Omdia reviews top data warehouses as they evolve into modern data analytics platforms capable of turning data into value for companies looking to survive and thrive amidst market disruptions.
Omdia Universe: Modern Data Analytics Platform, 2022
The Analyst Team
Bradley Shimmin
Chief Analyst, AI & Data Analytics
Brad has more than 25 years of experience in IT technology, analyzing data and information architectures. He is skilled in competitive market intelligence, technology selection, business development, and quantitative research. He also has experience as an IT professional, business analyst, book author/editor, and high-tech journalist/editor.
Brad helps enterprises and high-tech companies work effectively across several market areas, including enterprise data and analytics, artificial intelligence, digital transformation, and DevOps. His expertise also covers market evaluation and go-to-market messaging, and he has a background in software development and database administration.
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Fundamentals of Modern Data Analytics Platforms – 2022
Analyzes how these platforms are rapidly subsuming individual data lakes and data warehouses within a single, do-it-all platform capable of accelerating time to insight across the business.
Report / 20 May 2022 / Bradley Shimmin
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Analytics & Data Management Quarterly Briefing – 1Q22
Provides updates on the analytics and data management market, covering a new approach to data orchestration, insight into cloud-based data science workloads, and a preview of upcoming research on in-database machine learning. The attached presentation was shown at an analyst conference call on March 25, 2022.
Presentation / 25 Mar 2022 / Bradley Shimmin
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Analytics & Data Management Quarterly Briefing – 2Q22
Provides updates on the analytics and data management market, covering emerging technologies, as well as AI skills hiring practices. The attached presentation was shown at Omdia’s 2Q22 conference call on analytics and data management.
Presentation / 01 Jul 2022 / Bradley Shimmin
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These are Omdia driven recommendations based on content that is both similar, and has been frequently visited by other users in combination with the content you are currently viewing.
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