles to his credit.

Mon, 10 Oct 2022 12:01:00 -0500 en text/html https://www.businessnewsdaily.com/10734-database-certifications.html
Killexams : Healthcare Operational Analytics Market Expected to rise Significantly| IBM, Cerner, Oracle

Healthcare Operational Analytics

The latest release from WMR titled Healthcare Operational Analytics Market Research Report 2022-2029 contains all relevant information and Growth Factors. Providing its clients with accurate data, it provides the market outlook and helps in the making of crucial decisions. The market is described in general terms, along with its definition, uses, advancements, and production technology. This market research report on Healthcare Operational Analytics keeps tabs on all emerging advancements and changes in the industry. It provides information on the challenges faced when starting a business and offers advice on how to deal with impending difficulties. Healthcare Operational Analytics Market Research with 100+ market data Tables, Pie Chat, Graphs & Figures is now released BY WMR.

Ask For sample Report: https://www.worldwidemarketreports.com/sample/817083

The research offers a thorough analysis of the market, taking into consideration important factors including projected sales, cost analysis, import/export, production and consumption trends, CAGR, gross margin, and supply and demand trends. Additionally, it highlights current technological improvements, product innovations, and R&D initiatives in the area.

Analysis By Key Players:

◘ IBM
◘ Cerner
◘ Oracle
◘ McKesson
◘ MedeAnalytics
◘ Optum
◘ Allscripts
◘ Truven Health Analytics
◘ Verisk Analytics
◘ Vizient

Analysis By Type

◘ Supply chain analytics
◘ Human resource analytics
◘ Strategic analytics

Analysis By Application

◘ Healthcare
◘ Pharmaceuticals
◘ Biotechnology
◘ Research

Market Scenario:

The Healthcare Operational Analytics research report provides an overview of the market, covering definition, applications, product launches, developments, challenges, and geographical regions. Forecasts indicate that the industry will demonstrate high growth due to increased demand in many markets. The Healthcare Operational Analytics study offers an analysis of the market designs currently in use as well as other fundamental aspects.

If you have any queries related to the Healthcare Operational Analytics market report, you can ask our expert: https://www.worldwidemarketreports.com/quiry/817083

𝐓𝐡𝐢𝐬 𝐫𝐞𝐩𝐨𝐫𝐭 𝐚𝐢𝐦𝐬 𝐭𝐨 𝐩𝐫𝐨𝐯𝐢𝐝𝐞:

📌 An examination of the dynamics, trends, and projections for the years 2022 through 2029, both qualitatively and quantitatively.
📌 The ability of the customers and suppliers to make financially advantageous decisions and expand their businesses is explained by the use of analysis techniques like SWOT analysis and Porter’s five force analysis.
📌 The detailed research of market segmentation helps in identifying the current market opportunities.
📌 By collecting unbiased information under one roof, our Healthcare Operational Analytics report ultimately helps you save time and money.

𝐑𝐞𝐠𝐢𝐨𝐧-𝐖𝐢𝐬𝐞 𝐂𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐭𝐡𝐞 Healthcare Operational Analytics Market:

◘ The Middle East and Africa (Turkey, GCC Countries, Egypt, South Africa)

◘ North America (United States, Mexico, and Canada)

◘ South America (Brazil etc.)

◘ Europe (Germany, Russia, UK, Italy, France, etc.)

◘ Asia-Pacific (Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)

👉 𝐊𝐞𝐲 𝐈𝐧𝐝𝐢𝐜𝐚𝐭𝐨𝐫𝐬 𝐀𝐧𝐚𝐥𝐲𝐬𝐞𝐝

Market Players & Competitor Analysis: The report covers the key players of the industry including Company Profile, Product Specifications, Production Capacity/Sales, Revenue, Price, and Gross Margin & Sales with a thorough analysis of the market’s competitive landscape and detailed information on vendors and comprehensive details of factors that will challenge the growth of major market vendors.

👉 𝐑𝐞𝐠𝐢𝐨𝐧𝐚𝐥 𝐌𝐚𝐫𝐤𝐞𝐭 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬:
 The report includes the & Regional market status and outlook Further the report provides breakdown details about each region & country covered in the report. Identifying its sales, sales volume & revenue forecast. With detailed analysis by types and applications.

👉 𝐌𝐚𝐫𝐤𝐞𝐭 𝐓𝐫𝐞𝐧𝐝𝐬:
 Market key trends include Increased Competition and Continuous Innovations.

👉 𝐎𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐢𝐞𝐬 𝐚𝐧𝐝 𝐃𝐫𝐢𝐯𝐞𝐫𝐬:
Identifying the Growing Demands and New Technology

👉 𝐏𝐨𝐫𝐭𝐞𝐫’𝐬 𝐅𝐢𝐯𝐞 𝐅𝐨𝐫𝐜𝐞 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬:
 The report provides the state of competition in the industry depends on five basic forces: the threat of new entrants, the bargaining power of suppliers, the bargaining power of buyers, the threat of substitute products or services, and existing industry rivalry.

Healthcare Operational Analytics Market 𝐓𝐚𝐛𝐥𝐞 𝐎𝐟 𝐂𝐨𝐧𝐭𝐞𝐧𝐭:

1. Healthcare Operational Analytics Market Introduction
1.1.Definition
1.2.Research Scope

2. Executive Summary
2.1.Key Findings by Major Segments
2.2.Top strategies by Major Players

3. Global Healthcare Operational Analytics Market Overview
3.1.Healthcare Operational Analytics Market Dynamics
3.1.1.Drivers
3.1.2.Opportunities
3.1.3.Restraints
3.1.4.Challenges
3.2.COVID-19 Impact Analysis in Global Healthcare Operational Analytics Market
3.3.PESTLE Analysis
3.4.Opportunity Map Analysis
3.5.PORTER’S Five Forces Analysis
3.6.Market Competition Scenario Analysis
3.7.Product Life Cycle Analysis
3.8.Manufacturer Intensity Map
3.9.Major Companies sales by Value & Volume

𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐞…

𝐓𝐡𝐞 𝐟𝐨𝐥𝐥𝐨𝐰𝐢𝐧𝐠 𝐚𝐫𝐞 𝐭𝐡𝐞 𝐩𝐫𝐢𝐦𝐚𝐫𝐲 𝐫𝐞𝐚𝐬𝐨𝐧𝐬 𝐭𝐨 𝐩𝐮𝐫𝐜𝐡𝐚𝐬𝐞 𝐭𝐡𝐞 Healthcare Operational Analytics Market report:

📌  The global Healthcare Operational Analytics market research analysis provides exact and thorough insightful insights on industry trends, allowing businesses to make useful and smart decisions to gain a competitive advantage over the competition.
📌 It provides a complete analysis of the Healthcare Operational Analytics market as well as the most recent rising industry trends in the global Healthcare Operational Analytics market.
📌 The global Healthcare Operational Analytics market is comprised of valuable suppliers, industry trends, and massive movement in demand from 2022 to 2029.

𝐂𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧

Finally, the global Healthcare Operational Analytics market report provides a systematic and descriptive analysis of the Healthcare Operational Analytics market, supported by historical and current information of key players and vendors, and all of the factors mentioned above, as well as potential future developments, to help in gaining critical insights regarding revenue, volume, and others, which could benefit clients in business-related decisions.

𝐁𝐮𝐲 𝐓𝐡𝐢𝐬 𝐏𝐫𝐞𝐦𝐢𝐮𝐦 𝐑𝐞𝐩𝐨𝐫𝐭 𝐔𝐩𝐭𝐨 𝟕𝟎% 𝐃𝐢𝐬𝐜𝐨𝐮𝐧𝐭 𝐚𝐭: https://www.worldwidemarketreports.com/promobuy/817083

𝐂𝐨𝐧𝐭𝐚𝐜𝐭 𝐮𝐬:

Worldwide Market Reports
Tel: +1 415 871 0703
Email: [email protected]
Visit our news Website: www.worldwidemarketreports.com

Wed, 12 Oct 2022 02:33:00 -0500 Coherent Market Insights en-US text/html https://www.digitaljournal.com/pr/healthcare-operational-analytics-market-expected-to-rise-significantly-ibm-cerner-oracle
Killexams : CUET UG 2022: All you need to know about the test format, history & concerns

The National Testing Agency (NTA) released results of the maiden Common University Entrance Test for Undergraduate (CUET-UG) admissions late on Thursday night with almost 20,000 candidates scoring 100percentile in around 30 subjects.

The union government had in March announced that it will conduct CUET-UG, in line with the National Education Policy (NEP) 2020, and made its score a mandatory yardstick for all central universities while keeping it optional for others.

At least 90 universities are participating in the CUET-UG this year.

While the NTA– an autonomous testing agency under the union ministry of education was entrusted to conduct the exam–, the higher education regulation University Grants Commission (UGC) worked as its nodal agency for the exam.

Also Read: CUET results: Social media users question delay

The debut edition of CUET-UG was conducted in six phases between July 15 and August 30 across 489 examination centres located in 259 cities across India and 10 cities abroad.

A total of 14,90,000 candidates had registered for the examination that witnessed 60% consolidated attendance in all six phases.

HT here explains the journey of CUET-UG 2022:

Origin of CUET

In 2010, the government had set up 12 new central universities across the country, and introduced a common entrance test known as Central University Common Entrance Test (CUCET) for them. Till 2021, those 12 central universities, including central universities of Gujarat, Haryana, Kerala Jammu and Punjab, were conducting admissions through it.

Later in 2020, when NEP was launched, it envisaged a common entrance test for all universities. To implement the policy recommendations, the UGC had in 2020 set up a seven-member committee headed by VC of Central University of Punjab, RP Tiwari, to prepare the modalities for the common entrance exam.

After several rounds of discussion. UGC submitted its recommendations in December 2020 and suggested implementing them from 2021-22.

However, the UGC had put it on hold in view of the challenges posed by the Covid-19 pandemic.

In March this year, UGC announced the implementation of the test under the title CUET from the session 2022-23 and made it the sole criterion for admission to undergraduate courses in all central universities.

Until now, many universities were either enrolling students on the basis of their class 12 performance or were conducting their individual entrance exams.

Why a common entrance exam?

While introducing CUET-UG, the UGC had said it would reduce the burden of students. “The students right now are applying to different universities and appearing in different entrance exams for undergraduate admissions. At the same time, they also have to focus on their board exams to get 99% and 100% marks. We should not assume that all central universities were conducting admissions on the basis of class 12 marks. Many universities have already been conducting their individual entrance exams for undergraduate admissions. Multiple exams were causing a lot of stress not just among the students but also their parents,” UGC Chairperson M Jagadesh Kumar had said.

“Another reason why the NEP 2020 advocated for a ‘one nation one entrance exam’ is to provide equal opportunity to students from different backgrounds and different education boards. It will provide a kind of level playing ground for the students,” he had said.

The criticism

A section of students, parents, teachers and principal raised concerns over making CUET-UG the sole criteria for undergraduate admissions. They argued that not giving any weightage to class 12 marks in the admission process will make board exams “irrelevant”. Another criticism was on the syllabus of CUCET-UG as it was “strictly” based on NCERT syllabus. People questioned how it would provide equal opportunity to students from other boards, ISC or state boards. Lastly, there were apprehensions that CUET may also mutate into a coaching driven competition like most entrance exams are in the country.

Exam pattern

The CUET-UG was a computer-based test and was conducted in multiple choice questions (MCQ) format. It was divided into four sections namely, I-A, I-B, II, and III. Section I-A and I-B consisted of language subjects. Section II was domain specific and section III was a general test.

A candidate was allowed to choose a maximum of any three languages from Section I-A and Section I-B together, and up to six domain subjects. It means, overall, candidates could take a test in a maximum of nine subjects, i.e., two languages + six domain specific subjects + one general test or three languages + five domain specific subjects + one general test.

The test will be strictly based on the class 12 NCERT syllabus.

The hiccups

The exam, which was initially planned in two phases, had to be conducted in six phases due to multiple cancellations and postponement of papers after technical issues were reported at the examination centres. While the first phase was conducted in July, the remaining five phases were held throughout August. The initial phases of CUET were marred with technical and administrative glitches. While on August 4, all exams scheduled in the evening shift were cancelled at all 489 centres across the country, 50 and 53 centres were affected on August 5 and 6, respectively.

However, the NTA rescheduled exams for all affected students and extended the dates till August 30.

How CUET-UG was different from NEET, JEE?

In case of both, the National Eligibility Criteria Test (NEET) for admission to medical courses, and the Joint Entrance test (JEE) for engineering admissions, there are no subject combinations. It is either Physics, Chemistry and Mathematics or Physics, Chemistry and Biology and everybody takes these combinations only.

However, in CUET-UG, each of the 1.49lakh candidates had applied for at least five universities choosing around 54,000 subject combinations. That makes CUET-UG a big exercise.

What next?

The NTA will provide universities with the CUET-UG scores of students who have applied for admission to that particular university. The universities will then prepare their individual cut-off list using those scores and conduct their counseling sessions for admission. Students will have to visit the admission portal of the universities they have applied for and complete the registration process.

Meanwhile, the government is likely to conduct CUET-UG twice next year– one in March-April and the other in November-December – to provide more opportunities to students.

Thu, 15 Sep 2022 23:38:00 -0500 en text/html https://www.hindustantimes.com/education/exam-results/cuet-ug-2022-all-you-need-to-know-about-the-exam-format-history-concerns-101663308537181.html
Killexams : Manufacturing Predictive Analytics Market 2022 To 2028, Top Companies Booming Strategies, Progression Status, and Business Trends.

The MarketWatch News Department was not involved in the creation of this content.

Oct 13, 2022 (Reportmines via Comtex) -- Pre and Post Covid is covered and Report Customization is available.

The "Manufacturing Predictive Analytics Market" is one of the sectors that is expanding the fastest, thus it is crucial for players in the market to first do an exhaustive analysis of the sector. This list of companies IBM,Microsoft,Oracle,SAS,Cambridge Analytica,Civis Analytics,RapidMiner,SAP,Alteryx,Bridgei2i Analytics Solutions,Cisco Systems,FICO,Tibco Software is one of the principal market rivals, according to the research. The research covers the market for Manufacturing Predictive Analytics extensively, as well as the significant market developments and the coronavirus's consequences. The Manufacturing Predictive Analytics Market Research Report and Industry Analysis examine the worldwide 2022 to 2028 market for the Manufacturing Predictive Analytics industry. The market report includes data on supply, application-specifics, price patterns, historical and anticipated market statistics, and firm shares of the region's top-ranking Manufacturing Predictive Analytics market. Market segmentation exists. The total number of pages in this report is 128.

The global Manufacturing Predictive Analytics market size is projected to reach multi million by 2028, in comparision to 2021, at unexpected CAGR during 2022-2028 (Ask for sample Report).

The research covers the market for Manufacturing Predictive Analytics in great detail, as well as the significant market developments and the consequences of the coronavirus. Demand, application-specific details, price patterns, historical and anticipated market statistics, and firm shares of the top-ranking Manufacturing Predictive Analytics market by region are all included in the market study. It includes a comprehensive analysis of the market for Manufacturing Predictive Analytics by price, income stream, kind, approach, location, etc. Based on application, the market is divided into Automotive,Aerospace,Building Construction,Chemical,Others segments. The geographic breakdown includes the regions North America: United States, Canada, Europe: GermanyFrance, U.K., Italy, Russia,Asia-Pacific: China, Japan, South, India, Australia, China, Indonesia, Thailand, Malaysia, Latin America:Mexico, Brazil, Argentina, Colombia, Middle East & Africa:Turkey, Saudi, Arabia, UAE, Korea, and each of the previously mentioned segments is examined. Based on type, the market is segmented into Software,Hardware,Other Services submarkets. The report divides the market size into segments based on region, application type, volume, and value. The Manufacturing Predictive Analytics market study finishes with an in-depth examination of a leading Manufacturing Predictive Analytics market's profile and statistics.

Get sample PDF of Manufacturing Predictive Analytics Market Analysis https://www.predictivemarketresearch.com/enquiry/request-sample/1632998

Market Segmentation

The worldwide Manufacturing Predictive Analytics Market is categorized on Component, Deployment, Application, and Region.

In terms of Components, the Manufacturing Predictive Analytics Market is segmented into:

  • IBM
  • Microsoft
  • Oracle
  • SAS
  • Cambridge Analytica
  • Civis Analytics
  • RapidMiner
  • SAP
  • Alteryx
  • Bridgei2i Analytics Solutions
  • Cisco Systems
  • FICO
  • Tibco Software

The Manufacturing Predictive Analytics Market Analysis by types is segmented into:

  • Software
  • Hardware
  • Other Services

The Manufacturing Predictive Analytics Market Industry Research by Application is segmented into:

  • Automotive
  • Aerospace
  • Building Construction
  • Chemical
  • Others

In terms of Region, the Manufacturing Predictive Analytics Market Players available by Region are:

  • North America:
  • Europe:
    • Germany
    • France
    • U.K.
    • Italy
    • Russia
  • Asia-Pacific:
    • China
    • Japan
    • South Korea
    • India
    • Australia
    • China Taiwan
    • Indonesia
    • Thailand
    • Malaysia
  • Latin America:
    • Mexico
    • Brazil
    • Argentina Korea
    • Colombia
  • Middle East & Africa:
    • Turkey
    • Saudi
    • Arabia
    • UAE
    • Korea

Inquire or Share Your Questions If Any Before Purchasing This Report - https://www.predictivemarketresearch.com/enquiry/pre-order-enquiry/1632998

Key Benefits for Industry Participants & Stakeholders

This Manufacturing Predictive Analytics market research report contains all pertinent basic information about the Manufacturing Predictive Analytics industry, including market size, trends, competitors, and other important Manufacturing Predictive Analytics market essential elements. The market research forecast closely examines the market size for the Manufacturing Predictive Analytics, including market volume and value.

The Manufacturing Predictive Analytics market research report contains the following TOC:

  • Report Overview
  • Global Growth Trends
  • Competition Landscape by Key Players
  • Data by Type
  • Data by Application
  • North America Market Analysis
  • Europe Market Analysis
  • Asia-Pacific Market Analysis
  • Latin America Market Analysis
  • Middle East & Africa Market Analysis
  • Key Players Profiles Market Analysis
  • Analysts Viewpoints/Conclusions
  • Appendix

Get a sample of TOC https://www.predictivemarketresearch.com/toc/1632998#tableofcontents

Highlights of The Manufacturing Predictive Analytics Market Report

The Manufacturing Predictive Analytics Market Industry Research Report contains:

  • It is a detailed analysis of the Manufacturing Predictive Analytics market, considering the possibility for future industry expansion.
  • It completes the analysis of market trends, which is crucial for finding untapped opportunities.
  • The Future innovations and other R&D projects can be predicted with its assistance.
  • It provides a complete analysis of market share information for the Manufacturing Predictive Analytics.
  • In today's intensely competitive industry, the Manufacturing Predictive Analytics market research study clearly illustrates which new goods or services would be the most lucrative.

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COVID 19 Impact Analysis

Covid-19 had detrimental effects on a number of businesses, including the market for Manufacturing Predictive Analytics as well as on people's health. However, the Manufacturing Predictive Analytics business has already started to flourish and regain its pre-covid status. The Manufacturing Predictive Analytics Research Report provides a complete analysis of the Manufacturing Predictive Analytics market as well as the challenges that market participants are now dealing with as a result of the epidemic.

Get Covid-19 Impact Analysis for Manufacturing Predictive Analytics Market research report https://www.predictivemarketresearch.com/enquiry/request-covid19/1632998

Manufacturing Predictive Analytics Market Size and Industry Challenges

  • In this market analysis, our attention was drawn to the many difficulties and issues facing Manufacturing Predictive Analyticsmarket players.
  • In this research study, the size of the Manufacturing Predictive Analytics market is also highlighted.
  • Its main objective is to debate the biggest global marketing issues. Businesses can learn about potential areas for development and factors impeding progress thanks to their thorough Manufacturing Predictive Analytics market research.
  • The company's issues are also highlighted in the Manufacturing Predictive Analytics Market Research.
  • Major producers, well-known geographic areas, and product categories are used to segment the Manufacturing Predictive Analytics market.

Reasons to Purchase the Manufacturing Predictive Analytics Market Report

  • Investors and experts may get findings for the Manufacturing Predictive Analytics sector in the future with the help of this market study.
  • It learns crucial information on market size and market share for the Manufacturing Predictive Analytics market.
  • It provides you with crucial details about the competitors in the Manufacturing Predictive Analytics industry.
  • A part on market analysis by product type is also included in the Manufacturing Predictive Analytics market research.
  • It includes a thorough analysis of the market, industry trends, and important items for the Manufacturing Predictive Analytics market.

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Killexams : IBM Planning Analytics (TM1) Consultant/Developer at Datafin Recruitment – Western Cape Bellville

ENVIRONMENT:

A leading provider of Financial Performance Management solutions seeks a strong technical IBM Planning Analytics (TM1) Consultant/Developer to build TM1 cubes, dimensions and rules and setup ETL processes while also engaging with clients to understand their requirements. You will support the existing client base, as well as implement new solutions at new clients. The successful incumbent must at least have 1st-year tertiary level in Accounting and Information Systems or Computer Science. You will require 3+ years’ experience building TM1 models and dealt with clients, 2+ years’ experience & understanding of SQL fundamentals and able to write complex SQL queries and 2+ years’ Excel and VBA. You also need a strong understanding of the fundamentals of financial accounting, systems design and implementation.

DUTIES:

  • Engage with clients and understand client requirements.
  • Document business requirements, functional specifications and technical specifications.
  • Build TM1 cubes, dimensions and rules and setup ETL processes.
  • Design and develop input templates and reports using Excel and VBA.
  • Design and develop management reports, dashboards and scorecards.
  • Design and develop financial budgeting and forecasting systems.
  • Client training, on-going maintenance, and support.

REQUIREMENTS:

  • 3+ Years’ experience in building TM1 models and dealing with clients.
  • 2+ Years’ experience and understanding of SQL fundamentals and ability to write complex SQL queries.
  • 2+ Years’ experience in MS Excel and VBA.
  • Strong understanding of the fundamentals of financial accounting, systems design and implementation.
  • Demonstrable programming skills.
  • A minimum 1st-year tertiary level in Information systems or Computer Science.
  • A minimum of 1st-year tertiary level in Accounting.

ATTRIBUTES:

  • Excellent technical skills
  • Strong problem-solving abilities.
  • Excellent communication skills with the ability to interact with clients at all levels of the organisation.

While we would really like to respond to every application, should you not be contacted for this position within 10 working days please consider your application unsuccessful.

COMMENTS:

When applying for jobs, ensure that you have the minimum job requirements. OnlySA Citizens will be considered for this role. If you are not in the mentioned location of any of the jobs, please note your relocation plans in all applications for jobs and correspondence. Please e-mail a word copy of your CV to [Email Address Removed] and mention the reference numbers of the jobs. We have a list of jobs on [URL Removed] Datafin IT Recruitment – Cape Town Jobs.

Desired Skills:

Learn more/Apply for this position

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Killexams : Data Analytics in L & H Insurance Market to Witness Huge Growth by 2028 : IBM, Deloitte, SAP

Data Analytics in L & H Insurance Market 2022-2028

This press release was orginally distributed by SBWire

Pune, Maharashtra — (SBWIRE) — 10/08/2022 — The Latest research study released by HTF MI "Data Analytics in L & H Insurance Market" with 100+ pages of analysis on business Strategy taken up by key and emerging industry players and delivers know how of the current market development, landscape, technologies, drivers, opportunities, market viewpoint and status. Understanding the segments helps in identifying the importance of different factors that aid the market growth. Some of the Major Companies covered in this Research are Deloitte, SAP AG, LexisNexis, IBM, Verisk Analytics, Pegasystems, Oracle, OpenText, Majesco, SAS, TIBCO Software, Prima Solutions, Qlik, Global IQX, Earnix & Atidot etc.

Click here for free sample + related graphs of the report @: https://www.htfmarketreport.com/sample-report/3354367-data-analytics-in-l-h-insurance-market

Browse market information, tables and figures extent in-depth TOC on "Data Analytics in L & H Insurance Market by Application (Predictive Analysis, Demographic Profiling, Data Visualization & Others), by Product Type (, Service & Software), Business scope, Manufacturing and Outlook – Estimate to 2027".

for more information or any query mail at [email protected]

At last, all parts of the Data Analytics in L & H Insurance Market are quantitatively also subjectively valued to think about the Global just as regional market equally. This market study presents basic data and true figures about the market giving a deep analysis of this market based on market trends, market drivers, constraints and its future prospects. The report supplies the worldwide monetary challenge with the help of Porter's Five Forces Analysis and SWOT Analysis.

If you have any Enquiry please click here @: https://www.htfmarketreport.com/enquiry-before-buy/3354367-data-analytics-in-l-h-insurance-market

Customization of the Report: The report can be customized as per your needs for added data up to 3 businesses or countries .
On the basis of report- titled segments and sub-segment of the market are highlighted below:
Data Analytics in L & H Insurance Market By Application/End-User (Value and Volume from 2022 to 2027) : Predictive Analysis, Demographic Profiling, Data Visualization & Others

Market By Type (Value and Volume from 2022 to 2027) : , Service & Software

Data Analytics in L & H Insurance Market by Key Players: Deloitte, SAP AG, LexisNexis, IBM, Verisk Analytics, Pegasystems, Oracle, OpenText, Majesco, SAS, TIBCO Software, Prima Solutions, Qlik, Global IQX, Earnix & Atidot
Geographically, this report is segmented into some key Regions, with manufacture, depletion, revenue (million USD), and market share and growth rate of Data Analytics in L & H Insurance in these regions, from 2017 to 2027 (forecast), covering China, USA, Europe, Japan, Korea, India, Southeast Asia & South America and its Share (%) and CAGR for the forecasted period 2022 to 2027

Informational Takeaways from the Market Study: The report Data Analytics in L & H Insurance matches the completely examined and evaluated data of the noticeable companies and their situation in the market considering impact of Coronavirus. The measured tools including SWOT analysis, Porter's five powers analysis, and assumption return debt were utilized while separating the improvement of the key players performing in the market.

Key Development's in the Market: This segment of the Data Analytics in L & H Insurance report fuses the major developments of the market that contains confirmations, composed endeavors, R&D, new thing dispatch, joint endeavours, and relationship of driving members working in the market.

To get this report buy full copy @: https://www.htfmarketreport.com/buy-now?format=1&report=3354367

Some of the important question for stakeholders and business professional for expanding their position in the Data Analytics in L & H Insurance Market :
Q 1. Which Region offers the most rewarding open doors for the market Ahead of 2021?
Q 2. What are the business threats and Impact of latest scenario Over the market Growth and Estimation?
Q 3. What are probably the most encouraging, high-development scenarios for Data Analytics in L & H Insurance movement showcase by applications, types and regions?
Q 4.What segments grab most noteworthy attention in Data Analytics in L & H Insurance Market in 2020 and beyond?
Q 5. Who are the significant players confronting and developing in Data Analytics in L & H Insurance Market?

For More Information Read Table of Content @: https://www.htfmarketreport.com/reports/3354367-data-analytics-in-l-h-insurance-market

Key poles of the TOC:
Chapter 1 Data Analytics in L & H Insurance Market Business Overview
Chapter 2 Major Breakdown by Type [, Service & Software]
Chapter 3 Major Application Wise Breakdown (Revenue & Volume)
Chapter 4 Manufacture Market Breakdown
Chapter 5 Sales & Estimates Market Study
Chapter 6 Key Manufacturers Production and Sales Market Comparison Breakdown
…………………..
Chapter 8 Manufacturers, Deals and Closings Market Evaluation & Aggressiveness
Chapter 9 Key Companies Breakdown by Overall Market Size & Revenue by Type
………………..
Chapter 11 Business / Industry Chain (Value & Supply Chain Analysis)
Chapter 12 Conclusions & Appendix

Thanks for memorizing this article; you can also get an individual chapter-wise sections or region-wise report versions like North America, LATAM, Europe, or Southeast Asia.

Contact Us :
Craig Francis (PR & Marketing Manager)
HTF Market Intelligence Consulting Private Limited
Phone: +1 (434) 299-0043
[email protected]

For more information on this press release visit: http://www.sbwire.com/press-releases/data-analytics-in-l-h-insurance-market-to-witness-huge-growth-by-2028-ibm-deloitte-sap-1364486.htm

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Killexams : Marketing Analytics Market Competitive Insights 2022: IBM Corporation,Microsoft Corporation

(MENAFN- Ameliorate Digital Consultancy)

Market insights reports recently added a new report on Global Marketing Analytics Market, which an in-depth study is providing complete study of the industry for the period 2022 to 2027. It provides complete overview of Global Marketing Analytics Market industry as all the major industry trends, market subtleties and good set-up. Besides this, the report also provides key statistics on the Marketing Analytics Market status of the leading market players, key trends, and potential growth openings in the market. These study reports are planned with the goal to help the reader in favorable Strengthen data and make decisions that are helpful to grow their business.

The Marketing Analytics Market was valued at USD 2.13 billion in 2020 and is expected to reach USD 4.68 billion by 2027, at a CAGR of 14% over the forecast period (2022 – 2027) .

Click here to get the latest sample PDF copy of the report: –

The major players covered in the reports are:

– IBM Corporation

– Microsoft Corporation

– Oracle Corporation

– Salesforce.Com Inc.

– Accenture PLC

– Adobe Systems Incorporated

– SAS Institute Inc.

– Teradata Corporation

– Neustar, Inc.

– Pegasystems Inc.

– Tableau Software

– Google LLC

They said research study covers in-depth analysis of multiple market segments based on type, application, and studies different topographies. The report is also inclusive of competitive profiling of the leading Marketing Analytics Market product vendors, and their latest developments. This report has been segmented by type, by application and by geography and also includes the market size and forecast for all these segments. Compounded annual growth rates for all segments have also been provided for 2022 to 2027.

Browse the full report description and summary: –

Regional Analysis: –

Major regions covered in the report include North America, Asia Pacific, Europe, East & Africa, and South America. In addition, the report provides country level analysis for 25+ major countries including US, Germany, UK, Japan, China, India, UAE, South Korea, South Africa, and Brazil. Regional analysis provides regional as well as country level information about the market highlighting the dynamics of the market by various segments covered in the report.

Industry News and Updates:

In Jul 2017, Teradata announced the acquisition of StackIQ, a prominent developer of cloud analytics software, which has managed the deployment of cloud and analytics software at millions of servers in data centers around the world. The acquisition is expected to strengthen the R&D capabilities of the company. Further In Jun 2018, Microsoft signed a MoU with New Sales Wales to trial a major data science project based on procurement analytics.

Some of the key questions answered in this report:

  • What will the market growth rate, growth momentum or acceleration market carries during the forecast period?
  • Which are the key factors driving the Marketing Analytics Market?
  • What was the size of the emerging Marketing Analytics Market by value in 2029?
  • What will be the size of the emerging Marketing Analytics Market in 2029?
  • Which region is expected to hold the highest market share in the Marketing Analytics Market?
  • What trends, challenges and barriers will impact the development and sizing of the Global Marketing Analytics Market?
  • What is sales volume, revenue, and price analysis of top manufacturers of Marketing Analytics Market?
  • What are the Marketing Analytics Market opportunities and threats faced by the vendors in the global Marketing Analytics Market Industry?

Highlights of Global Marketing Analytics Market Report: –

  • Examines the Marketing Analytics Market industry's prospects and quickly compares historical, current, and projected market figures.
  • This report examines growth constraints, market drivers and challenges, and current and prospective development prospects.
  • Key market participants are evaluated based on various factors, including revenue share, price, regional growth, and product portfolio, to demonstrate how market shares have changed in the past and are expected to change in the future.
  • Describes the expansion of the global Marketing Analytics Market across various industries and geographies. This allows players to concentrate their efforts on regional markets with the potential for rapid growth in the short term.
  • Discuss the global, regional, and national ramifications of COVID-19.

MENAFN20092022004660010643ID1104894631


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Killexams : Sports Analytics Market Size Reached US$ 2,778.20 Million by 2027, Will Grow at 19.20% CAGR till 2027

"Global Sports Analytics Market Size. Trends 2022-2027"

The global sports analytics market size reached US$ 907.5 Million in 2021. By 2027, it will reach a value of US$ 2,778.20 Million, growing at 19.20% (2022-2027).

The latest research study “Sports Analytics Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2022-2027” by IMARC Group, finds that the global sports analytics market size reached a value of US$ 907.5 Million in 2021. Looking forward, IMARC Group expects the market to reach a value of US$ 2,778.20 Million by 2027 exhibiting a CAGR of 19.20% during 2022-2027.

What is Sports Analytics? How Big is Sports Analytics Market?

Sports analytics represents the application of statistical and mathematical principles to analyze numerous components of sports, such as player performance, recruitment, business performance, etc. It involves collecting data from a broad sample and establishing various parameters that measure the hit rate. Based on the type, sports analytics is segmented into on-field and off-field analytics. Sports analytics assists in ensuring high returns on investments, reducing operating costs, increasing overall income, etc. It also aids in evaluating the strengths and weaknesses of opponents. As a result, sports analytics is widely utilized by professional and college sports programs, sports media, training technology companies, etc.

Note: We are regularly tracking the direct effect of COVID-19 on the market, along with the indirect influence of associated industries. These observations will be integrated into the report.

Request a PDF sample for more detailed market insights: https://www.imarcgroup.com/sports-analytics-market/requestsample

Sports Analytics Market Trends and Drivers:

The growing investments across the sports industry towards making data-driven decisions are primarily bolstering the sports analytics market. In addition to this, the inflating need for tracking and monitoring the data of players is further augmenting the market growth.

Moreover, the escalating demand for enhanced wearable devices among athletes to gain insights into their performance is acting as another significant growth-inducing factor.

Besides this, the rising health consciousness among consumers, particularly owing to the sudden outbreak of the COVID-19 pandemic, is also positively influencing the global market. Additionally, the development of high-end and cost-effective computing solutions is anticipated to fuel the sports analytics market in the coming years.

Sports Analytics Market Report Scope

Report Coverage

Details

Forecast Period

2022­–2027

Base Year

2021

Market Size in 2021

US$ 907.5 Million

Market Size in 2027

US$ 2,778.20 Million

CAGR

19.20%


Global Sports Analytics Market 2022-2027 Analysis and Segmentation:

Competitive Landscape:

The competitive landscape of the market has been studied in the report with the detailed profiles of the key players operating in the market.


Sports Analytics Companies: 

Chyronhego Corporation

Experfy Inc.

HCL Technologies HCLTECH

International Business Machines Corporation IBM

iSportsAnalysis

Oracle Corporation ORCL

Qualitas Global Services

SAP SE SAP

Sas Institute Inc.

Sportradar AG

Stats Perform

Tableau Software LLC (Salesforce.com Inc.)

The report has segmented the market on the basis of region, component, analysis type and sport.


Breakup by Component:


Breakup by Analysis Type:

  • On-field
    • Player and Team Analysis
    • Video Analysis
    • Health Assessment
  • Off-field
    • Fan Engagement
    • Ticket Pricing


Breakup by Sport:

  • Football
  • Cricket
  • Hockey
  • Basketball
  • American Football
  • Others


Breakup by Region:

  • North America: (United States, Canada)
  • Asia Pacific: (China, Japan, India, South Korea, Australia, Indonesia, Others)
  • Europe: (Germany, France, United Kingdom, Italy, Spain, Russia, Others)
  • Latin America: (Brazil, Mexico, Others)
  • Middle East and Africa


Explore Report Description with TOC & List of Figure: 
https://www.imarcgroup.com/sports-analytics-market


If you want latest primary and secondary data (2022-2027) with Cost Module, Business Strategy, Distribution Channel, etc. Click request free sample report, published report will be delivered to you in PDF format via email within 24 to 48 hours of receiving full payment.


Key highlights of the report:

  • Market Performance (2016-2021)
  • Market Outlook (2022- 2027)
  • Porter’s Five Forces Analysis
  • Market Drivers and Success Factors
  • SWOT Analysis
  • Value Chain
  • Comprehensive Mapping of the Competitive Landscape


If you need specific information that is not currently within the scope of the report, we can provide it to you as a part of the customization.

Browse More Trending Industry Research Reports (Book Now With 10% Discount + COVID-19 Scenario): 

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About Us:

IMARC Group is a leading market research company that offers management strategy and market research worldwide. We partner with clients in all sectors and regions to identify their highest-value opportunities, address their most critical challenges, and transform their businesses.


IMARC’s information products include major market, scientific, economic and technological developments for business leaders in pharmaceutical, industrial, and high technology organizations. Market forecasts and industry analysis for biotechnology, advanced materials, pharmaceuticals, food and beverage, travel and tourism, nanotechnology and novel processing methods are at the top of the company’s expertise.

Media Contact
Company Name: IMARC Group
Contact Person: Elena Anderson
Email: Send Email
Phone: +1-631-791-1145
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City: Sheridan
State: WY
Country: United States
Website: https://www.imarcgroup.com

 

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To view the original version on ABNewswire visit: Sports Analytics Market Size Reached US$ 2,778.20 Million by 2027, Will Grow at 19.20% CAGR till 2027

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