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Data Analytics - Thematic Intelligence

Publisher GlobalData
Published Aug 09, 2023
Length 92 Pages
SKU # GBDT18180165

Description

Data Analytics - Thematic Intelligence


Summary

Human activity generates a vast amount of data, from databases containing information about citizens to user-generated content on social media platforms and sensor data generated by smartphones and industrial machinery. Many industry forecasts expect over 175 zettabytes of data to be generated by 2025. A zettabyte is as much information as there are grains of sand on all the world’s beaches. We are drowning in data, and making sense of so much information is becoming more difficult. Data analytics tools can help us convert raw data into valuable insights and actionable knowledge. GlobalData estimates the total data analytics market will be worth $188.8 billion in 2027, implying a 13% compound annual growth rate between 2022 and 2027.

Scope
  • This report provides an overview of the data analytics theme.
  • It identifies the key trends impacting growth of the theme over the next 12 to 24 months, split into three categories: technology trends, macroeconomic trends, and regulatory trends.
  • It includes a comprehensive industry analysis, including market size and growth forecasts for the global data and analytics market, alongside analysis of trends in GlobalData's proprietary signals data, including M&As, venture financing, patents, company filings, hiring, and social media.
  • The detailed value chain is split into four segments: hardware, data management, applications, and delivery.
  • Also included are profiles of leading players in the data analytics theme, including Alphabet, Amazon, IBM, Microsoft, Oracle, Salesforce, and Snowflake.
Reasons to Buy
  • Humans increasingly generate more and more data, largely due to the digitalization of our society, from databases containing information about citizens in a standardized format to user-created content on social media platforms and sensor data generated by smartphones and industrial machinery. Many industry forecasts expect over 175 zettabytes of data to be generated by 2025. We are drowning in data, and making sense of so much information is becoming difficult.
  • Data analytics help us go from raw data to useful insights and actionable knowledge. This report is an invaluable guide to a theme that is relevant to every company in every industry.

Table of Contents

92 Pages
Executive Summary
Players
Technology Briefing
The four primary types of data analytics
Data classifications
The data analytics pipeline
Enterprise data architecture
Collect
Store
Process and analyze
Visualize
Action
Governance, privacy, and security
It’s not just what you implement; it’s how you implement it
Trends
Technology trends
Macroeconomic trends
Regulatory trends
Industry Analysis
Market size and growth forecasts
Timeline
Signals
M&A trends
Venture financing trends
Patent trends
Company filing trends
Hiring trends
Social media trends
Value Chain
Hardware
Semiconductors
Cameras
Sensors and lasers
Servers
Storage devices
Networking equipment
Edge equipment
Data management
Data integration
Data aggregation
Data processing
Data storage
Data validation
Data governance and security
Applications
Descriptive analytics
Diagnostic analytics
Predictive analytics
Prescriptive analytics
Delivery
Hardware appliance
Licensed software
Analytics as a service
Companies
Public companies
Private companies
Sector Scorecards
Application software sector scorecard
Who’s who
Thematic screen
Valuation screen
Risk screen
Cloud services sector scorecard
Who’s who
Thematic screen
Valuation screen
Risk screen
IT infrastructure sector scorecard
Who’s who
Thematic screen
Valuation screen
Risk screen
Glossary
Further Reading
GlobalData reports
Our Thematic Research Methodology
About GlobalData
Contact Us
List of Tables
Table 1: Technology Briefing
Table 2: Technology trends
Table 3: Macroeconomic trends
Table 4: Regulatory trends
Trend Table 5:
Table 6: Key M&A transactions associated with the data analytics theme since January 2022
Table 7: key venture financing deals associated with the data analytics theme since January 2022
Table 8: Public companies
Table 9: Private companies
Table 10: Glossary
Table 11: GlobalData reports
List of Figures
Figure 1: Who are the leading players in the data analytics theme, and where do they sit in the value chain?
Figure 2: Technology Briefing
Figure 3: Descriptive and diagnostic describe the past; predictive and prescriptive are about the future
Figure 4: There are many different ways of classifying data
Figure 5: The data analytics pipeline includes collecting, storing, processing, analyzing, visualizing, and actioning
Figure 6: Data analytics technology stack
Figure 7: Data sources are infinite
Figure 8: Lakehouses aim to combine the benefits of lakes and warehouses with none of the drawbacks
Figure 9: BI dashboards help run businesses
Figure 10: The artificial intelligence value chain
Figure 11: Data science uses statistical techniques, ML, and huge datasets to identify KPIs and make predictions
Figure 12: Generative AI is integrated with data analytics tools
Figure 13: The core principles of data governance
Figure 14: The global data analytics market will be worth $189 billion by 2027
Figure 15: Asia Pacific and North America are the leading data analytics markets
Figure 16: The data analytics story
Figure 17: Data analytics M&A volume has been growing over the last 10 years
Figure 18: Data analytics venture financing volume has been steadily growing over the last 10 years
Figure 19: IBM, Alphabet, and Huawei lead the way in granted data analytics-related patents
Figure 20: Data analytics-related patent publications have accelerated since 2018
Figure 21: Data analytics mentions in company filings have steadily grown over the last five years
Figure 22: Data analytics-related hiring peaked in April 2022
Figure 23: Data analytics has been a somewhat declining talking point
Figure 24: The data analytics value chain - An overview
Figure 25: The data analytics value chain - Hardware – semiconductors
Figure 26: The data analytics value chain - Hardware – cameras
Figure 27: The data analytics value chain - Hardware – sensors and lasers
Figure 28: The data analytics value chain - Hardware – servers
Figure 29: The data analytics value chain - Hardware – storage devices
Figure 30: The data analytics value chain - Hardware – networking equipment
Figure 31: The data analytics value chain - Hardware – edge equipment
Figure 32: The data analytics value chain - Data management – data integration
Figure 33: The data analytics value chain - Data management – data aggregation
Figure 34: The data analytics value chain - Data management – data processing
Figure 35: The data analytics value chain - Data management – data storage
Figure 36: The data analytics value chain - Data management – data validation
Figure 37: The data analytics value chain - Data management – data governance and security
Figure 38: The data analytics value chain - Applications
Figure 39: The AI value chain - Delivery
Figure 40: Who does what in the application software space?
Figure 41: Thematic screen - Application software sector scorecard
Figure 42: Valuation screen - Application software sector scorecard
Figure 43: Risk screen - Application software sector scorecard
Figure 44: Who does what in the cloud services space?
Figure 45: Thematic screen - Cloud services sector scorecard
Figure 46: Valuation screen - Cloud services sector scorecard
Figure 47: Risk screen - Cloud services sector scorecard
Figure 48: Who does what in the IT infrastructure space?
Figure 49: Thematic screen - IT infrastructure sector scorecard
Figure 50: Valuation screen - IT infrastructure sector scorecard
Figure 51: Risk screen - IT infrastructure sector scorecard
Figure 52: Our five-step approach for generating a sector scorecard

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