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Killexams : RES Orchestration learning - BingNews https://killexams.com/pass4sure/exam-detail/ES0-006 Search results Killexams : RES Orchestration learning - BingNews https://killexams.com/pass4sure/exam-detail/ES0-006 https://killexams.com/exam_list/RES Killexams : The Rise of AI Orchestration

The funny thing about artificial intelligence and AI derivatives such as machine learning, deep learning, and now generative AI is that they’ve been around for so long. While those entering the IT market have a renewed understanding of AI, its core mechanisms pretty much remain the same.

The cost and the ease of building very complex and valuable AI models are what has changed. The use of cloud computing ignited the rapid rise of AI systems. As businesses expand their investments in cloud technology innovations, AI can provide still more business value.

Most enterprises leverage AI systems as monolithic systems. They receive training data, learn from it, and then leverage those models to carry out some predefined purpose. For example, determining the credit risks within a loan processing system, automating a supply chain to minimize inventory, or picking stocks for an investment firm.

However, the innovations available within these standalone systems limit the value of these monolithic AI systems. This limitation created the drive to integrate AI technology with other core business systems and other AI systems to add value.

When done correctly, the end state is 1+1=3. This will also increase an AI system’s ROI, which can be costly to develop and maintain.

Also see: What is Artificial Intelligence 

AI Orchestration and Integrating AI Systems

Integrating AI systems with many other business systems (either loosely or tightly coupled) is nothing new. AI systems are featureless, at the end of the day. While they can carry out some impressive functions, they are not business applications unto themselves. They must be bound to business applications to create the business value needed from AI.

The trend in the past was to tightly couple AI systems to applications and application data. The AI systems were either a component of the business system that runs in the same space and on the same platform or the systems that are accessed through synchronous (blocking) APIs that can programmatically interact with the AI systems.

The tight coupling of AI systems to business systems was all about choosing the path of least resistance. While it “worked,” it limited the value AI systems could provide to many other business systems.

Lightweight orchestration services can deal with the unique requirements of AI systems and provide loosely coupled access to any number of AI systems. They leverage those systems using no-code or low-code development, where orchestration services create solutions by using configuration rather than deep development. Loose coupling vs. tight coupling allows access and orchestration to be set up to leverage AI systems in ways that can drive more business value from those systems.

Orchestrations are neither new nor innovative, whether they run within the same cloud, across clouds, or across internal systems. It’s a new application of an existing innovation that provides the ability for orchestration layers to deal with AI system interaction in ways that make the AI systems much more effective when leveraged together (1+1=3).

For example, let’s say we have an AI system to pick stocks that will increase in value, an AI system to support risk analytics for specific companies, and an AI system to spot trends in social media before they become trends. While each system has clear value by itself, the ability to create orchestrations that can evaluate specific business problems or proposals through the combination of all or some of the AI systems has much more value.

Referring to the above example, we can use a list of stocks created by the stock-picking AI system and then pass that information off to the risk analytics system. That system can cull through the data and assign risk rankings based on its training data and the resulting knowledge model.

Then, we take the risk-ordered list of good stocks to our social media AI-powered analytics system that can assign good or bad trends to specific products that those companies produce. This combined application of AI systems can further determine if the market will likely support that company.

You get the idea. Follow the patterns of process integration, RPA, data integration, and other systems that operate above more primitive systems, which allow more value to be extracted. This is about supporting automation between these systems to find useful orchestrations that can be built as an ad-hoc solution, or as something more permanent.

Also see: The Future of Artificial Intelligence

Full Potential of AI Orchestration

Of course, our simple example does not illustrate the full potential of AI orchestration or the number of potential business applications. Other examples include:

  • Orchestration of 12 different AI systems and 110 databases to support supply chain integration that allows decision-making with near-perfect information and understanding.
  • The ability to create an investment system like the one defined in our example that picks stocks with an 89 percent success rate using dozens of AI systems and internal and external data sources.
  • A system that ranks the best potential employee candidates using external and internal data, and 9 AI systems that can determine which candidates are most likely to be successful in a specific role.

AI on its own has some value. Integrating AI with other AI systems and other data sources can produce much more value. This is the point where companies can take AI to value levels that have not been reached. This also provides a platform for experimenting with the power of AI, which can, in turn, find innovative values that most businesses have yet to realize or even conceptualize.

Also see: The History of Artificial Intelligence 

Two Types of AI Orchestration

So, what does an AI orchestration tool look like? There are two general types:

  • The first type includes workflow and orchestration tools that natively support AI integration.
  • The second type of tool requires you to extend its capabilities to interface with the AI system and deal with AI data to be generated and consumed (e.g., training data).

Some may even leverage AI for their workflow or orchestration capabilities, but that’s not on the critical path. The critical path is to leverage a tool that can integrate your source and target databases and AI systems, preferably using a low-code or no-code orchestration engine that you can easily and quickly setup. The platform you leverage (e.g., public cloud), the enabling technology, and other factors will determine the “right” tool AI orchestration tool to leverage.

Again, this type of AI is not new or science fiction. It’s simply an approach that leverages existing technologies to bring more value to the business. That said, most businesses don’t yet understand what AI orchestration is, and fewer recognize its game-changing value for businesses. It’s time to do some homework.

Also see: How AI is Altering Software Development with AI-Augmentation 

Fri, 20 Jan 2023 02:52:00 -0600 en-US text/html https://www.eweek.com/big-data-and-analytics/ai-orchestration/
Killexams : The Learning Network No result found, try new keyword!By The Learning Network Research shows that today’s parents feel intense pressure to be engaged with their children. Does that ring true for your own experiences? Is more involvement always a ... Thu, 16 Feb 2023 17:47:00 -0600 en text/html https://www.nytimes.com/section/learning Killexams : Orchestration and choreography in .NET microservices

As more businesses adopt microservice architectures for their applications, more developers have had to grapple with the concepts of orchestration and choreography. Although these terms are sometimes used interchangeably, there are key differences between these two architectural patterns.

Orchestration is a centralized approach to making all control decisions about interactions between services. Here a central orchestrator service coordinates all of the other services that execute a business transaction or workflow. By contrast, a choreography is a decentralized approach to coordinating this workflow, where each service determines its own behavior based on the messages it receives from other services.

This article will cover the core concepts of orchestration and choreography in microservices architectures and discuss how you might use each (or both) in your microservices-based applications. We’ll also simulate microservices orchestration and choreography in code examples provided below.

What is microservices architecture?

Microservices refer to a style of software architecture where a large application can be built as a conglomeration of small, autonomous services. Each microservice has a specific purpose and is deployable independently.

A microservices architecture makes it easy to scale individual services as needed. It also allows for more speed and flexibility when making changes to the application because only the affected service needs to be redeployed.

Two main approaches to managing communication between microservices are orchestration and choreography. Let’s understand the differences.

Copyright © 2023 IDG Communications, Inc.

Wed, 15 Feb 2023 20:39:00 -0600 en text/html https://www.infoworld.com/article/3687638/orchestration-and-choreography-in-net-microservices.html
Killexams : The 6 Best Automation and Orchestration Tools for Linux © Provided by MUO

Whether you have a few PCs or a large IT infrastructure, orchestration and automation tools can help you bring in a lot of efficiencies and enable you to simplify the management of complex tasks and workflows.

The main orchestration and configuration software can handle all sorts of repetitive workloads such as OS and application installation, removal, updates, etc. Here are some of the most common orchestration and automation tools for Linux.

1. Ansible

Ansible is an open-source configuration and automation tool for managing and maintaining your IT infrastructure. It is ideal for automating the deployment, configuration, and updating of applications on your PCs.

Some key features of Ansible include:

  • Agentless: You do not need to install Ansible-related software on managed systems. This makes it easy to start with Ansible and reduces the overhead of managing agents on multiple systems.
  • Easy to use: It uses a high-level language called Ansible Playbooks to define the desired state of your IT infrastructure. Written in YAML, Ansible Playbooks are easy to read and understand.
  • Idempotent: Ansible is idempotent, which means that it can be safely run, multiple times, without changing your systems if they are already in the desired state.
  • Extensible: Ansible has a large library of pre-written modules for managing common tasks such as installing packages, managing services, and configuring applications. In addition, you can write your own modules to add new functionality.

In case you are wondering, the Ansible platform is mainly developed and maintained by Red Hat. It is written in the Python programming language.

Ansible is widely used by individuals and organizations of all sizes. If adopted, it can help in reducing the time and effort required to maintain your Linux systems, and ensure that they are consistently configured and compliant with best practices.

2. Puppet

Yet another open-source configuration management and orchestration tool, Puppet allows you to define the desired state of your IT infrastructure, including the packages, services, and applications you need on your PCs.

A key feature of Puppet is ensuring the state of your IT infrastructure matches the defined or desired state.

In addition to configuration management, Puppet also provides orchestration capabilities that allow you to automate complex tasks and workflows across your infrastructure.

Puppet is highly scalable and efficient and you can use it to manage both small and large IT infrastructures.

3. cloud-init

cloud-init is an open-source tool mainly used for configuring and customizing cloud instances. For example, installing and setting up VMs in cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Of course, you can also use it with local or on-prem virtualization software such as VirtualBox and VMware.

Other common tasks that you can automate with cloud-init include installing packages and applications, user and group administration, network configuration, and writing files.

cloud-init reads its configuration data from a variety of sources, including cloud-specific metadata files, configuration files on the instance's file system, and from user data files.

The platform is developed by Canonical and was originally only supported on Ubuntu, but it is now available on all major Linux distros including FreeBSD.

4. Salt

Salt is a configuration management and orchestration tool for Linux and Unix-like systems. It allows you to automate the process of managing and maintaining your PCs. It is ideal for installing software, managing services, and other administrative operations.

Salt mainly follows the server-client model, where you have to configure and install software on the PC that will be managed by Salt. The server is called the "master" and the clients are known as "minions." Salt also supports agentless architecture.

It utilizes the ZeroMQ communication method, which allows for high-speed communication, allowing Salt to perform tasks on thousands of systems in parallel, making it very efficient and scalable.

Similar to Ansible, Salt utilizes YAML for defining your infrastructure state. However, Salt has a steeper learning curve. If you intend to manage large IT infrastructures then Salt could be your ideal solution.

5. Chef

Chef is a powerful and lightweight orchestration and automation tool. You can use Chef to manage and configure your IT infrastructure.

Similar to other main-stream tools, it allows you to define the desired state of your IT infrastructure, including the configuration, services, and software packages you need to install. Chef then ensures that the real state of your infrastructure matches the desired state, making it easy to manage and maintain your systems.

Chef uses a high-level language known as Chef Infra Language to define your server or PC state. Written in Ruby, Chef Infra Language is relatively easy to read and understand.

In addition to configuration management, Chef also provides automation capabilities that allow you to automate complex tasks and workflows across your IT infrastructure. For example, you can use it to manage your server lifecycle and perform rolling updates across multiple live systems.

Chef is scalable and efficient and you can use it to manage IT infrastructure of all sizes, from a few to thousands of servers.

6. Terraform

Terraform is an open-source tool for building, changing, and versioning infrastructure safely and efficiently. Like cloud-init, it is mainly used with cloud service providers such as AWS, Azure, and Google Cloud Platform. Terraform also supports on-prem IT infrastructure.

Terraform utilizes the DevOps methodology known as "infrastructure as code," which is simply a model for deploying your IT infrastructure. It uses a high-level configuration language called HashiCorp Configuration Language (HCL).

A great feature of Terraform is version control, and it encourages collaboration with other team members via version control systems like Git.

You can use terraform for automating tasks such as creating, updating, network configurations, and managing storage accounts in the cloud in a safe and predictable manner.

Terraform is easy to learn and at the same time is very flexible, reliable, and scalable. It is ideal for small to large-scale IT infrastructure.

Automate Repetitive Tasks on Linux

We've looked at some of the most prominent tools you can use to manage the entire lifecycle of your Linux servers and PCs, from installing the OS to managing software and services.

With Linux, you can take your automation to a whole new level by automating mundane tasks using Linux cron jobs.

Mon, 16 Jan 2023 06:39:00 -0600 en-US text/html https://www.msn.com/en-us/money/other/the-6-best-automation-and-orchestration-tools-for-linux/ar-AA16pBbK
Killexams : Intelligent Process Automation Market has Provided Valuable Insights Comprehensive Analysis of the Industry 2028

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

Feb 17, 2023 (The Expresswire) -- "Intelligent Process Automation Market" research report aims to provide a [Comprehensive Overview 2023]of the Intelligent Process Automation Market, with a combination of quantitative and qualitative analysis. Intelligent Process Automation Market detailed analysis of business is mainly cover by Application [IT Operations, Business Process Automation, Application Management, Content Management, Security, Others (Human Resource Management, Incident Resolution, and Service Orchestration)], by Type [Natural Language Processing, Machine and Deep Learning, Neural Networks, Virtual Agents, Mini Bots and RPA, Computer Vision, Others, ] Region Forecast to 2028.The research report on Intelligent Process Automation Market utilizes several methodologies and analyses to deliver comprehensive and accurate information. It offers an overview of successful marketing strategies, market contributions, and accurate developments of the leading companies in the industry. In addition, the report provides a dashboard overview of these companies' past and present performance. Through this research, readers can gain in-depth insights into the Intelligent Process Automation Market and its top players.

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The report combines in-depth statistical analysis with in-depth qualitative analysis; it covers a wide variety of topics, from a macro overview of market dynamics, industry structure, and market size dynamics to micro-details of market segmentation by type and application. As a consequence, it provides an in-depth analysis of the Kayaking Equipment market that considers all of its major factors.The market report is a good combination of qualitative and quantitative data that highlights significant market changes, obstacles that business and the competition must overcome, as well as new possibilities and trends in the global Intelligent Process Automation Market.Ask for trial Report

Top Manufactures of the Intelligent Process Automation market

● Tata Consultancy Services ● Sutherland Global Services ● Genpact ● Accenture ● SYKES ● CGI ● Infosys ● Oracle Corporation ● Capgemini ● IBM ● EXL ● Cognizant ● Atos ● SAP SE ● Pegasystems ● HCL Technologies ● Blue Prism

Get a trial Copy of the Intelligent Process Automation Market Report 2023

Intelligent Process Automation Market Report Overview:

The global Intelligent Process Automation market size was valued at USD 12390.66 million in 2022 and is expected to expand at a CAGR of 12.65% during the forecast period, reaching USD 25321.85 million by 2028.The report combines extensive quantitative analysis and exhaustive qualitative analysis, ranges from a macro overview of the total market size, industry chain, and market dynamics to micro details of segment markets by type, application and region, and, as a result, provides a holistic view of, as well as a deep insight into the Intelligent Process Automation market covering all its essential aspects.

For the competitive landscape, the report also introduces players in the industry from the perspective of the market share, concentration ratio, etc., and describes the leading companies in detail, with which the readers can get a better idea of their competitors and acquire an in-depth understanding of the competitive situation. Further, mergers and acquisitions, emerging market trends, the impact of COVID-19, and regional conflicts will all be considered.

In a nutshell, this report is a must-read for industry players, investors, researchers, consultants, business strategists, and all those who have any kind of stake or are planning to foray into the market in any manner.

The report combines extensive quantitative analysis and exhaustive qualitative analysis, ranges from a macro overview of the total market size, industry chain, and market dynamics to micro details of segment markets by type, application and region, and, as a result, provides a holistic view of, as well as a deep insight into the Intelligent Process Automation market covering all its essential aspects. In a nutshell, this report is a must-read for industry players, investors, researchers, consultants, business strategists, and all those who have any kind of stake or are planning to foray into the market in any manner.

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Intelligent Process Automation Based on TYPE, the Intelligent Process Automation market from 2023 to 2028 is primarily split into:

● Natural Language Processing ● Machine and Deep Learning ● Neural Networks ● Virtual Agents ● Mini Bots and RPA ● Computer Vision ● Others

Based on applications, the Intelligent Process Automation market from 2023 to 2028 covers:

● IT Operations ● Business Process Automation ● Application Management ● Content Management ● Security ● Others (Human Resource Management, Incident Resolution, and Service Orchestration)

COVID-19 AND RUSSIA-UKRAINE WAR INFLUENCE ANALYSIS:

COVID-19 can have an impact on the world economy have been by directly altering market dynamics, by breaking the market supply chain, and by having an economic impact on businesses and financial markets. According to our researchers, who are keeping an eye on the situation around the world, the market will create profitable opportunities for producers after the COVID-19 crisis. The purpose of the report is to further illustrate how the current situation decline in the economy, and COVID-19's effects on the entire industry.

To Understand How COVID-19 Impact is Covered in This Report. Request a trial copy of the report

Geographically, the detailed analysis of consumption, revenue, market share and growth rate, historical data and forecast (2018-2028) of the following regions are covered in Chapter 4 and Chapter 7:

● United States ● Europe ● China ● Japan ● India ● Southeast Asia ● Latin America ● Middle East and Africa

Years considered for this report:

Historical Years: 2018-2022

Base Year: 2022

Estimated Year: 2023

Forecast Period: 2023-2028

Some of the key questions answered in this report:

● What focused approach and constraints are holding the Intelligent Process Automation market? ● What are the key market trends impacting the growth of the Intelligent Process Automation market? ● Who are the global key manufacturers of the Intelligent Process Automation market? ● What are the Intelligent Process Automation market opportunities and threats faced by the vendors? ● What are the different sales, marketing, and distribution channels in the global industry? ● What is the global sales value, production value, consumption value, import and export of the Intelligent Process Automation market? ● What is the Intelligent Process Automation market size at the regional and country level?

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Detailed TOC of the Intelligent Process Automation market:

1 Intelligent Process Automation Market Overview
1.1 Product Overview and Scope of Intelligent Process Automation Market
1.2 Intelligent Process Automation Market Segment by Type
1.2.1 Global Intelligent Process Automation Market Sales Volume and CAGR (%) Comparison by Type (2018-2028)
1.3 Global Intelligent Process Automation Market Segment by Application
1.3.1 Intelligent Process Automation Market Consumption (Sales Volume) Comparison by Application (2018-2028)
1.4 Global Intelligent Process Automation Market, Region Wise (2018-2028)
1.4.1 Global Intelligent Process Automation Market Size (Revenue) and CAGR (%) Comparison by Region (2018-2028)
1.4.2 United States Intelligent Process Automation Market Status and Prospect (2018-2028)
1.4.3 Europe Intelligent Process Automation Market Status and Prospect (2018-2028)
1.4.4 China Intelligent Process Automation Market Status and Prospect (2018-2028)
1.4.5 Japan Intelligent Process Automation Market Status and Prospect (2018-2028)
1.4.6 India Intelligent Process Automation Market Status and Prospect (2018-2028)
1.4.7 Southeast Asia Intelligent Process Automation Market Status and Prospect (2018-2028)
1.4.8 Latin America Intelligent Process Automation Market Status and Prospect (2018-2028)
1.4.9 Middle East and Africa Intelligent Process Automation Market Status and Prospect (2018-2028)
1.5 Global Market Size of Intelligent Process Automation (2018-2028)
1.5.1 Global Intelligent Process Automation Market Revenue Status and Outlook (2018-2028)
1.5.2 Global Intelligent Process Automation Market Sales Volume Status and Outlook (2018-2028)
1.6 Global Macroeconomic Analysis
1.7 The impact of the Russia-Ukraine war on the Intelligent Process Automation Market

2 Industry Outlook
2.1 Intelligent Process Automation Industry Technology Status and Trends
2.2 Industry Entry Barriers
2.2.1 Analysis of Financial Barriers
2.2.2 Analysis of Technical Barriers
2.2.3 Analysis of Talent Barriers
2.2.4 Analysis of Brand Barrier
2.3 Intelligent Process Automation Market Drivers Analysis
2.4 Intelligent Process Automation Market Challenges Analysis
2.5 Emerging Market Trends
2.6 Consumer Preference Analysis
2.7 Intelligent Process Automation Industry Development Trends under COVID-19 Outbreak
2.7.1 Global COVID-19 Status Overview
2.7.2 Influence of COVID-19 Outbreak on Intelligent Process Automation Industry Development

3 Global Intelligent Process Automation Market Landscape by Player
3.1 Global Intelligent Process Automation Sales Volume and Share by Player (2018-2023)
3.2 Global Intelligent Process Automation Revenue and Market Share by Player (2018-2023)
3.3 Global Intelligent Process Automation Average Price by Player (2018-2023)
3.4 Global Intelligent Process Automation Gross Margin by Player (2018-2023)
3.5 Intelligent Process Automation Market Competitive Situation and Trends
3.5.1 Intelligent Process Automation Market Concentration Rate
3.5.2 Intelligent Process Automation Market Share of Top 3 and Top 6 Players
3.5.3 Mergers and Acquisitions, Expansion

4 Global Intelligent Process Automation Sales Volume and Revenue Region Wise (2018-2023)
4.1 Global Intelligent Process Automation Sales Volume and Market Share, Region Wise (2018-2023)
4.2 Global Intelligent Process Automation Revenue and Market Share, Region Wise (2018-2023)
4.3 Global Intelligent Process Automation Sales Volume, Revenue, Price and Gross Margin (2018-2023)
4.4 United States Intelligent Process Automation Sales Volume, Revenue, Price and Gross Margin (2018-2023)
4.4.1 United States Intelligent Process Automation Market Under COVID-19
4.5 Europe Intelligent Process Automation Sales Volume, Revenue, Price and Gross Margin (2018-2023)
4.5.1 Europe Intelligent Process Automation Market Under COVID-19
4.6 China Intelligent Process Automation Sales Volume, Revenue, Price and Gross Margin (2018-2023)
4.6.1 China Intelligent Process Automation Market Under COVID-19
4.7 Japan Intelligent Process Automation Sales Volume, Revenue, Price and Gross Margin (2018-2023)
4.7.1 Japan Intelligent Process Automation Market Under COVID-19
4.8 India Intelligent Process Automation Sales Volume, Revenue, Price and Gross Margin (2018-2023)
4.8.1 India Intelligent Process Automation Market Under COVID-19
4.9 Southeast Asia Intelligent Process Automation Sales Volume, Revenue, Price and Gross Margin (2018-2023)
4.9.1 Southeast Asia Intelligent Process Automation Market Under COVID-19
4.10 Latin America Intelligent Process Automation Sales Volume, Revenue, Price and Gross Margin (2018-2023)
4.10.1 Latin America Intelligent Process Automation Market Under COVID-19
4.11 Middle East and Africa Intelligent Process Automation Sales Volume, Revenue, Price and Gross Margin (2018-2023)
4.11.1 Middle East and Africa Intelligent Process Automation Market Under COVID-19

5 Global Intelligent Process Automation Sales Volume, Revenue, Price Trend by Type
5.1 Global Intelligent Process Automation Sales Volume and Market Share by Type (2018-2023)
5.2 Global Intelligent Process Automation Revenue and Market Share by Type (2018-2023)
5.3 Global Intelligent Process Automation Price by Type (2018-2023)
5.4 Global Intelligent Process Automation Sales Volume, Revenue and Growth Rate by Type (2018-2023)
5.4.1 Global Intelligent Process Automation Sales Volume, Revenue and Growth Rate of Natural Language Processing (2018-2023)
5.4.2 Global Intelligent Process Automation Sales Volume, Revenue and Growth Rate of Machine and Deep Learning (2018-2023)
5.4.3 Global Intelligent Process Automation Sales Volume, Revenue and Growth Rate of Neural Networks (2018-2023)
5.4.4 Global Intelligent Process Automation Sales Volume, Revenue and Growth Rate of Virtual Agents (2018-2023)
5.4.5 Global Intelligent Process Automation Sales Volume, Revenue and Growth Rate of Mini Bots and RPA (2018-2023)
5.4.6 Global Intelligent Process Automation Sales Volume, Revenue and Growth Rate of Computer Vision (2018-2023)
5.4.7 Global Intelligent Process Automation Sales Volume, Revenue and Growth Rate of Others (2018-2023)

6 Global Intelligent Process Automation Market Analysis by Application
6.1 Global Intelligent Process Automation Consumption and Market Share by Application (2018-2023)
6.2 Global Intelligent Process Automation Consumption Revenue and Market Share by Application (2018-2023)
6.3 Global Intelligent Process Automation Consumption and Growth Rate by Application (2018-2023)
6.3.1 Global Intelligent Process Automation Consumption and Growth Rate of IT Operations (2018-2023)
6.3.2 Global Intelligent Process Automation Consumption and Growth Rate of Business Process Automation (2018-2023)
6.3.3 Global Intelligent Process Automation Consumption and Growth Rate of Application Management (2018-2023)
6.3.4 Global Intelligent Process Automation Consumption and Growth Rate of Content Management (2018-2023)
6.3.5 Global Intelligent Process Automation Consumption and Growth Rate of Security (2018-2023)
6.3.6 Global Intelligent Process Automation Consumption and Growth Rate of Others (Human Resource Management, Incident Resolution, and Service Orchestration) (2018-2023)

7 Global Intelligent Process Automation Market Forecast (2023-2028)
7.1 Global Intelligent Process Automation Sales Volume, Revenue Forecast (2023-2028)
7.1.1 Global Intelligent Process Automation Sales Volume and Growth Rate Forecast (2023-2028)
7.1.2 Global Intelligent Process Automation Revenue and Growth Rate Forecast (2023-2028)
7.1.3 Global Intelligent Process Automation Price and Trend Forecast (2023-2028)
7.2 Global Intelligent Process Automation Sales Volume and Revenue Forecast, Region Wise (2023-2028)
7.2.1 United States Intelligent Process Automation Sales Volume and Revenue Forecast (2023-2028)
7.2.2 Europe Intelligent Process Automation Sales Volume and Revenue Forecast (2023-2028)
7.2.3 China Intelligent Process Automation Sales Volume and Revenue Forecast (2023-2028)
7.2.4 Japan Intelligent Process Automation Sales Volume and Revenue Forecast (2023-2028)
7.2.5 India Intelligent Process Automation Sales Volume and Revenue Forecast (2023-2028)
7.2.6 Southeast Asia Intelligent Process Automation Sales Volume and Revenue Forecast (2023-2028)
7.2.7 Latin America Intelligent Process Automation Sales Volume and Revenue Forecast (2023-2028)
7.2.8 Middle East and Africa Intelligent Process Automation Sales Volume and Revenue Forecast (2023-2028)
7.3 Global Intelligent Process Automation Sales Volume, Revenue and Price Forecast by Type (2023-2028)
7.3.1 Global Intelligent Process Automation Revenue and Growth Rate of Natural Language Processing (2023-2028)
7.3.2 Global Intelligent Process Automation Revenue and Growth Rate of Machine and Deep Learning (2023-2028)
7.3.3 Global Intelligent Process Automation Revenue and Growth Rate of Neural Networks (2023-2028)
7.3.4 Global Intelligent Process Automation Revenue and Growth Rate of Virtual Agents (2023-2028)
7.3.5 Global Intelligent Process Automation Revenue and Growth Rate of Mini Bots and RPA (2023-2028)
7.3.6 Global Intelligent Process Automation Revenue and Growth Rate of Computer Vision (2023-2028)
7.3.7 Global Intelligent Process Automation Revenue and Growth Rate of Others (2023-2028)
7.4 Global Intelligent Process Automation Consumption Forecast by Application (2023-2028)
7.4.1 Global Intelligent Process Automation Consumption Value and Growth Rate of IT Operations(2023-2028)
7.4.2 Global Intelligent Process Automation Consumption Value and Growth Rate of Business Process Automation(2023-2028)
7.4.3 Global Intelligent Process Automation Consumption Value and Growth Rate of Application Management(2023-2028)
7.4.4 Global Intelligent Process Automation Consumption Value and Growth Rate of Content Management(2023-2028)
7.4.5 Global Intelligent Process Automation Consumption Value and Growth Rate of Security(2023-2028)
7.4.6 Global Intelligent Process Automation Consumption Value and Growth Rate of Others (Human Resource Management, Incident Resolution, and Service Orchestration)(2023-2028)
7.5 Intelligent Process Automation Market Forecast Under COVID-19

8 Intelligent Process Automation Market Upstream and Downstream Analysis
8.1 Intelligent Process Automation Industrial Chain Analysis
8.2 Key Raw Materials Suppliers and Price Analysis
8.3 Manufacturing Cost Structure Analysis
8.3.1 Labor Cost Analysis
8.3.2 Energy Costs Analysis
8.3.3 RandD Costs Analysis
8.4 Alternative Product Analysis
8.5 Major Distributors of Intelligent Process Automation Analysis
8.6 Major Downstream Buyers of Intelligent Process Automation Analysis
8.7 Impact of COVID-19 and the Russia-Ukraine war on the Upstream and Downstream in the Intelligent Process Automation Industry

9 Players Profiles
9.1 Tata Consultancy Services
9.1.1 Tata Consultancy Services Basic Information, Manufacturing Base, Sales Region and Competitors
9.1.2 Intelligent Process Automation Product Profiles, Application and Specification
9.1.3 Tata Consultancy Services Market Performance (2018-2023)
9.1.4 accurate Development
9.1.5 SWOT Analysis
9.2 Sutherland Global Services
9.2.1 Sutherland Global Services Basic Information, Manufacturing Base, Sales Region and Competitors
9.2.2 Intelligent Process Automation Product Profiles, Application and Specification
9.2.3 Sutherland Global Services Market Performance (2018-2023)
9.2.4 accurate Development
9.2.5 SWOT Analysis
9.3 Genpact
9.3.1 Genpact Basic Information, Manufacturing Base, Sales Region and Competitors
9.3.2 Intelligent Process Automation Product Profiles, Application and Specification
9.3.3 Genpact Market Performance (2018-2023)
9.3.4 accurate Development
9.3.5 SWOT Analysis
9.4 Accenture
9.4.1 Accenture Basic Information, Manufacturing Base, Sales Region and Competitors
9.4.2 Intelligent Process Automation Product Profiles, Application and Specification
9.4.3 Accenture Market Performance (2018-2023)
9.4.4 accurate Development
9.4.5 SWOT Analysis
9.5 SYKES
9.5.1 SYKES Basic Information, Manufacturing Base, Sales Region and Competitors
9.5.2 Intelligent Process Automation Product Profiles, Application and Specification
9.5.3 SYKES Market Performance (2018-2023)
9.5.4 accurate Development
9.5.5 SWOT Analysis
9.6 CGI
9.6.1 CGI Basic Information, Manufacturing Base, Sales Region and Competitors
9.6.2 Intelligent Process Automation Product Profiles, Application and Specification
9.6.3 CGI Market Performance (2018-2023)
9.6.4 accurate Development
9.6.5 SWOT Analysis
9.7 Infosys
9.7.1 Infosys Basic Information, Manufacturing Base, Sales Region and Competitors
9.7.2 Intelligent Process Automation Product Profiles, Application and Specification
9.7.3 Infosys Market Performance (2018-2023)
9.7.4 accurate Development
9.7.5 SWOT Analysis
9.8 Oracle Corporation
9.8.1 Oracle Corporation Basic Information, Manufacturing Base, Sales Region and Competitors
9.8.2 Intelligent Process Automation Product Profiles, Application and Specification
9.8.3 Oracle Corporation Market Performance (2018-2023)
9.8.4 accurate Development
9.8.5 SWOT Analysis
9.9 Capgemini
9.9.1 Capgemini Basic Information, Manufacturing Base, Sales Region and Competitors
9.9.2 Intelligent Process Automation Product Profiles, Application and Specification
9.9.3 Capgemini Market Performance (2018-2023)
9.9.4 accurate Development
9.9.5 SWOT Analysis
9.10 IBM
9.10.1 IBM Basic Information, Manufacturing Base, Sales Region and Competitors
9.10.2 Intelligent Process Automation Product Profiles, Application and Specification
9.10.3 IBM Market Performance (2018-2023)
9.10.4 accurate Development
9.10.5 SWOT Analysis
9.11 EXL
9.11.1 EXL Basic Information, Manufacturing Base, Sales Region and Competitors
9.11.2 Intelligent Process Automation Product Profiles, Application and Specification
9.11.3 EXL Market Performance (2018-2023)
9.11.4 accurate Development
9.11.5 SWOT Analysis
9.12 Cognizant
9.12.1 Cognizant Basic Information, Manufacturing Base, Sales Region and Competitors
9.12.2 Intelligent Process Automation Product Profiles, Application and Specification
9.12.3 Cognizant Market Performance (2018-2023)
9.12.4 accurate Development
9.12.5 SWOT Analysis
9.13 Atos
9.13.1 Atos Basic Information, Manufacturing Base, Sales Region and Competitors
9.13.2 Intelligent Process Automation Product Profiles, Application and Specification
9.13.3 Atos Market Performance (2018-2023)
9.13.4 accurate Development
9.13.5 SWOT Analysis
9.14 SAP SE
9.14.1 SAP SE Basic Information, Manufacturing Base, Sales Region and Competitors
9.14.2 Intelligent Process Automation Product Profiles, Application and Specification
9.14.3 SAP SE Market Performance (2018-2023)
9.14.4 accurate Development
9.14.5 SWOT Analysis
9.15 Pegasystems
9.15.1 Pegasystems Basic Information, Manufacturing Base, Sales Region and Competitors
9.15.2 Intelligent Process Automation Product Profiles, Application and Specification
9.15.3 Pegasystems Market Performance (2018-2023)
9.15.4 accurate Development
9.15.5 SWOT Analysis
9.16 HCL Technologies
9.16.1 HCL Technologies Basic Information, Manufacturing Base, Sales Region and Competitors
9.16.2 Intelligent Process Automation Product Profiles, Application and Specification
9.16.3 HCL Technologies Market Performance (2018-2023)
9.16.4 accurate Development
9.16.5 SWOT Analysis
9.17 Blue Prism
9.17.1 Blue Prism Basic Information, Manufacturing Base, Sales Region and Competitors
9.17.2 Intelligent Process Automation Product Profiles, Application and Specification
9.17.3 Blue Prism Market Performance (2018-2023)
9.17.4 accurate Development
9.17.5 SWOT Analysis

10 Research Findings and Conclusion

11 Appendix
11.1 Methodology
11.2 Research Data Source
 

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Killexams : Creating Meaningful And Relevant Customer Experiences Using Data Quality

Today’s consumers have high expectations for brands, including expectations for highly personalized experiences – with conditions. For instance, a accurate Prosper Insights & Analytics survey shows that over 68 percent of consumers state that they don’t like when advertisers buy their personal data.

Additionally, nearly 3 in 4 consumers (73 percent) have taken steps to protect their online privacy. So how can brands meet high expectations for personalization when consumers are hesitant to share their personal data?

I recently spoke with John Nash, chief marketing and strategy officer at Redpoint Global – a leading software provider helping brands deliver revenue-generating, personalized customer experiences (CX) – to discuss this. Follow along as we dive into the evolution of personalization, consumer sentiments around data privacy and brand communications efforts, and how data quality can enable brands to reduce CX gaps while increasing trust and loyalty.

Gary Drenik: What is the biggest mistake brands make when it comes to customer experience and personalization? How can brands remedy this?

John Nash: A common barrier to delivering a personalized CX is a lack of insights, which is really a data quality issue. This can be due to an entrenched mindset of engaging with customers across siloed channels, and a brand’s inability to converse with customers in real time.

To remedy this, brands must have an accurate and unified view of a customer. Identity resolution resolves a customer identity across all devices, IDs and touchpoints – whether an individual, a household or another entity – and is a key step toward creating a customer “golden record,” or holistic view of the individual.

When this view is updated in real-time and accessible to every application and user, brands can orchestrate the personalized experiences that consumers desire across channels and at every point in the customer journey.

Drenik: Survey results show that consumers are willing to provide access to their data in exchange for better CX. Yet, despite this willingness to share information, consumers continue to experience mistargeted information. Where does this disconnect stem from and how can it be avoided?

Nash: According to a accurate Redpoint Global survey, 70% of respondents said they receive mistargeted information at least once a month, with data quality issues causing this disconnect. Brands that lack an updated, real time single view introduce irrelevant communications because they fundamentally misunderstand either who they’re trying to engage with, or how individuals move through a customer journey.

When information is relevant to a customer in the context of their unique journey, there is no disconnect. Rather, that opens the door to the value exchange you mention where customers willingly provide data. Why? Because they know it will be used to provide highly relevant interactions that are consistent across channels.

Drenik: Given the increased need for customer data in personalizing experiences, how can brands satisfy customer expectations around trust and transparency?

Nash: Trust is the other component of the value exchange. Customers will provide personal data in exchange for a more personalized experience, with the caveat that brands are also fully transparent about data collection and how it is used. Ideally, preference management does more than check the compliance box and honor the right to be forgotten with GDPR, CCPA and other regulatory requirements. Building understanding, preferences and trust into each interaction gives brands an opportunity to elevate CXs and differentiate themselves in a competitive market.

Drenik: Should brands be leaning into generational differences among each group’s personalization expectations? If so, what best practices can you share for brands?

Nash: If the goal of identity resolution is to know the customer you’re trying to engage with, generational differences can provide valuable insights into what a customer expects from a brand and how customers perceive themselves.

A clustered audience machine learning model, for example, provides opportunities for further segmentation as it finds commonalities among customers that are potentially far more meaningful than age such as purchasing patterns, post-buying behavior and browsing activity.

Research shows that younger consumers are more open to fully digital experiences. In the accurate Prosper Insights & Analytics survey you mentioned earlier, data revealed 21 percent of Gen-Z and nearly 25 percent of Millennials are comparative shopping online more often given the current state of the U.S. economy. Curbside pickup and digital returns are just a few other examples of the contact-less, digital-first options that may appeal to these younger customers. Providing flexibility in how CX is received and letting consumers choose an engagement method is another effective way to honor consumer preferences.

As we look ahead though, new technology that allows brands to segment a market of one will likely lead to fewer brands relying on demographic data alone.

Drenik: Personalization continues to be a popular Topic for CX – how has the conversation transformed in accurate years, and why should brands care?

Nash: Since identity resolution and real-time personalization are now a matter of course for many companies, CX will be critical for brands to differentiate themselves. The technology now exists to do this at scale, in a way that is possible without having to scale your organization to meet these more granular segments. I always come back to a Harris Poll survey, conducted post-pandemic, where 39% of consumers surveyed said they will not do business with a brand that fails to deliver a personalized experience. It’s too much of a risk not to embrace a data-driven approach.

The challenge now is operational. An organization must align its people and processes around existing capabilities while also rethinking and re-aligning entrenched behaviors. Over-investment in channels and under-investment in orchestration will essentially have to be flipped. Companies need to examine whether there’s friction – either in the experience they’re providing customers, or from a disjointed martech stack.

Drenik: For brands that are behind the curve when it comes to personalization, how can they get started on making some of these changes?

Nash: It starts with having a handle on data quality. By starting with the right foundation, an organization can phase in capabilities over time, moving from a channel-centric to an omnichannel approach and eventually supporting more complex use cases. The goal is to combine a single customer view with real-time decision-making and orchestration capabilities, thereby providing companies with a single point of operational control over data, decisions and interactions.

To a customer this looks like a consistent, personalized omnichannel experience that engenders trust and the sharing of more data, leading to deeper personalization, loyalty and enhanced lifetime value. It’s a closed-loop cycle that perpetually builds off its own success.

Drenik: Thanks, John, for sharing your insights on the crucial role data quality plays in the customer experience.

Tue, 07 Feb 2023 00:00:00 -0600 Gary Drenik en text/html https://www.forbes.com/sites/garydrenik/2023/02/07/creating-meaningful-and-relevant-customer-experiences-using-data-quality/
Killexams : Learning Communities
Learning Communities StudentWritingEquation

Through learning communities, you have a great opportunity to connect with other students who share your interests and get to know faculty.

Student Testimonial Video »

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Students who participate in a learning community earn higher grades and have increased exposure to university resources and the Greater Lafayette community.

LC Introductory Video »

Learning Communities StudentsWorkingLaptop

Over 3,000 first-year students and 1,000 current students who participate in learning communities every year! Don't be left out!

Click here to learn more »

Incoming students to Purdue for Fall 2023, can apply to a learning community starting January 18th - July 5th. April 15th is the priority application deadline to be placed in a learning community. Applications submitted or modified after April 15th will be considered based on availability following the initial placement period.

Students who apply for a Learning Community by the April 15th priority deadline will be notified of their placement status through their Purdue email account by the end of the first full week in May. 

A housing contract with University Residences must be completed prior to applying for a learning community. After accepting your offer of admission, allow up to two business days to gain access to the housing contract portal.

The DataMine application for 2023-2024 Academic Year for current Purdue students is now open. Click here to apply.

Apply Today »
Fri, 27 Apr 2012 04:53:00 -0500 en text/html https://www.purdue.edu/learningcommunities/
Killexams : Resolution - definition

A term that refers to the number of pixels on a display or in a camera sensor (specifically in a digital image). A higher resolution means more pixels and more pixels provide the ability to display more visual information (resulting in greater clarity and more detail).

Standard Display Resolution Sizes

The industry standard way of representing screen resolution is publishing the number of pixels that form the two sides of the display rectangle.

A number of standards currently exist when it comes to display resolutions:

Name(s) Resolution in pixels
High Definition (HD) 1280 x 720
Full HD, FHD 1920 x 1080
2K, Quad HD, QHD 2560 x 1440
4K, Ultra HD 3840 x 2160
Standard display sizes compared

When launched in 2007, the original iPhone came with a screen resolution of 320 pixels x 480 pixels.

A range of smartphone screen resolutions compared

Resolution does not refer to the physical size of the display, camera sensor or image. For example, two displays with the same resolution can have different physical dimensions. Hence the importance of the other parameter that we publish - pixel density, which is measured in pixels-per-inch (ppi). Since a smaller display of the same resolution will have more pixels per inch the image provided by it should be clearer and more detailed (although graphics will be physically smaller).

Fri, 21 Aug 2020 13:41:00 -0500 en-US text/html https://www.gsmarena.com/glossary.php3?term=resolution
Killexams : Portfolio Orchestration: Private Equity’s New Superpower To Improve Value Creation

Jay Goldman, cofounder and CEO of Sensei Labs, co-author of New York Times bestseller The Decoded Company, HBR Advisory Council member.

If 2022 was the year companies began embracing enterprise orchestration for sustained transformation, 2023 will be the year their investors and private equity owners become fast followers.

Rising interest rates, extended inflation and a potential recession have made it difficult for PEs to meet expectations (see PEI LP survey). Hugh MacArthur, a partner at consultancy Bain & Company, sums it up: “There’s no arguing that private equity faces a dual threat from rising rates and costs.”

Value Creation Is Transformation By A Different Name

The last decade has been the age of transformations, which I refer to as the era of enterprise orchestration. Transformation is now a critical skill and success factor for enterprises, including many owned by PE. Successful portfolio transformations are a prerequisite to fundraising and the fund’s ongoing existence.

Value creation plans (VCPs) have the same characteristics as transformations, with the added clarity of well-defined financial KPIs and a fixed duration. Accelerating VCPs and reducing risk is a massive competitive advantage for scarcer LP investments and against other funds. The same transformation strategies that help enterprises transform can be re-run as VCPs by PE funds. A recent report by Constellation Research demonstrated that transformations orchestrated on modern, purpose-built platforms had nearly triple the average success rate of traditional methods.

Solving PE’s Top Challenges

Enterprise orchestration isn’t a panacea for all the challenges faced by PE, but it can deliver rapid ROI against the most common ones we’ve encountered as we’ve helped portcos and funds around the world accelerate their VCPs.

Missing LP/GP/Portco Alignment

PwC’s 2022 Next in Private Equity Survey showed 54% of PEs use email attachments to collect data from portcos, and 36% just write their response in the email body. For a sophisticated data-driven industry, having 90% of your data delivered by the antiquated equivalent of carrier pigeons needs to be urgently addressed. Access to real-time data is the first, prerequisite step toward alignment on shared best practices and accelerated value-creation strategies.

LPs are also becoming more sophisticated in measuring PE success. As Joana Rocha Scaff, head of private equity at LP Neuberger Berman, notes in a PEI article (paywall): “More and more, we’re also increasingly looking not just at returns per se, but how that return was created – earnings growth, leverage reduction, multiple arbitrage, ESG KPIs, etc.”

Enterprise orchestration can standardize KPIs, build on a shared model across portcos and provide simplified, real-time reporting by integrating various data sources (e.g., multiple ERPs, CRMs, etc.) with structured data/KPI/benefits tracking that enforces adaptive governance models. Automating real-time dashboards for cohort-based analysis and LP reporting saves hundreds of hours of effort by PE firms/portcos while ensuring alignment and transparency and accelerating value creation. Predictive models can highlight gaps to be filled by future investments.

Lagging Digital Transformation

The Private Funds Leaders Survey 2022 looked across areas of focus for PE CFOs. Its view of tech enablement found portfolio management is most poised for tech disruption, followed by fund operations.

This speaks to the need to replace the antiquated carrier pigeons and modernize portfolio orchestration. Big funds like KKR and Blackstone have been hiring chief information and innovation officers and global heads of data science to build this capability. Funds outside of the top five should look to enterprise orchestration platforms to achieve similar outcomes at a much smaller investment and much faster ROI.

The same push toward digital exists in the portcos. Traditional VCP tactics based on management teams’ prior experience are no longer sufficient to drive necessary results within hold periods. The aforementioned PwC survey found 40% of portcos’ top priority is creating value through digital transformation by digitizing more areas of their companies. Enterprise orchestration drives transformation by deploying proven playbooks, coordinating across silos and ensuring activity alignment with KPIs and outcomes.

Talent Shortfalls

Winning the war for talent is critical to create value. Transformation leaders and teams are drawn to exciting opportunities for personal growth. Today’s hybrid work reality, especially for global companies spanning geographies and time zones, requires a modern remote work environment that breaks down silos. A next-generation enterprise orchestration model inherently provides the framework for successful transformation while supporting a work-from-anywhere workforce.

Delayed Value Creation

The Journal of Alternative Investments found average 2000 to 2008 hold periods were 4.7 years but have stretched to 5.8 years since, causing IRR to drop as holds run longer. That extra time can diminish portco performance against faster-moving competitors and make acquirers more aggressive in reducing valuations due to slower value creation.

Accelerated value creation is survival of the fastest brought to life. Enterprise orchestration significantly accelerates VCPs through adaptive playbooks that build on best practices learned across portfolio and fund cohorts, building a library by portco industry, geography and strategy. Access to the right financial, commercial and operational data by the right people at the right time drives higher performance and better decision making. An enterprise orchestration maturity model, as seen in the Constellation Research report and explained in my previous Forbes article, helps assess transformation capabilities in potential portcos and identifies areas of required focus to drive VCP results.

Welcome To The Portfolio Orchestration Era

The need to deploy the unprecedented $1.1 trillion dry powder held by U.S. PEs alone only becomes more pressing over time. PwC’s US Deals 2023 Outlook highlights the slowdown of 2022 and into 2023 as a perfect chance for innovation before returning to normal deal volumes. And as described in its Next in Private Equity Survey, “PE must adapt to thrive over the next five years. The traditional PE model relies on tried-and-true methods that can fall short at every step of dealmaking in today’s superheated, competitive environment. Firms...risk overpaying for deals and seeing companies underperform during the hold period.”

The macroeconomic stars have aligned to provide PE funds with a rare chance to transform themselves before dealmaking returns to normal levels. This can be achieved with the help of real-time dashboards, predictive analytics, collaboration automation, playbooks and adaptive governance to accelerate VCPs and future fundraising. Now is the time to turn this economic crisis into your perfect opportunity to leverage digital transformation to enter the portfolio orchestration era.


Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?


Wed, 25 Jan 2023 10:00:00 -0600 Jay Goldman en text/html https://www.forbes.com/sites/forbestechcouncil/2023/01/26/portfolio-orchestration-private-equitys-new-superpower-to-improve-value-creation/
Killexams : Security Orchestration, Automation And Response Market Is Projected To Grow At A 16% Rate Through The Forecast Period
(MENAFN- EIN Presswire)

Security Orchestration, Automation And Response (SOAR) Global Market Report 2023 – Market Size, Trends, And Market Forecast 2023-2032

TBRC's Security Orchestration, Automation And Response (SOAR) Global Market Report 2023 – Market Size, Trends, And Market Forecast 2023-2032

LONDON, GREATER LONDON, UK, February 10, 2023 /einpresswire.com / -- The Business Research Company's“Security Orchestration, Automation And Response (SOAR) Global Market Report 2023” is a comprehensive source of information that covers every facet of the security orchestration, automation and response (SOAR) market. As per TBRC's security orchestration, automation and response (SOAR) market forecast, the security orchestration, automation and response (SOAR) market size is expected to grow to $2.77 billion in 2027 at a CAGR of 15.8%.

The growth in the security orchestration, automation and response (SOAR) market is due to an increase in the number of cyberattacks. North America region is expected to hold the largest security orchestration, automation and response (SOAR) market share. Major players in the security orchestration, automation and response (SOAR) market include IBM Corporation, Cisco Systems Inc., FireEye Inc., Palo Alto Networks Inc., Swimlane LLC, Rapid7, LogRhythm Inc.

Learn More On The Security Orchestration, Automation And Response (SOAR) Market By Requesting A Free trial (Includes Graphs And Tables):

Trending Security Orchestration, Automation And Response (SOAR) Market Trend
Technological advancements have emerged as a key trend gaining popularity in the security orchestration, automation, and response markets. Major companies operating in the security orchestration, automation, and response sector are focused on introducing new technologies to sustain their position.

security orchestration, automation and response (soar) market segments
.By Component: Solution, Services
.By Deployment Mode: Cloud, On Premises
.By Organisation Size: Small And Medium Enterprises, Large Enterprises
.By Application: Threat Intelligence, Network Forensics, Incident Management, Compliance Management, Workflow Management, Other Applications
.By End User: BFSI, Retail, Healthcare, Energy And Utilities, Government, IT And Telecommunications, Other End Users
.By Geography: The global security orchestration, automation and response (SOAR) market is segmented into North America, South America, Asia-Pacific, Eastern Europe, Western Europe, Middle East and Africa.

Read more on the global security orchestration, automation and response (SOAR) market report at:

Security orchestration automation and response (SOAR) is a collection of technologies that enable businesses to collect information and security alerts from a variety of sources. Enterprises can define response processes and perform threat analysis using security orchestration automation and response tools. The security orchestration, automation, and response (SOAR) is used to perform security threat analysis in a systematic digital workflow format without any human assistance.

Security Orchestration, Automation And Response (SOAR) Global Market Report 2023 from TBRC covers the following information:
.Market size date for the forecast period: Historical and Future
.Market analysis by region: Asia-Pacific, China, Western Europe, Eastern Europe, North America, USA, South America, Middle East and Africa.
.Market analysis by countries: Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA.

Trends, opportunities, strategies and so much more.

The Security Orchestration, Automation And Response (SOAR) Global Market Report 2023 by The Business Research Company is the most comprehensive report that provides security orchestration, automation and response (SOAR) industry insights and security orchestration, automation and response (SOAR) global market outlook on security orchestration, automation and response (SOAR) global market size, drivers and security orchestration, automation and response (SOAR) global market trends, security orchestration, automation and response (SOAR) global market major players, competitors' revenues, market positioning, and security orchestration, automation and response (SOAR) market growth across geographies. The security orchestration, automation and response (SOAR) market report helps you gain in-depth insights on opportunities and strategies. Companies can leverage the data in the report and tap into segments with the highest growth potential.


Browse Through More Similar Reports By The Business Research Company:
SOC As A Service Global Market Report 2023

Incident Response Global Market Report 2023

Cybersecurity Global Market Report 2023

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