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Rational Associate Application Developer V8
IBM Application Topics
Killexams : IBM Application subjects - BingNews Search results Killexams : IBM Application subjects - BingNews Killexams : IBM's Expertise Nurturing Transformational Change in Fintech

A consultancy business is only as good as the knowhow it can impart onto clients. So it speaks volumes that, when asked what sets IBM Consulting apart, Lee-Han Tjioe, General Manager for Hong Kong and Macau, points to its rich and varied expertise.

“We have both business consulting and technology consulting in our scope,” Lee-Han says. “We have business consultants in our team that help clients with their strategy, with their new propositions, with defining or optimising business processes. That's one part of our practice. The other part is where we also advise on specific technology topics. So we have consultants that are very specialised in key technologies like AI and Hybrid Cloud that can help clients to achieve technology enabled major operational improvements. We basically have both deep business and technology skill sets to deliver end-to-end solutions.”

IBM has been a trusted advisory and delivery partner with high market reputation for decades, and has further developed into an eco-system provider with exact major corporate acquisitions to expand its AI and Hybrid Cloud skill sets to support clients with implementing differentiating industry and technology solutions. Today, IBM works closely and collaboratively with companies and eco-system partners to achieve required business model changes enabled by modern digital solutions which, without reliable partners, would be hard to scale at fast pace.

In many cases, IBM’s clients are international and local conglomerate companies across multiple key industries. “We are co-creating with our clients and ecosystem partners to develop new propositions and experiences, and applying best practices in a fast fashion with fast go-to-market. One example is with an insurance company that we work with on IOT for “pay-how-you-drive” insurance. And so we helped the client to actually get the right technologies into the cars to track driving behaviours and attach that to very innovative insurance propositions.”

IBM’s partnership with AXA

Another example is IBM’s strong partnership with insurance company AXA, which has endured for many years. Initially, AXA had their applications managed by providers over the world but was looking to consolidate, recognising that it was very hard to achieve consistent levels of service as well as cost-effectiveness. AXA brought IBM on board to manage those applications but also to help them innovate.

“Our partnership with AXA means that we are delivering multi-year support for the business-critical applications that AXA has,” Lee-Han continues. “Those applications are supporting distribution, sales, and key internal operations. We have transferred knowledge of 60 applications within four months and now support about 100+ applications. This is the foundation for our partnership with AXA. We are now helping with further accelerated0 deployment of API-based services on AXA’s digital platform to meet the fast developing new market needs.”

IBM Consulting and Our Transformation

IBM Consulting’s business can be broken down into four pillars: 1. Strategy Consulting, where it works with clients to define vision and blueprint for its future; 2. Experience Consulting, where Garage and Design thinking approaches are applied to redefine new experiences for clients and their customers; 3. Operations Consulting, in which it examines how it can optimise current business activity with automation and new technologies such as AI and IoT; and lastly 4. Technology Consulting, where IBM helps clients to implement or manage enterprise solutions and leverage Cloud technologies for optimising application management. 

It’s a diverse remit – but at the heart of everything the firm does is the Virtual Enterprise, IBM’s framework that helps clients in their pursuit of digital transformation. Transformation is not just about taking on technical hurdles, IBM’s depth of transformation experiences and understanding of key industry opportunities proofs a Virtual Enterprise approach can be achieved with an end-to-end vision for achieving business growth.


Tue, 12 Jul 2022 18:39:00 -0500 en text/html
Killexams : Search IBM Courses No result found, try new keyword!You'll build your chatbot application with ... Courses 1 and 2 of the IBM AI Enterprise Workflow specialization and you have a solid understanding of the following subjects prior to starting this ... Thu, 22 Apr 2021 07:23:00 -0500 text/html Killexams : IBM Made a 'Crash Course' For The White House, And It'll Teach You All The AI Basics

Alarmed by the AI Revolution

Vernor Vinge once stated in his book The Singularity, “We are on the edge of change comparable to the rise of human life on Earth.” As AI now undoubtedly plays a pivotal role in many industries, its risks and repercussions simply cannot be ignored; and shining a light upon these has never been more imperative.

That's why, in response to the White House's Notice Of Request For Information (RFI), IBM has created what seems to be an AI 101—covering the huge field of AI and its vast potential applications.

Image Credit: Futuristech

"The views of the American people, including stakeholders such as consumers, academic and industry researchers, private companies, and charitable foundations, are important to inform an understanding of current and future needs for AI in diverse fields," the RFI summary read.

Responding to Skepticsm

IBM's AI 101 consisted of a numbered list of subjects in a somewhat re-ordered and slightly re-factored response to the RFI's questions. As Techcrunch suggests, each subject is explained well enough to make readers the smartest in the room. The following are the subjects in IBM's response:

  1. The use of AI for public good
  2. Social and economic implications of AI 
  3. Education for harnessing AI technologies 
  4. Fundamental questions in AI research, and the most important research gaps
  5. Data sets that can accelerate AI research 
  6. Multi-disciplinary research 
  7. Role of incentives and prizes 
  8. Safety and control issues for AI 
  9. Legal and governance implications of AI
  10. Other issues: Business models 

In hindsight, even though there are many ambiguities and inefficiencies associated with the AI revolution, IBM believes that these can be eliminated and that "AI systems...will ultimately transform our personal and professional lives. Its benefits far outweigh its risks. And with the right policies and support, those benefits can be realized sooner."

Sat, 06 Aug 2016 02:27:00 -0500 text/html
Killexams : Responsible computing isn’t just about moving to the cloud

Member Article

Nick Westall CTO, CSI Ltd

IT departments are being asked by their boards to demonstrate improved sustainability. Often, they attribute their move to the cloud as a way of showing commitment to the reduction of their carbon footprint and the green agenda. While it’s a good example of carbon offset, is it just a way to pass the buck to the cloud provider rather than look in more depth about being a responsible user of IT? How much real consideration goes into calculating and demonstrating responsible computing in business today?

In 2020 the IBM Academy of Technology (AoT) brought together experts in many fields to discuss responsible computing. They analysed the anxieties of over 100 CTOs and looked at all aspects of IT to answer questions such as, “Am I doing enough to be sustainable?”, “Are we being ethical in our use of data?” and “Am I doing enough to ensure that the infrastructure we use is minimising its impact on the environment?” As a result, the IBM AoT initiative has created a framework which outlines important considerations of responsible computing.

Six domains of responsible computing From the more obvious subjects associated with running your computing infrastructure to its wider impacts, the AoT framework summarised that responsible computing comprised of six main domains:

• Data centres – which looks at the potential impact on the environment of an advanced modern data centre. • Infrastructure – which considers the Environmental, Social and Governance (ESG) impact of the hardware, software and networks required to develop, test, deliver, monitor, control and support IT services. • Code – which entails being aware of the potential environmental, societal and economic impact that design and requirements choices could have whilst utilising methods to minimise their negative impact. • Data Usage – which involves the duty to deal with and have control over data and its lifecycle as well as being accountable of its mindful, effective and efficient usage. • Systems – which summarises the need for developing systems that everyone, including the company itself, can trust. A “system” is an integrated set of technologies that provide a service to human beings. It can be composed of hardware, data, code, models and services. • Impact – which encompasses the use of technology to change the world for a better future.

Being a responsible CTO The reasons for needing to be a responsible CTO are just as strong as the need to be a tech-savvy one if a company wants to thrive in a digital economy. There are many facets to being a responsible CTO, such as making sure that code is being written in a diverse way and that citizen data is being used appropriately.

In a BCS webinar, IBM Fellow and Vice President for Technology in EMEA, Rashik Parmar, summarised that the three biggest forces driving unprecedented change today included post-pandemic work, digitalisation and the climate emergency. With many organisations turning to technology to help solve some of the biggest challenges they’re facing today, it’s clear that there will need to be answers about how this tech-heavy economy will impact the environment. It makes sense that this is often the first place that a CTO will start when deciding how to drive a more responsible future.

Responsible computing is much more than a move to the cloud When you consider that each of the six domains above will make a huge difference to how responsible an organisation is deemed, it’s easy to see why it’s about much more than a move to the cloud.

If we focus on the environmental considerations, it’s becoming more commonly known that whilst a move to the cloud may be better for reducing an organisation’s carbon emissions than running multiple on-premises systems, the initiative alone isn’t going to spell good news for climate change. In fact, if everyone were to move to the cloud in droves the internet would need to quickly find a way of being more sustainable.

A large part of this is the requirement for major cloud providers to switch most of their data centres to more renewable energy sources. This is an area that falls outside of a customer’s control. But in fact, the issue of reducing emissions can be influenced far more greatly by the activities undertaken by the organisations themselves. It can all come down to understanding how their workloads are running and whether it is driving high levels of utilisation.

Making more efficient use of the computational resources available

When it comes to running at high levels of utilisation, the answer isn’t necessarily all cloud driven. For example, the performance and scale of the new IBM Power server, the E1080, delivers the benefits of consolidation at levels far higher than is possible with x86-based alternatives.

When compared with the cloud hyperscalers, such as Azure and AWS, it offers a greater ability to scale. In a exact webinar, David Spurway, IBM Systems Technology Architect, modelled IBM’s Power10 against Azure and AWS, looking at the largest of their offerings which could then be filled up with workloads such as multiple containers*.

*In the model, David used the conservative performance metric of the IDC QPI, which gives relative performance across architectures but does not consider advantages for specific workloads. For example, the new Power10 cores can hold over four times more containers per core than x86, so the real values may be even higher.

By doing much more per core, fewer cores are needed, which leads to less energy needed. Whilst Virtual Servers in the Cloud can run at high levels of utilisation – near the 90% mark - the average utilisation is much lower. This is because the number of workloads that smaller servers can hold is lower, and that means more servers are needed. With IBM’s large E1080 server, average and peak utilisations demonstrate a more efficient use of the computational resources available. When utilisation is combined with scale and performance it provides a very powerful and efficient option.

Can cost savings be a by-product of energy efficiency? If an organisation is on a software licencing model that adjusts depending on the level of utilisation and usage, it is also possible to achieve significant cost savings. The ability to turn applications on and off when not in use will reduce the number of processors needed. If the organisation is charged by the processor core this could be as much as five times less expensive because of the software savings when running fewer cores.

Environmental considerations that organisations should make There are detailed methodologies available that help organisations establish where they are today in terms of responsible computing. As sustainability is such a relatively new factor, it’s important for an organisation to understand where it is so that it can measure what improvements are being made in the form of Key Performance Indicators.

The three main considerations can be summarised as:

• Are you using latest infrastructure components? This has a real impact because as technology advances, newer components deliver better performance and require less energy for a given workload. • Are you consolidating workloads? Consolidation allows workloads which peak at different times to complement each other and make more efficient use of resources. • Are you running at high utilisation? High levels of utilisation (which can be improved by consolidation) delivers more efficient use of energy and resources.

The responsible computing deliverables include methodologies for all six domains to help companies understand where they are today and demonstrate how they are improving and delivering against their KPIs. While it’s true that cloud infrastructure does deliver carbon savings, organisations should also think about the environmental and cost saving benefits in other on-premises measures.

This was posted in Bdaily's Members' News section by CSI .

Mon, 04 Jul 2022 10:35:00 -0500 en text/html
Killexams : Data Sciences and Applications MPS

Note: An asterick (*) indictates a new course that is being finalized for approval.

CDA 501/EAS 503 Introduction to Data Driven Analysis

This course introduces students to computer science fundamentals for building basic data science applications. The course has two components. The first part introduces students to algorithm design and implementation in a modern, high-level, programming language (currently, Python). It emphasizes problem-solving by abstraction. subjects include data types, variables, expressions, basic imperative programming techniques including assignment, input/output, subprograms, parameters, selection, iteration, Boolean type, and expressions, and the use of aggregate data structures including arrays. Students will also have an introduction to the basics of abstract data types and object-oriented design. The second part covers regression analysis and introduction to linear models. subjects include multiple regression, analysis of covariance, least square means, logistic regression, and nonlinear regression. The students learn to implement the regression models as a computer program and use the developed application to analyze synthetic and real world data sets.

CDA 502/MGS 613 Database Management Systems  

This course provides basic understanding of relational databases including normalization, database schemas and relational algebra, create, update, query and delete tables using standard SQL statements, understand workflows such as ETL (extract, transform, and load) to aggregate data from multiple sources integrating it in databases and data warehouses use, manage and customize NoSQL databases including key value, wide column, document and graph stores as well as their application on non-tabular data, use, manage and customize graph databases and apply them to multi-dimensional datasets.

CDA 511 Introduction to Numerical Analysis

A first course on the design and implementation of numerical methods to solve the most common types of problem arising in science and engineering. Most such problems cannot be solved in terms of a closed analytical formula, but many can be handled with numerical methods learned in this course. subjects for the two semesters include: how a computer does arithmetic, solving systems of simultaneous linear or nonlinear equations, finding eigenvalues and eigenvectors of (large) matrices, minimizing a function of many variables, fitting smooth functions to data points (interpolation and regression), computing integrals, solving ordinary differential equations (initial and boundary value problems), and solving partial differential equations of elliptic, parabolic, and hyperbolic types. We study how and why numerical methods work, and also their errors and limitations.  Students gain practical experience through course projects that entail writing computer programs.

CDA 531/MTH 511 Probability and Data Analysis  

Topics include: review of probability, conditional probability, Bayes' Theorem; random variables and distributions; expectation and properties; covariance, correlation, and conditional expectation; special distributions; Central Limit Theorem and applications; estimations, including Bayes; estimators, maximum likelihood estimators, and their properties. Includes use of sufficient statistics to 'improve' estimators, distribution of estimators, unbiasedness, hypothesis testing, linear statistical models, and statistical inference from the Bayesian point of view.

CDA 541/STA 545 Statistical Data Mining 1

This course presents statistical models for data mining, inference and prediction. The focus will be on supervised learning, which concerns outcome prediction from input data. Students will be introduced to a number of methods for supervised learning, including: linear and logistic regression, shrinkage methods, lasso, partial least squares, tree-based methods, model assessment and selection, model inference and averaging, and neural networks. Computational applications will be presented using R and high dimensional data to reinforce theoretical concepts.

CDA 546/STA 546 Statistical Data Mining 2

This course presents the subject of data mining from a statistical perspective, with attention directed towards both applied and theoretical considerations. An emphasis will be placed on unsupervised learning methods, especially those designed to discover and exploit hidden structures in high-dimensional data. subjects include: hierarchical and center based clustering, principal component analysis, data visualization, random forests, directed and undirected graphical models, and special considerations when n>>p. Computational applications to high-dimensional data will be presented using Matlab and R to illustrate methods and concepts.

CDA 542/CSE 574 Machine Learning

Humans have an uncanny ability to learn from their mistakes and adapt to new environments by relying on their past experience. Machine learning focuses on "How to write a computer program than can Excellerate performance through experience?" Machine learning has a huge number of practical applications, more so in the present era of Big Data, where staggering volumes of diverse data in almost every facet of society, science, engineering, and commerce, are presenting opportunities for valuable discoveries. For example, machine learning is being used to understand financial markets, impact of climate change on society, protein-protein interactions, diseases, etc. Machine learning also has far ranging applications such as self-driving cars to never ending language learning systems. This course will focus on understanding the mathematical and statistical foundations of machine learning. We will also cover the core set of techniques and algorithms needed to understand the practical applications of machine learning. The course will be an integrated view of machine learning, statistics (classical and Bayesian), data mining, and information theory. A basic understanding of probability, statistics, algorithms, and linear algebra is expected. Familiarity with Python is required for homework assignments and for understanding in-class demonstrations.

CDA 551/MGS 639 Cybersecurity Privacy and Ethics  

Present-day terms, philosophies, technologies, and strategies that go into buttressing an organization’s cybersecurity posture. Managing the resources of a corporate information assurance program, while continually improving a risk footprint and response, is an underpinning of all subjects that will be covered. Students will critically examine concepts such as networking, system administration, and system security as well as identifying and applying basic security hardening techniques. Students will gain practical experience through a virtualized lab environment where they will build and secure a small corporate network.

*CDA 561 Major Applications - Health, Social, Finance, Science and Engineering

This course will provide students with an overview of data driven analytics in different industry sectors. The class will have a series of visiting lecturers with the faculty member teaching the class providing overview, continuity and grading of homework and term papers.

CDA 571/ Project Guidance  

This course will provide students with a final integrative project experience. The class will require students to obtain an integrative project experience either in industry or at the university. In either case the students will use the skills acquired during the other classes in executing project goals. Students will provide short reports to supervising faculty to ensure that learning objectives are being met.

Thu, 30 Jun 2022 11:59:00 -0500 en text/html
Killexams : How Automation Affects The Interpretation Profession And Interpreting Services

Interpretation, as a language-intensive profession, is a hot subject in the age of language automation. Automation, lower prices, and international competition are putting pressure on the interpretation industry right now.

Everyone wants their interpretations to be automated. The negative perception of machine interpretation among interpreters is well-known, but the economic implications of this position are poorly understood. 

Automation is vast in terms of its applications, its implications, and its opportunities. It is a trend that is reshaping industries across the globe. Chatbots, for example, communicate with customers and answer questions in customer service. Robotic arms are used in manufacturing to assemble everything from furniture to automobiles.

However, one aspect where automated methods have been reluctant to take hold is the aspect of interpretation services. Even IBM’s Project Debater, a robot that has learned to develop its own thoughts, cannot compete with human-written interpretation services.

How does automatic interpretation software work?

Automatic interpretation and interpreting services providers created a “gisting” tool that generates interpretations to help the end-user understand the source content better. It is a great tool that allows users to concentrate on their most important duties rather than repeating the same fundamental operations.

Simply said, automation allows users to set up automatic operations within their technology solutions that are triggered by specified events. Based on the determined trigger, the platform will subsequently carry out those precise activities or follow-up actions.

Technology Advancement

In exact years, interpretation technology has advanced at a breakneck pace, with the goal of partially or completely automating the interpreting services process.

According to the European Language Industry Survey 2022, control of the process of interpretation is shifting from interpreters to computers, with 45 percent of language companies saying that automated workflows and interpreting services are used in more than 25% of their projects.

When the term “automated interpretation” is said, the first thing that comes to mind is machine interpretation. Although globalization has increased the demand for interpreting services, exact events like the COVID pandemic have exponentially increased that demand.

There is currently a focus on remote work and limiting inter-personal contact to necessary situations. As a result of these trends, businesses have begun to rely on AI solutions to help them communicate across language barriers.

Software Systems in Advanced Interpretation Technology

Automatic interpretation software systems employ advanced interpretation technology, including extensive dictionaries and a set of linguistic principles, to convert one language into another without the involvement of human interpreters.

An automatic interpretation software system analyzes the structure of phrases in the source language (the language from which the user is interpreting) and produces an interpretation based on the destination language’s rules (the language the user is interpreting to).

Breaking down complicated and variable sentence patterns, identifying portions of speech, resolving ambiguities, and synthesizing the information into the components and structure of the new language are all part of the process.

How Does Automation Affect Interpretation Services?

According to Bert Esselink, Strategic Account Director at RWS, language service providers (LSPs) use automation for the following:

  • Content transmission to and from interpretation is automated.
  • Automating processes help in getting higher efficiency and productivity in the long run for those with regular and continuous interpretation demands. While automation does necessitate initial setup, it does so only once, allowing for simplified and faster responses to all subsequent queries.
  • Manual steps in the interpreting services process, such as file conversions, word counting, and quality checks, are being substantially reduced.
  • Applying specified process steps or automated content adjustments based on the content given for translation utilizing business rules or artificial intelligence (AI).
  • Automating and routing files.

Besides the wage dispersion in interpreting services which can be attributed to growing interpretation automation, their analysis revealed a deeper change in the concept of interpretation itself.

The more interpreters are aware of automation and prepared to work with it, the more they seek to have their multilingual interactive skills valued. That way, interpreters can either make the results of automation more reliable or explain and humanize the benefits of technology.

In particular, the development of neural machine interpretation systems since 2016 has brought fears together with it that soon there will be no more human interpretation services. When considered in terms of the history of automation, however, any such direct effect is far from obvious: the interpretation industry is still growing and machine interpretation is only one instance of automation.

At the same time, data on remuneration indicate structural wage dispersion in professional interpretation services, with some signs that this dispersion may increase in certain market segments as automated workflows and interpretation technologies are adopted more by large language-service providers than by smaller companies and individual freelancers. 

Conclusively, automation does not need to be our enemy. Machines can make life easier for people by rendering interpreting services. An analysis of exact changes in discourses on and in the interpretation profession further indicates conceptual adjustments in the profession that may be attributed to growing automation, particularly with respect to expanding skill sets associated with translation, the tendency to combine interpreting services with other forms of communication, and the use of interactive communication skills to authorize and humanize the results of automation.

More Automation Topics

Mon, 04 Jul 2022 10:16:00 -0500 en-US text/html
Killexams : Quantum Computing With QISKit

We all know that quantum computing is coming, but it is hard to know how to get started with it. [Mtreinish] suggests Qiskit — an Apache Licensed SDK for developing quantum applications. He has a presentation he gave in Singapore that you can see below, and a notebook you can go through on GitHub. If you are impatient, you can even run the notebook online through Google.

The tools can work against several backends including a simulator or the real hardware available from IBM. The official site has a different notebook you can use as a tutorial. Interestingly, the foundation of all Qiskit programs is “Terra” (the Earth) and permeating all Qiskit elements is Aer or air. There are also fire and water elements. At the bottom of the official notebook, you’ll find a lot of community notebooks that go deeper into specific topics.

The notebooks are a great example of using Juypter to share computation in a literate way. We agree with [Mtreinish] that it is nice to have a simulator, but the real thrill is to use one of the real devices IBM makes available via the Internet.

However, simulators do have a certain charm. We like Quirk, on which we did a three-part series last year. You might find that article useful to learn about basic transforms and other fundamental concepts.

Sat, 11 Jun 2022 12:00:00 -0500 Al Williams en-US text/html
Killexams : 7 Overlooked Blue-Chip Stocks to Add to Your Buy List No result found, try new keyword!Therefore, the subsequent rush of excitement as the public catches on could buoy overlooked blue-chip stocks to buy. Another factor to consider is the balanced nature of large-cap firms. Yes, it’s ... Mon, 11 Jul 2022 02:59:00 -0500 text/html Killexams : Structured Data Archiving and Application Retirement Market Size, Share and Forecast till 2028

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

Jul 04, 2022 (Reportmines via Comtex) -- Pre and Post Covid is covered and Report Customization is available.

"Structured Data Archiving and Application Retirement market research report"includes in-depth detailed company profiling of leading players of the Structured Data Archiving and Application Retirement market. All of the segments studied in the report are analyzed based on different factors such as market share, revenue, and CAGR rate 2022 - 2028. The analysts have also thoroughly analyzed different regions such as a 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 based on production, revenue, and sales in the Structured Data Archiving and Application Retirement market. The researchers used advanced primary and secondary research methodologies and tools for preparing this report on the Structured Data Archiving and Application Retirement market. The market research segmentation study by type includes a Cloud-based,On-premises.

The global Structured Data Archiving and Application Retirement market size is projected to reach multi million by 2028, in comparision to 2021, at unexpected CAGR during 2022-2028 (Ask for demo Report).

Furthermore, one of its most important applications is BFSI,Education,Manufacturing,Telecom & IT,Others. The report has a total of 138 pages. The key competitors of this Structured Data Archiving and Application Retirement Market include Metalogix,Delphix,OpenText,PBS Software,IBM,Gimmal,Informatica,Actifio,Oracle,Microsoft,DCSoftware (Arctools),Dolphin,Micro Focus,Solix Technologies,ZL Technologies.

Get demo PDF of Structured Data Archiving and Application Retirement Market Analysis

The top competitors in the Structured Data Archiving and Application Retirement Market, as highlighted in the report, are:

  • Metalogix
  • Delphix
  • OpenText
  • PBS Software
  • IBM
  • Gimmal
  • Informatica
  • Actifio
  • Oracle
  • Microsoft
  • DCSoftware (Arctools)
  • Dolphin
  • Micro Focus
  • Solix Technologies
  • ZL Technologies

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Market Segmentation

The worldwide Structured Data Archiving and Application Retirement Market is categorized on Component, Deployment, Application, and Region.

The Structured Data Archiving and Application Retirement Market Analysis by types is segmented into:

The Structured Data Archiving and Application Retirement Market Industry Research by Application is segmented into:

  • BFSI
  • Education
  • Manufacturing
  • Telecom & IT
  • Others

In terms of Region, the Structured Data Archiving and Application Retirement 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 the Purchasing This Report

Stakeholders and Industry Participant’s Benefits:

  • This Structured Data Archiving and Application Retirement market research report examines the industry's drivers, constraints, and opportunities.
  • This Structured Data Archiving and Application Retirement market research study covers potential, sectors, and areas with prospective growth.
  • Structured Data Archiving and Application Retirement Market sizes (historical, present, and projection) in terms of revenue.

The Structured Data Archiving and Application Retirement 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

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Highlights of The Structured Data Archiving and Application Retirement Market Report

The following are some of the subjects covered in the Structured Data Archiving and Application Retirement Market Industry Research Report:

  • Structured Data Archiving and Application Retirement Market structure and forecasts for the coming years.
  • market drivers, limitations, opportunities, and current trends.
  • Data from the past as well as projections.
  • Forecast period estimates.
  • The Structured Data Archiving and Application Retirement market for developments and trends.
  • Regional, sub-regional, and country Structured Data Archiving and Application Retirement market scenarios.

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Analyses of COVID 19

The COVID-19 crisis has had a big impact on Structured Data Archiving and Application Retirement market research reports, to varying degrees. Because they have stronger defenses, others will find it difficult to return to a constantly shifting normal. The impact of COVID-19 on the Structured Data Archiving and Application Retirement market research industry is examined in this market research report, which contains insights, analysis, projections, and forecasts.

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Structured Data Archiving and Application Retirement Industry Challenges and Market Size

Top-down and bottom-up approaches are used to validate the Structured Data Archiving and Application Retirement market size and estimate the market size for businesses, regions segments, product segments, and applications (end users). Various factors affecting the Structured Data Archiving and Application Retirement market research industry were investigated, including the government policy, market environment, competitive landscape, historical data, current Structured Data Archiving and Application Retirement market industry trends, technological innovation, upcoming technologies, and the technical progress in related industries, as well as market risks, opportunities, market barriers, and challenges.

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Purchase the Structured Data Archiving and Application Retirement Market Report for the Following Reasons:

  • The Structured Data Archiving and Application Retirement market study provides a variety of information, including market trends and opportunities for the forecast period.
  • Demand and supply forces, as well as their impact on the Structured Data Archiving and Application Retirement market, are covered in regional, sub-regional, and country-level statistics.
  • The competitive landscape has included Structured Data Archiving and Application Retirement market participants, innovations, and tactics in the last three years.
  • This Structured Data Archiving and Application Retirement market research report includes a list of firms that sell items, as well as financial data, current events, SWOT analyses, and strategies for these organizations.

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Mon, 04 Jul 2022 07:00:00 -0500 en-US text/html
Killexams : Hatters’ new CEO to employees: ‘We will have to fight for Red Hat to succeed—it won’t be given to us’

RALEIGH – Matt Hicks bleeds Red Hat. Having risen through the company ranks since joining the Raleigh-based company as a programmer in 2006, he has seen the open source company grow, become part of IBM, and establish itself as a global leader for Wall Street financial management and – now – cloud computing. But in taken over as CEO in a move announced Tuesday he told Hatters now is not the time to be complacent.

Here’s what he said in an emial to employees just before his taking over as CEO in place of Paul Cormeir was formally announced:

Hi all,

When I joined Red Hat in 2006 as a developer on the IT team working on porting Perl applications to Java, I never imagined that my career would lead me to this moment. If I had followed my initial path, not raised my hand for certain projects, or shied away from contributing ideas and asking questions, I might not be here. That is what I love about Red Hat and it’s something that differentiates us from other companies: nothing is predetermined; we’re only limited by our passion and drive to contribute and make an impact. That’s true not just for us as individuals but also for us as a company.

Matt Hicks. (Red Hat photo)

Our legacy of success, however, can trick us into believing it’s a given for Red Hat. I’ve learned a lot from Paul Cormier over the years, but the thing that I try to bring in every day is that we will have to fight for Red Hat to succeed—it won’t be given to us. That was true the day Red Hat was founded, it is true today, and it will be true far into the future.

I’ve worked with Paul for over a decade and have never seen him complacent. I’ve never seen him quit. He gives Red Hat his all every single day. That drive has always motivated me to look forward to what is possible for Red Hat. And if there’s one thing I can ensure in Paul’s role as Chairman, it’s that he will continue to push us towards success. And we must always be ready to earn it.

I’m honored, proud and thankful as I step into this role, to both serve you and help take Red Hat to even greater places. There’s a significant opportunity ahead of us and I’m eager to help us seize it. As I’ve prepared to step into the CEO role, I’ve spent a lot of time reflecting on what makes Red Hat unique. There are three values that I want to see us embrace, or in some cases recommit to, as Red Hatters.

Passion with Respect

We are here because we believe that Red Hat can solve many of the biggest challenges in our industry and our world with open source. We are here because we believe Red Hat can enable our customers to innovate and solve challenges for their customers with open source. We can only say open unlocks the world’s potential if we have passion behind that statement. And we do.

Open source development has always resulted in better innovation faster because it brings together people with diverse experiences to work together to solve a common challenge and spark new ideas. This is Red Hat.

To live up to that statement means bringing our all to the table every day and never being complacent. We must constantly push one another, always remembering that we are on the same team. We must seek out and actively include new and differing perspectives. Ask questions, share ideas, debate approaches, and challenge assumptions as we work to solve problems and find better solutions together. This is how ideas are strengthened.

Respect goes hand-in-hand with passion and constructively challenging each other. If you are as passionate about understanding someone else’s contributions as you are about your own ideas, finding mutual respect will be easy.

Red Hat is a global company with 20,000+ associates, all with something to contribute and a unique perspective, unified on the same team by a shared mission. Approach every interaction with a curiosity for understanding one another. Listen to and respect one another, even if you disagree. Be open to learning something new or gaining a different perspective, whether on a piece of technology or an experience. Be open to the barriers others might see in the way of your idea. Learn from them. When necessary, be open to changing your mind.

I’ve learned infinitely more from being challenged and proven wrong than when I’ve been correct. Pride can make these moments hard to accept, but we must be open to them—we can’t be blinded by passion. When we can step outside of our typical mindsets, new ideas can be born.

As Red Hatters, we are called to debate ideas, not people. We will productively debate the ideas that will enable us to make progress, innovate, and deliver breakthrough solutions. We don’t have to agree on everything; truthfully, if we’re bringing that passion I talked about, we shouldn’t. The open part of Red Hat’s culture has never meant we work as a democracy, or even that we’ll get consensus. As a company, we must make swift decisions that enable us to seize the opportunity in front of us. Sometimes, this means you will voice your ideas or thoughts and then disagree and commit once a decision has been made.

No matter the subject or depth of your passion, we must always bring a level of respect that can put us all on equal footing.

Contribution with Accountability

Being on equal footing is what sets Red Hat apart: every one of you has the power to influence the company. Every single one. Even coming in as an intern, you can make an impact. I genuinely believe this.

At Red Hat, you can influence the company and make an impact by contributing and participating. Your title has no bearing on how impactful you can be. We need your ideas, skills and expertise. You are all here for a reason and bring something unique to Red Hat no matter where you sit. But you have to share it. Everyone here should feel that you not only can but that we need you to jump in, share ideas, volunteer for projects, and push yourself. Embrace your role and excel at it, but never be limited by it.

When you contribute, we want it to count. You must have the accountability to direct your contributions. You have to understand our strategy and make contributions that progress it, not work against it or one another. How you contribute matters.

Contributing doesn’t mean your ideas will always succeed. I want to see us try new things. I also want us to make mistakes and even fail at times—that’s important because it means we are being bold and stepping outside our comfort zones. The key is that we always learn and quickly adjust so we do not make the same mistake again, and so we can make faster progress in areas that are working. Don’t get trapped in the cycle of trying to make something work when it’s not delivering results.

If you are going to contribute, you must follow through. One of the things that I believe has helped me throughout my career is that I am not afraid to dig in and do whatever task helps move the team forward. In my teens, I worked in a bagel bakery. I had a boss named Alan, who regularly reminded us that “we all empty the trash around here.” No job was beneath anyone—we all pitched in to do the work. No matter what title you hold at Red Hat, you should always be willing to jump in and do the heavy lifting. Red Hat became Red Hat by being scrappy, and we must keep that mentality because we will all empty the trash around here (thanks Alan).

Realizing Potential

We also must stay curious. Stay curious about the world around us, stay hungry for the next challenge and keep an eye out for potential, perhaps in unlikely places. In open source communities, there is a straightforward system to find out who are the most impactful contributors; often, it’s not always the most vocal person or the people you would expect.

Time and time again, I’m inspired by the incredible potential in people. I’ve seen us hire associates with no experience in open source who have become some of the world’s most impactful open source engineers. Taking the chance, whether on a person or a new project, will be critical as we scale. When we hire, look for culture add, not culture fit. Find that passion, encourage contributions, and make this a place where everyone is welcome and can thrive.

Embracing these values will give us the team dynamic we need to win. But our playbook will need some refinement as well. With all the opportunities in the market, it would be easy to start doing more and more things to try and capture it.

Instead, I believe we are at the perfect time in our journey to simplify. There is power in simplicity and focus. Our strategy is to deliver open hybrid cloud. To do that, we must deliver the platforms that enable customer success from on-premises environments to cloud services and at the edge. We will refine our playbook to the simplest possible set of things to deliver in these areas, and with that simplicity, I believe we can become best-in-class in everything we do.

In this simplification, I also want us to reinvigorate the core of Red Hat’s value–what we give to customers that others can’t. We make customers successful with open source software.

Sometimes we stop after the word successful, but the “with open source software” piece is what’s most important. There’s a lot of open source software out there, and yes, the marketplace is more crowded than it was at the beginning. But that’s because we’re accomplishing what we set out to do: show the power of open source to change the world.

Open source is now solidly the innovation driver for the software industry and Red Hat is the leader in enterprise open source, period. No one does it better than us. We will continue to earn that respected position and push ourselves to deliver the open source innovation that makes customers successful.

I’m here to do the work with you. Let’s roll up our sleeves together, embrace these values and earn the opportunity ahead of us.

Tue, 12 Jul 2022 23:04:00 -0500 en-US text/html
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