RESEARCH & RESOURCES

Recent Work: Philip Russom

Philip Russom

Philip Russom, Ph.D.

Senior Director of TDWI Research for data management

Philip Russom, Ph.D., is senior director of TDWI Research for data management and is a well-known figure in data management and business intelligence circles, having published numerous research reports, magazine articles, opinion columns, and more. Before joining TDWI in 2005, Russom was an industry analyst covering BI at Forrester Research and Giga Information Group. He also ran his own business as an independent industry analyst and BI consultant and was a contributing editor with leading IT magazines.

Research

Webinars

  • The Automation and Optimization of Advanced Analytics based on Machine Learning

    However, embracing machine learning successfully is challenged by ML’s serious data requirements. In development, designing an analytic model depends on very large volumes of diverse data. In production, an analytic model created via machine learning again needs voluminous data, so it can learn and improve over time. In turn, managing big data for machine learning demands a substantial data management infrastructure and tool portfolio. May 31, 2018 View Now

  • Six Strategies for Balancing Risk with Data Value

    Managing data for value is a business-oriented focus on the potential of data. It complements the all-too-common obsession with data’s technical requirements. Data value recognizes that data is a valuable business asset and should be leveraged accordingly. If you are managing data for value, your asset portfolio of data should be protected, grown, and governed. March 29, 2018 View Now

  • Extending Your Data Warehouse Environment with Hadoop: Bringing Enterprise and External Data Together

    Surveys run by TDWI show that roughly a fifth of mature data warehouse environments now include Hadoop in production. Hadoop is becoming entrenched in warehousing because it can improve many components of the data warehouse architecture—from data ingestion to analytics processing to archiving—all at scale with a reasonable price. February 27, 2018 View Now

  • Building a Successful Data Lake in the Cloud

    Data lakes on Hadoop have come on strong in recent years because they help many types of user organizations – from Internet firms to mainstream industries – capture big data at scale and analyze or otherwise process it for business value. December 12, 2017 View Now

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