Data Analytics Strategic Intelligence Research: Market will be Worth $190 Billion in 2028 - SAS, IBM, Oracle, and SAP are Being Disrupted by AI-native Vendors


Dublin, Jan. 20, 2025 (GLOBE NEWSWIRE) -- The "Strategic Intelligence: Data Analytics" report has been added to ResearchAndMarkets.com's offering.

Total data analytics market will be worth $190 billion in 2028, implying an 11.1% compound annual growth rate (CAGR) between 2023 and 2028.






This report provides a detailed overview of the data analytics theme, focusing on key trends projected to influence growth within the next 12 to 24 months, categorized into technology, macroeconomic, and regulatory trends. It features a comprehensive industry analysis, including market size and growth forecasts for the global data and analytics market.

Human activity generates vast amounts 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.






Additionally, the report analyzes trends based on the analyst's proprietary signals data, covering mergers and acquisitions, venture financing, patents, company filings, and hiring activities. The value chain is meticulously divided into four segments: hardware, data management, applications, and delivery, providing a structured insight into the industry's framework.

Furthermore, the report profiles leading players in the data analytics field, such as Alphabet, Amazon, IBM, Microsoft, Oracle, Salesforce, and Snowflake, highlighting their roles and impacts within the market. This resource is essential for stakeholders looking to understand the dynamics of the data analytics sector and identify opportunities and challenges that could shape future strategies.

Key Highlights

  • Data analytics is a relatively mature market, yet significant innovation has occurred in recent years. Prescriptive analytics is the most advanced innovation, aiming to tell organizations what to do next rather than just describing what happened and why. Machine learning (ML) techniques can now provide data-driven recommendations by parsing large amounts of data and assessing "what if" scenarios. The traditional data analytics vendors such as SAS, IBM, Oracle, and SAP are being disrupted by AI-native vendors, such as Cognitive Scale and H2O.ai, which aim to help companies automate operational decision-making using ML. Furthermore, the emergence of generative artificial intelligence (AI) tools has led data analytics vendors to embed those solutions in their platforms, democratizing access to data science capabilities. For instance, Microsoft has launched Copilot, embedding ChatGPT into analytics products such as Excel and PowerBI.
  • The ability of generative AI to create highly sophisticated models and simulations from vast datasets raises significant concerns about the potential misuse of personal information. The risk of exposing sensitive data increases as these AI systems become more adept at generating detailed, realistic outputs. This calls for stringent data governance frameworks.

Reasons to Buy

  • 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.

Key Topics Covered:

  • Executive Summary
  • Players
  • Technology Briefing
  • Trends
  • Industry Analysis
  • Signals
  • Value Chain
  • Companies
  • Sector Scorecards
  • Glossary
  • Further Reading
  • Thematic Research Methodology

Data AnalyticsCompanies Featured

  • Alibaba
  • Alphabet
  • Alteryx
  • Amazon
  • Anthropic
  • Arista
  • Baidu
  • CData Virtuality
  • China Investment Corp
  • Cisco
  • Cloud Software Group
  • CognifiveScale
  • Cohere
  • Cohesity
  • Crowdstrike
  • Databricks
  • Dataiku
  • DataRobot
  • DataStax
  • Dbt Labs
  • Ericsson
  • H2O.ai
  • HPE
  • Huawei
  • IBM
  • IBM
  • Informatica
  • Intel
  • Meta
  • Microsoft
  • Microstrategy
  • Nokia
  • OpenAI
  • Oracle
  • Palantir
  • Qlik
  • Salesforce
  • SAP
  • SAS
  • Snowflake
  • Spark Cognition
  • Teradata
  • ThoughtSpot

For more information about this report visit https://www.researchandmarkets.com/r/wxg5ye

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