+353-1-416-8900REST OF WORLD
+44-20-3973-8888REST OF WORLD
1-917-300-0470EAST COAST U.S
1-800-526-8630U.S. (TOLL FREE)

Data Analytics Market Size, Share & Industry Trends Analysis Report By Type (Predictive Analytics, Customer Analytics, Descriptive Analytics, Prescriptive Analytics), By Application, By Solution, By Regional Outlook and Forecast, 2023 - 2030

  • PDF Icon

    Report

  • 278 Pages
  • June 2023
  • Region: Global
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5852311
The Global Data Analytics Market size is expected to reach $301.8 billion by 2030, rising at a market growth of 26.8% CAGR during the forecast period.

North America region is the leader in utilizing data analytics in different industries. Consequently, North America would account for more than 33% share of the market by 2030. Prominent companies from various sectors are present in the region and use data analytics software extensively. For instance, utilizing data analytics, Twitter, Facebook, and Instagram gather user information about their tastes and send relevant adverts. The market expansion in North America may be attributed to the availability of the infrastructure required to enable data analytics as well as the rising use of cutting-edge tools like AI and machine learning.

Moreover, over the past few years, the demand for healthcare data analytics has only grown. The Centers for Disease Control and Prevention (CDC) reported that in the US, national healthcare spending made up 17.7% of GDP in 2019. The World Bank estimated that healthcare spending accounted for 5.59% of GDP in 2020. Consequently, the use of healthcare data analytics is being encouraged by numerous healthcare institutions. Therefore, with the expansion of the healthcare sector, the market will grow rapidly.



The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. For instance, In May, 2022, Amazon Web Services collaborated with IBM to enable IBM to provide a wide range of its software catalog as Software-as-a-Service (SaaS) on AWS. Moreover, the collaboration helped the customers of both companies in enhancing their modernization to the cloud and consuming IBM Services in a cloud-native manner on AWS. Additionally, In March, 2022, Microsoft entered into a partnership with FD Technologies to expand the reach of its KX Insights streaming data analytics platform as many companies seek to develop the data infrastructure for real-time decision-making.

The Cardinal Matrix - Market Competition Analysis


Based on the Analysis presented in the The Cardinal Matrix; Microsoft Corporation and Google LLC are the forerunners in the Market. In August, 2022, Google extended its collaboration with CoreLogic, a leading global property data and analytics-driven solutions provider. Through this collaboration, Google focused on supporting the launch of the CoreLogic Discovery Platform. The platform was built on Google Cloud’s sustainable and secure infrastructure. The collaboration aims to fulfill CoreLogic’s clients’ demands and allows the provision of efficient and comprehensive solutions for enterprises in the real estate finance market. Companies such as Oracle Corporation, SAP SE, IBM Corporation are some of the key innovators in the Market.



Market Growth Factors

More companies and businesses are favoring digitalization

Businesses can easily get over important contemporary business issues that may act as barriers to effective data projects by using data analytics as the commonality that runs through digital transformation, both at the beginning and throughout. The process of digital transformation is ongoing and is based on data analytics rather than being a one-time endeavor. It also demands a cultural shift within the firm centered on placing data at the core of decision-making, not merely adopting new technologies. Hence, with the rapid adoption of digitalization, the demand will increase, propelling the market's growth.

Increasing utilization of the Internet across the world

Smart manufacturing, or Industry 4.0, is also becoming more prevalent. The IoT is the machine-to-machine integration of commonplace devices. The Internet of Things (IoT) will rise due to rising bandwidth consumption as connected devices increase. Data center colocation services will also help the IoT industry flourish. Increased demand for OTT video content, increased internet access, and an increase in the number of total connected devices in households are further factors boosting internet demand. Because of all of these causes, more people are using the Internet, which has increased the use of data analytics and is driving the market's expansion.

Market Restraining Factors

Increase in privacy and security breaches among businesses

Data gathering can occasionally violate a customer's privacy because the companies whose services they are utilizing have access to information about their online transactions, purchases, and subscriptions. Some businesses might trade datasets with other businesses for mutual gain. There is a possibility that some of the data obtained could be used maliciously against an individual, nation, or society. Companies need to be careful about the kind of data they are gathering from clients and make sure the data is secure and protected. Only the data necessary for the analysis must be collected, and any sensitive data must be anonymized in order to keep it secure. As a result, these privacy concerns are hampering the growth of the market.



The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships & Collaborations.

Type Outlook

Based on type, the market is segmented into prescriptive analytics, predictive analytics, customer analytics, descriptive analytics, and others. The predictive analytics segment garnered the highest revenue share in the market in 2022. Predictive analytics offers precise and trustworthy insights that assist firms in finding solutions to issues and seeing opportunities, such as spotting fraud, improving marketing campaigns, enhancing decision-making, and increasing operational efficiency. Today's businesses are flooded with data, which can range from log files to photos and video, stored in various locations around the company. Data scientists employ machine learning and deep learning algorithms to identify patterns in this data and forecast future events.



Solution Outlook

On the basis of solution, the market is fragmented into security intelligence, data management, data monitoring, and data mining. The security intelligence segment acquired the highest revenue share in the market in 2022. The segment is expanding because sophisticated analytics are used more frequently to spot fraud, streamline procedures, and manage data risks. Over the projection period, segment expansion is anticipated to be fueled by an increase in the adoption of data analytics software that offers secure transaction processing, control access to client records, and enhanced customer service.

Application Outlook

By application, the market is divided into supply chain management, enterprise resource planning, database management, human resource management, and others. The enterprise resource planning segment garnered a remarkable growth rate in the market in 2022. Applications for data analytics can connect data lakes, traditional databases, and data warehouses to combine Big Data with data from business applications to enhance analysis, forecasting, and planning. Additionally, the requirement to access and evaluate databases is growing as firms depend more on data-driven decision-making. The rapid expansion of big data, which created even more complexity for organizations to manage due to the segment's growth, was fueled by the quick development of artificial intelligence, IoT, hybrid cloud, and edge computing.

Regional Outlook

Region wise, the market is analysed across North America, Europe, Asia Pacific, and LAMEA. The Asia Pacific region acquired a substantial revenue share in the market in 2022. This results from the growth of other industries, including automotive, BFSI, healthcare, and retail. Additionally, it is anticipated that the demand will grow as social media, the internet, cell phones, and communication technology advances all become more widely used. Data analytics is becoming increasingly popular due to adoption of information-intensive AI and ML features throughout several Asian nations, including China, India, and Japan. Market growth is accelerated by the increasing use of data analytics techniques and solutions.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Amazon Web Services Inc., IBM Corporation, Google LLC (Alphabet Inc.), Mu Sigma, Inc., Oracle Corporation, SAP SE, Sisense Inc, Microsoft Corporation, ThoughtSpot Inc. and Zoho Corporation Pvt. Ltd.

Strategies Deployed in the Market

Partnerships, Collaborations and Agreements:

  • Aug-2022: Google extended its collaboration with CoreLogic, a leading global property data and analytics-driven solutions provider. Through this collaboration, Google focused on supporting the launch of the CoreLogic Discovery Platform. The platform was built on Google Cloud’s sustainable and secure infrastructure. The collaboration aims to fulfill CoreLogic’s clients’ demands and allows the provision of efficient and comprehensive solutions for enterprises in the real estate finance market.
  • May-2022: Amazon Web Services collaborated with IBM, an American multinational technology corporation. Through this collaboration, AWS aimed to enable IBM to provide a wide range of its software catalog as Software-as-a-Service (SaaS) on AWS. Moreover, the collaboration helped the customers of both companies in enhancing their modernization to the cloud and consuming IBM Services in a cloud-native manner on AWS.
  • Mar-2022: Microsoft entered into a partnership with FD Technologies, a leading provider of products and consulting services. This partnership aimed at Microsoft to expand the reach of its KX Insights streaming data analytics platform as many companies seek to develop the data infrastructure for real-time decision-making.
  • Feb-2022: Microsoft extended partnership with The Qatar Financial Center Regulatory Authority (QFCRA), an independent regulator of the QFC, incorporated to authorize and regulate firms and individuals conducting financial services in or from the QFC. This partnership aimed Microsoft to explore a dedicated path for solutions that enhances Artificial Intelligence (AI) and data analytics to obtain actionable information via social media analytics, Robotics Process Automation (RPA), AI-powered knowledge mining, chatbots, and to transform digital objectives.
  • Dec-2021: Google Cloud partnered with Kyndryl, an American multinational information technology infrastructure services provider. Following this partnership, the latter company focused on expediting the digital transformation of customers and assisting them in becoming more data-driven, advanced, and sustainable businesses. In this collaboration, Google and Kyndryl applied their expertise in applied AI, analytics, and data, thereby assisting customers in attaining new knowledge and driving business results.
  • Nov-2021: Amazon Web Services partnered with Nasdaq, an American stock exchange based in New York City. Under this partnership, AWS focused on providing the next generation of cloud-enabled infrastructure for the capital markets of the world. Additionally, the partnership provided Nasdaq a way to move its main infrastructure to the cloud and create new services as they advance its second decade of cloud adoption.
  • Nov-2021: Amazon Web Services collaborated with Teradata, a connected multi-cloud data platform for business analytics. With this collaboration, AWS aimed at expediting Teradata’s capabilities to fulfill the demands of the voluminous data workloads and subsequently help customers in utilizing data to modernize and innovate rapidly in the cloud. The collaboration accelerated the benefits and value that Teradata can provide to its customers.
  • Oct-2021: IBM formed a collaboration with Deloitte, a multinational professional services network. This collaboration aimed to introduce a new offering, DAPPER, which is an AI-enabled managed analytics solution. DAPPER's end-to-end capabilities would enable companies to gain confidence in the insights that their data offers through a secured, simple to consume managed service offering to resolve the challenges of adopting AI.
  • Aug-2021: IBM teamed up with Black & Veatch, a global leader in building critical human infrastructure. This collaboration aimed to jointly market Asset Performance Management (APM) solutions, which include remote monitoring technologies that integrate near real-time data analytics with AI to assist users to keep equipment and assets running at peak performance and reliability.
  • Aug-2021: IBM partnered with Cloudera, an American software company. Under this partnership, the companies would strengthen their joint development as well as go-to-market programs in order to bring the cutting-edge analytical potentials of IBM Cloud Pak for Data, a unified platform for AI and data, to the Cloudera Data Platform.
  • Mar-2021: Google Cloud collaborated with Deloitte, an international professional services network. Following this collaboration, the companies launched a platform for enterprises to assist them in handling cyber threats. This cloud-native platform is called PACE or Predictive Analytics for Cyber in Enterprises tool. The platform utilizes Deloitte's cyber risk quantification and risk management frameworks along with Google Products namely Loker, Chronicle, and BigQuery. PACE enables companies to identify and mitigate cyber threats.
  • Mar-2021: Oracle came into partnership with Red Bull Racing Honda. Under this partnership, Red Bull would leverage the ML and data analytics offerings of Oracle Cloud Infrastructure (OCI) to optimize how data is utilized over its business; from on-track tasks to putting more data in the hands of the Team’s global fan base. In addition, the OCI-powered offerings would assist the team to sharpen its already formidable competitive edge.
  • Feb-2021: SAP entered into a partnership with Software AG, an enterprise software company. This partnership aimed to enhance surface supply chain management data to improve product quality. Additionally, the partnership would bring sensor-generated time-series data into the analytics and operational performance fold.

Product Launch and Product Expansion:

  • May-2023: ThoughtSpot revealed ThoughtSpot Monitor for Mobile, a mobile application that works with the ThoughtSpot analytics application. The new ThoughtSpot Monitor for Mobile delivers key performance indicators (KPIs) and other business metrics to users.
  • Nov-2022: IBM launched IBM Business Analytics Enterprise. The new product is a comprehensive suite that includes budgeting, reporting, forecasting, planning, and dashboard capabilities, providing the user with a holistic view of data sources across the entire business.
  • Sep-2022: ThoughtSpot unveiled ThoughtSpot Cloud, a fully managed SaaS offering based on its popular augmented analytics platform. The new platform is packed with artificial intelligence and automation. ThoughtSpot Cloud features a full-stack architecture and intuitive insight generation capabilities via the in-memory calculation engine.
  • Mar-2022: Microsoft unveiled Azure Health Data Services, a platform for analyzing and managing different kinds of patient data. The launched platform-as-a-service (PaaS) assists enterprises in managing disparate kinds of protected health information (PHI) spanning over multiple data stores and allowing them to work with -- and gather insights from -- patient data utilizing fewer resources and time.
  • Nov-2021: Oracle expanded its product line with new capabilities in Oracle Fusion Cloud Enterprise Resource Planning (ERP) Analytics. This product expansion aimed to allow finance and operations leaders to have higher visibility into costs and assets and fasten decision-making. Oracle Fusion ERP Analytics would provide the insights required to easily analyze working capital and procurement, revenue, payment performance, and profitability.
  • Jun-2021: SAP unveiled the SAP Business Network, integrating the vendor’s logistics, purchasing, and asset intelligence software & services. In addition, the company also introduced new planning and analytics capabilities for the vendor’s Business Technology Platform, along with new planning & data analysis capabilities and advancements to the SAP Business Technology Platform (BTP).
  • Mar-2021: Oracle unveiled a set of innovative enhancements to Oracle Autonomous Data Warehouse. These enhancements offer easy-to-use, no-code tools, which would empower Data Analysts to do tasks that earlier needed data engineers and data scientists.
  • Feb-2021: Sisense unveiled a new AI-driven analytics platform called Sisense Fusion. The new platform features actionable intelligence made up of five key components (Fuse, Connect, Analyze, Augment, Infuse) to enable businesses to make improved decisions, as well as the ability to embed analytics into customer-facing applications.

Acquisitions and Mergers:

  • Jan-2022: Oracle took over Federos, a leading provider of cloud-enabled, AI-optimized network assurance, analytics, and automation software. With this acquisition, Oracle focused on empowering service providers with AI-optimized service and network analytics, assurance, and automated orchestration.
  • Jul-2021: Microsoft took over Suplari, a Seattle startup that utilizes AI to aid companies to understand and get a handle on spending. This acquisition aimed to aid customers to enhance financial visibility by using AI to automate the analysis of existing data and historical patterns from numerous data sources.
  • May-2021: ThoughtSpot entered into an agreement to acquire Diyotta, a data integration tool that connects enterprises to all their data. The acquisition would enable the company to further boost the ecosystem for the Modern Analytics Cloud, helping connect and integrate the analytics platform of the company with technologies across this growing industry.
  • Feb-2021: Amazon Web Services (AWS) acquired DataRow, a Web-based client for the Amazon Redshift cloud data warehouse. Through this acquisition, AWS enabled customers to offer users better AWS visualization & query resolution.

Scope of the Study

By Type

  • Predictive Analytics
  • Customer Analytics
  • Descriptive Analytics
  • Prescriptive Analytics
  • Others

By Application

  • Supply Chain Management
  • Enterprise Resource Planning
  • Database Management
  • Human Resource Management
  • Others

By Solution

  • Security Intelligence
  • Data Management
  • Data Monitoring
  • Data Mining

By Geography

  • North America
  • US
  • Canada
  • Mexico
  • Rest of North America
  • Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
  • LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Key Market Players

List of Companies Profiled in the Report:

  • Amazon Web Services Inc.
  • IBM Corporation
  • Google LLC (Alphabet Inc.)
  • Mu Sigma, Inc.
  • Oracle Corporation
  • SAP SE
  • Sisense Inc
  • Microsoft Corporation
  • ThoughtSpot Inc.
  • Zoho Corporation Pvt. Ltd.

Unique Offerings

  • Exhaustive coverage
  • The highest number of Market tables and figures
  • Subscription-based model available
  • Guaranteed best price
  • Assured post sales research support with 10% customization free

Table of Contents

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Data Analytics Market, by Type
1.4.2 Global Data Analytics Market, by Application
1.4.3 Global Data Analytics Market, by Solution
1.4.4 Global Data Analytics Market, by Geography
1.5 Methodology for the research
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition and Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 Analyst's Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.3 Market Share Analysis, 2021
3.4 Top Winning Strategies
3.4.1 Key Leading Strategies: Percentage Distribution (2019-2023)
3.4.2 Key Strategic Move: (Partnerships, Collaborations and Agreements: 2019, May - 2022, Aug) Leading Players
Chapter 4. Global Data Analytics Market by Type
4.1 Global Predictive Analytics Market by Region
4.2 Global Customer Analytics Market by Region
4.3 Global Descriptive Analytics Market by Region
4.4 Global Prescriptive Analytics Market by Region
4.5 Global Others Market by Region
Chapter 5. Global Data Analytics Market by Application
5.1 Global Supply Chain Management Market by Region
5.2 Global Enterprise Resource Planning Market by Region
5.3 Global Database Management Market by Region
5.4 Global Human Resource Management Market by Region
5.5 Global Others Market by Region
Chapter 6. Global Data Analytics Market by Solution
6.1 Global Security Intelligence Market by Region
6.2 Global Data Management Market by Region
6.3 Global Data Monitoring Market by Region
6.4 Global Data Mining Market by Region
Chapter 7. Global Data Analytics Market by Region
7.1 North America Data Analytics Market
7.1.1 North America Data Analytics Market by Type
7.1.1.1 North America Predictive Analytics Market by Country
7.1.1.2 North America Customer Analytics Market by Country
7.1.1.3 North America Descriptive Analytics Market by Country
7.1.1.4 North America Prescriptive Analytics Market by Country
7.1.1.5 North America Others Market by Country
7.1.2 North America Data Analytics Market by Application
7.1.2.1 North America Supply Chain Management Market by Country
7.1.2.2 North America Enterprise Resource Planning Market by Country
7.1.2.3 North America Database Management Market by Country
7.1.2.4 North America Human Resource Management Market by Country
7.1.2.5 North America Others Market by Country
7.1.3 North America Data Analytics Market by Solution
7.1.3.1 North America Security Intelligence Market by Country
7.1.3.2 North America Data Management Market by Country
7.1.3.3 North America Data Monitoring Market by Country
7.1.3.4 North America Data Mining Market by Country
7.1.4 North America Data Analytics Market by Country
7.1.4.1 US Data Analytics Market
7.1.4.1.1 US Data Analytics Market by Type
7.1.4.1.2 US Data Analytics Market by Application
7.1.4.1.3 US Data Analytics Market by Solution
7.1.4.2 Canada Data Analytics Market
7.1.4.2.1 Canada Data Analytics Market by Type
7.1.4.2.2 Canada Data Analytics Market by Application
7.1.4.2.3 Canada Data Analytics Market by Solution
7.1.4.3 Mexico Data Analytics Market
7.1.4.3.1 Mexico Data Analytics Market by Type
7.1.4.3.2 Mexico Data Analytics Market by Application
7.1.4.3.3 Mexico Data Analytics Market by Solution
7.1.4.4 Rest of North America Data Analytics Market
7.1.4.4.1 Rest of North America Data Analytics Market by Type
7.1.4.4.2 Rest of North America Data Analytics Market by Application
7.1.4.4.3 Rest of North America Data Analytics Market by Solution
7.2 Europe Data Analytics Market
7.2.1 Europe Data Analytics Market by Type
7.2.1.1 Europe Predictive Analytics Market by Country
7.2.1.2 Europe Customer Analytics Market by Country
7.2.1.3 Europe Descriptive Analytics Market by Country
7.2.1.4 Europe Prescriptive Analytics Market by Country
7.2.1.5 Europe Others Market by Country
7.2.2 Europe Data Analytics Market by Application
7.2.2.1 Europe Supply Chain Management Market by Country
7.2.2.2 Europe Enterprise Resource Planning Market by Country
7.2.2.3 Europe Database Management Market by Country
7.2.2.4 Europe Human Resource Management Market by Country
7.2.2.5 Europe Others Market by Country
7.2.3 Europe Data Analytics Market by Solution
7.2.3.1 Europe Security Intelligence Market by Country
7.2.3.2 Europe Data Management Market by Country
7.2.3.3 Europe Data Monitoring Market by Country
7.2.3.4 Europe Data Mining Market by Country
7.2.4 Europe Data Analytics Market by Country
7.2.4.1 Germany Data Analytics Market
7.2.4.1.1 Germany Data Analytics Market by Type
7.2.4.1.2 Germany Data Analytics Market by Application
7.2.4.1.3 Germany Data Analytics Market by Solution
7.2.4.2 UK Data Analytics Market
7.2.4.2.1 UK Data Analytics Market by Type
7.2.4.2.2 UK Data Analytics Market by Application
7.2.4.2.3 UK Data Analytics Market by Solution
7.2.4.3 France Data Analytics Market
7.2.4.3.1 France Data Analytics Market by Type
7.2.4.3.2 France Data Analytics Market by Application
7.2.4.3.3 France Data Analytics Market by Solution
7.2.4.4 Russia Data Analytics Market
7.2.4.4.1 Russia Data Analytics Market by Type
7.2.4.4.2 Russia Data Analytics Market by Application
7.2.4.4.3 Russia Data Analytics Market by Solution
7.2.4.5 Spain Data Analytics Market
7.2.4.5.1 Spain Data Analytics Market by Type
7.2.4.5.2 Spain Data Analytics Market by Application
7.2.4.5.3 Spain Data Analytics Market by Solution
7.2.4.6 Italy Data Analytics Market
7.2.4.6.1 Italy Data Analytics Market by Type
7.2.4.6.2 Italy Data Analytics Market by Application
7.2.4.6.3 Italy Data Analytics Market by Solution
7.2.4.7 Rest of Europe Data Analytics Market
7.2.4.7.1 Rest of Europe Data Analytics Market by Type
7.2.4.7.2 Rest of Europe Data Analytics Market by Application
7.2.4.7.3 Rest of Europe Data Analytics Market by Solution
7.3 Asia Pacific Data Analytics Market
7.3.1 Asia Pacific Data Analytics Market by Type
7.3.1.1 Asia Pacific Predictive Analytics Market by Country
7.3.1.2 Asia Pacific Customer Analytics Market by Country
7.3.1.3 Asia Pacific Descriptive Analytics Market by Country
7.3.1.4 Asia Pacific Prescriptive Analytics Market by Country
7.3.1.5 Asia Pacific Others Market by Country
7.3.2 Asia Pacific Data Analytics Market by Application
7.3.2.1 Asia Pacific Supply Chain Management Market by Country
7.3.2.2 Asia Pacific Enterprise Resource Planning Market by Country
7.3.2.3 Asia Pacific Database Management Market by Country
7.3.2.4 Asia Pacific Human Resource Management Market by Country
7.3.2.5 Asia Pacific Others Market by Country
7.3.3 Asia Pacific Data Analytics Market by Solution
7.3.3.1 Asia Pacific Security Intelligence Market by Country
7.3.3.2 Asia Pacific Data Management Market by Country
7.3.3.3 Asia Pacific Data Monitoring Market by Country
7.3.3.4 Asia Pacific Data Mining Market by Country
7.3.4 Asia Pacific Data Analytics Market by Country
7.3.4.1 China Data Analytics Market
7.3.4.1.1 China Data Analytics Market by Type
7.3.4.1.2 China Data Analytics Market by Application
7.3.4.1.3 China Data Analytics Market by Solution
7.3.4.2 Japan Data Analytics Market
7.3.4.2.1 Japan Data Analytics Market by Type
7.3.4.2.2 Japan Data Analytics Market by Application
7.3.4.2.3 Japan Data Analytics Market by Solution
7.3.4.3 India Data Analytics Market
7.3.4.3.1 India Data Analytics Market by Type
7.3.4.3.2 India Data Analytics Market by Application
7.3.4.3.3 India Data Analytics Market by Solution
7.3.4.4 South Korea Data Analytics Market
7.3.4.4.1 South Korea Data Analytics Market by Type
7.3.4.4.2 South Korea Data Analytics Market by Application
7.3.4.4.3 South Korea Data Analytics Market by Solution
7.3.4.5 Singapore Data Analytics Market
7.3.4.5.1 Singapore Data Analytics Market by Type
7.3.4.5.2 Singapore Data Analytics Market by Application
7.3.4.5.3 Singapore Data Analytics Market by Solution
7.3.4.6 Malaysia Data Analytics Market
7.3.4.6.1 Malaysia Data Analytics Market by Type
7.3.4.6.2 Malaysia Data Analytics Market by Application
7.3.4.6.3 Malaysia Data Analytics Market by Solution
7.3.4.7 Rest of Asia Pacific Data Analytics Market
7.3.4.7.1 Rest of Asia Pacific Data Analytics Market by Type
7.3.4.7.2 Rest of Asia Pacific Data Analytics Market by Application
7.3.4.7.3 Rest of Asia Pacific Data Analytics Market by Solution
7.4 LAMEA Data Analytics Market
7.4.1 LAMEA Data Analytics Market by Type
7.4.1.1 LAMEA Predictive Analytics Market by Country
7.4.1.2 LAMEA Customer Analytics Market by Country
7.4.1.3 LAMEA Descriptive Analytics Market by Country
7.4.1.4 LAMEA Prescriptive Analytics Market by Country
7.4.1.5 LAMEA Others Market by Country
7.4.2 LAMEA Data Analytics Market by Application
7.4.2.1 LAMEA Supply Chain Management Market by Country
7.4.2.2 LAMEA Enterprise Resource Planning Market by Country
7.4.2.3 LAMEA Database Management Market by Country
7.4.2.4 LAMEA Human Resource Management Market by Country
7.4.2.5 LAMEA Others Market by Country
7.4.3 LAMEA Data Analytics Market by Solution
7.4.3.1 LAMEA Security Intelligence Market by Country
7.4.3.2 LAMEA Data Management Market by Country
7.4.3.3 LAMEA Data Monitoring Market by Country
7.4.3.4 LAMEA Data Mining Market by Country
7.4.4 LAMEA Data Analytics Market by Country
7.4.4.1 Brazil Data Analytics Market
7.4.4.1.1 Brazil Data Analytics Market by Type
7.4.4.1.2 Brazil Data Analytics Market by Application
7.4.4.1.3 Brazil Data Analytics Market by Solution
7.4.4.2 Argentina Data Analytics Market
7.4.4.2.1 Argentina Data Analytics Market by Type
7.4.4.2.2 Argentina Data Analytics Market by Application
7.4.4.2.3 Argentina Data Analytics Market by Solution
7.4.4.3 UAE Data Analytics Market
7.4.4.3.1 UAE Data Analytics Market by Type
7.4.4.3.2 UAE Data Analytics Market by Application
7.4.4.3.3 UAE Data Analytics Market by Solution
7.4.4.4 Saudi Arabia Data Analytics Market
7.4.4.4.1 Saudi Arabia Data Analytics Market by Type
7.4.4.4.2 Saudi Arabia Data Analytics Market by Application
7.4.4.4.3 Saudi Arabia Data Analytics Market by Solution
7.4.4.5 South Africa Data Analytics Market
7.4.4.5.1 South Africa Data Analytics Market by Type
7.4.4.5.2 South Africa Data Analytics Market by Application
7.4.4.5.3 South Africa Data Analytics Market by Solution
7.4.4.6 Nigeria Data Analytics Market
7.4.4.6.1 Nigeria Data Analytics Market by Type
7.4.4.6.2 Nigeria Data Analytics Market by Application
7.4.4.6.3 Nigeria Data Analytics Market by Solution
7.4.4.7 Rest of LAMEA Data Analytics Market
7.4.4.7.1 Rest of LAMEA Data Analytics Market by Type
7.4.4.7.2 Rest of LAMEA Data Analytics Market by Application
7.4.4.7.3 Rest of LAMEA Data Analytics Market by Solution
Chapter 8. Company Profiles
8.1 Amazon Web Services, Inc. (Amazon.com, Inc.)
8.1.1 Company Overview
8.1.2 Financial Analysis
8.1.3 Segmental Analysis
8.1.4 Recent strategies and developments:
8.1.4.1 Partnerships, Collaborations, and Agreements:
8.1.4.2 Product Launches and Product Expansions:
8.1.4.3 Acquisition and Mergers:
8.1.5 SWOT Analysis
8.2 IBM Corporation
8.2.1 Company Overview
8.2.2 Financial Analysis
8.2.3 Regional & Segmental Analysis
8.2.4 Research & Development Expenses
8.2.5 Recent strategies and developments:
8.2.5.1 Partnerships, Collaborations, and Agreements:
8.2.5.2 Product Launches and Product Expansions:
8.2.5.3 Acquisition and Mergers:
8.2.6 SWOT Analysis
8.3 Google LLC (Alphabet Inc.)
8.3.1 Company Overview
8.3.2 Financial Analysis
8.3.3 Segmental and Regional Analysis
8.3.4 Research & Development Expense
8.3.5 Recent strategies and developments:
8.3.5.1 Partnerships, Collaborations, and Agreements:
8.3.5.2 Acquisition and Mergers:
8.3.6 SWOT Analysis
8.4 Mu Sigma, Inc.
8.4.1 Company Overview
8.5 Oracle Corporation
8.5.1 Company Overview
8.5.2 Financial Analysis
8.5.3 Segmental and Regional Analysis
8.5.4 Research & Development Expense
8.5.5 Recent strategies and developments:
8.5.5.1 Partnerships, Collaborations, and Agreements:
8.5.5.2 Product Launches and Product Expansions:
8.5.5.3 Acquisition and Mergers:
8.5.6 SWOT Analysis
8.6 SAP SE
8.6.1 Company Overview
8.6.2 Financial Analysis
8.6.3 Segmental and Regional Analysis
8.6.4 Research & Development Expense
8.6.5 Recent strategies and developments:
8.6.5.1 Partnerships, Collaborations, and Agreements:
8.6.5.2 Product Launches and Product Expansions:
8.6.5.3 Acquisition and Mergers:
8.6.6 SWOT Analysis
8.7 Sisense, Inc.
8.7.1 Company Overview
8.7.2 Recent strategies and developments:
8.7.2.1 Partnerships, Collaborations, and Agreements:
8.7.2.2 Product Launches and Product Expansions:
8.7.2.3 Acquisition and Mergers:
8.8 Microsoft Corporation
8.8.1 Company Overview
8.8.2 Financial Analysis
8.8.3 Segmental and Regional Analysis
8.8.4 Research & Development Expenses
8.8.5 Recent strategies and developments:
8.8.5.1 Partnerships, Collaborations, and Agreements:
8.8.5.2 Product Launches and Product Expansions:
8.8.5.3 Acquisition and Mergers:
8.8.6 SWOT Analysis
8.9 ThoughtSpot, Inc.
8.9.1 Company Overview
8.9.2 Recent strategies and developments:
8.9.2.1 Partnerships, Collaborations, and Agreements:
8.9.2.2 Product Launches and Product Expansions:
8.9.2.3 Acquisition and Mergers:
8.10. Zoho Corporation Pvt. Ltd.
8.10.1 Company Overview

Companies Mentioned

  • Amazon Web Services Inc.
  • IBM Corporation
  • Google LLC (Alphabet Inc.)
  • Mu Sigma, Inc.
  • Oracle Corporation
  • SAP SE
  • Sisense Inc
  • Microsoft Corporation
  • ThoughtSpot Inc.
  • Zoho Corporation Pvt. Ltd.

Methodology

Loading
LOADING...