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  • December 02, 2015 02 Dec'15

    Analysts and Data Scientists Need SQL-on-Everything

    Business analysts and data scientists no longer restrict themselves to internally produced data that comes from IT-managed production systems. For their analysis they use all the data they can lay ...

  • October 12, 2015 12 Oct'15

    Big Data Myth 4: Big Data is Unstructured Data

    Not so long ago I attended a session in which the speaker was very clear on what big data is and what it is not. In his opinion, big data is unstructured data and unstructured data is big data. ...

  • October 05, 2015 05 Oct'15

    Big Data Myth 3: Big Data is Too Big for SQL

    The third big data myth in this series deals with how big data is defined by some. Some state that big data is data that is too big for a relational database, and with that, they undoubtedly mean a ...

  • September 28, 2015 28 Sep'15

    Strengthening Data Preparation with Data Virtualization

    Self-service analytics allows users to design and develop their own reports and do their own data analysis with minimal support by IT. Most recently, due to the availability of tools, such as those ...

  • September 22, 2015 22 Sep'15

    Big Data Myth 2: Analytics Requires Big data

    In Part 1 of this series on big data myths I indicated that the goal of most big data projects is analytics. In other words, big data systems are almost always developed to improve the analytical ...

  • September 18, 2015 18 Sep'15

    Big Data Myth 1: Big Data is the Goal

    Big data is an incredibly popular topic. Plentiful articles, books, and blogs have been written on this topic and countless sessions have been presented that discuss some aspect of big data. I am a ...

  • July 02, 2015 02 Jul'15

    Convergence of Data Virtualization Servers and SQL-on-Hadoop Engines?

    Hadoop has become a popular and powerful platform for data storage and data processing. Data stored in Hadoop can be used by a wide range of applications and tools and for a wide range of use ...

  • June 30, 2015 30 Jun'15

    The Data Strategy is the Puzzle

    In the history of IT, the number of times that IT departments proposed to top management to invest in a new technology, a new data quality program, or a new design technique, but were not able to ...

  • April 15, 2015 15 Apr'15

    How Self-Service BI is Changing Data Modeling

    There was a time when data models were only touched by experts in white coats wearing soft cotton gloves while carrying them around. The data models were kept in a vault that Fort Knox would have ...

  • March 31, 2015 31 Mar'15

    Polyglot Persistence and Future Integration Costs

    Polyglot persistence must be the ugliest term we have ever come up with in the IT industry. It means that different persistency technologies (read data storage technologies) are used to store data. ...

  • March 31, 2015 31 Mar'15

    Data Virtualization and Data Vault: Double Agility

    Data vault is a modern approach to design enterprise data warehouses. The two key benefits of data vault are data model extensibility and reproducibility of reporting results. Unfortunately, from a ...

  • December 19, 2014 19 Dec'14

    The Time Is Ripe for Self-Service Data Preparation

    Implementing rules for detecting and cleansing incorrect data is almost always done by BI specialists and not by business users themselves. Is that going to change with the introduction of ...

  • December 16, 2014 16 Dec'14

    The Wondrous World of Data

    Since the first day of my career, I have been interested in all aspects of data: data modeling, data storage, database query languages, big data, data virtualization, data warehousing, data ...

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