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The purpose of TDWI Chapters is to enable local Business Intelligence/Data Warehousing professionals to:

  • Meet regularly with each other on a regional basis
  • Share best practices in a small group setting
  • Establish a strong network of peers
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Everyone is welcome. We encourage you to join TDWI, but you do not need to be a member to attend.

Denmark Chapter

The purpose of the Denmark Chapter is to enable local BI/DW professionals to:

  • Meet regularly with each other on a regional basis
  • Share best practices in a small group setting
  • Establish a strong network of peers
  • Gain technical advice and career direction

Everyone is welcome. We encourage you to join TDWI, but you do not need to be a member to attend.

  • “Designing, Managing & Operating a Distributed Data Lake” presented by Mr. Mike Ferguson

    05/19/2017

    Connect. Share. Learn.
    ATTENTION ALL BI/DW AND MASTER DATA MANAGEMENT PROFESSIONALS! 
    Please join us at TDWI Denmark Chapter on Friday the 2nd of June for another interesting presentation on BI/DW and master data management.



    Designing, Managing & Operating a Distributed Data Lake

    When:

    Friday the 2nd of June 2017 09:00–13:30

    Where:

    SAS Institute A/S
    Købmagergade 9
    1150 København K

    Agenda:



    08:30 – 09:00

    Registration and coffee with “Kanel fristelser”

    09:00 – 10:30

    Designing, Managing & Operating a Distributed Data Lake

    10:30 – 10:45

    Coffee Break

    10:45 – 12:15

    Designing, Managing & Operating a Distributed Data Lake

    12:15 –12:30

    TDWI DK General Assembly

    12:30 – 13:30

    Networking, Sandwich and Refreshments

    Please RSVP.
    Don’t miss this chance to hear Mr. Mike Ferguson and to connect with your peers

    For more information about TDWI Membership, contact chapters@tdwi.org or tdwi.denmark@hotmail.com
    Please RSVP.
    Connect also to our group on LinkedIn: TDWI – The Data Warehouse Institute - Denmark
    Abstract                                           
    Designing, Managing & Operating a Distributed Data Lake

    For many companies, the number of new data sources that a business wants to analyze is rapidly increasing. In addition, data integration is now happening almost everywhere in the organization whether it be for master data management, data warehousing, building data marts, data science projects, real-time analytics, or self-service BI. The result of all this activity is that the cost of data integration is rising rapidly, silos are emerging and complexity in terms of managing a governing data has the potential to spiral out of control.

    Therefore, many are saying, create a data lake. Put all data in one place where you can clean and integrate it for any purpose.  However, data is being collected in many different locations across the enterprise and in the cloud with much of it too big to move. So how do you manage and govern this environment? How do you accelerate delivery of trusted data that is ready for business use? This session looks at this problem and proposes a new collaborative information architecture to organize, govern, rapidly process, and manage distributed big and small data to provision it to wherever it is needed.

    • Data integration complexity
    • The siloed approach to managing and governing data
    • A new inclusive approach to governing and managing data
    • Introducing the distributed data reservoir and data refinery
    • Goals of a data reservoir
    • How does a data reservoir and data refinery work?
    • Tasks and services to manage and prepare data
    • The mission-critical importance of an information catalog in a distributed data landscape
    • Managing multiple data integration tools in a distributed data reservoir and data refinery
    • The publish and subscribe model for readying information
    • Mapping new data and insights into your shared business vocabulary
    • Enabling the dynamic data map—managing metadata in a graph database
    • Creating an Amazon for data—ordering trusted data as a service

     

    Biography
    Mike Ferguson is managing director of Intelligent Business Strategies Limited. As an analyst and consultant, he specializes in business intelligence and analytics, data management, big data, and enterprise architecture. With over 35 years of IT experience, Mike has consulted for dozens of companies on business intelligence strategy, technology selection, enterprise architecture, and data management. He has spoken at events all over the world and written numerous articles. Formerly he was a principal and cofounder of Codd and Date Europe Limited—the inventors of the Relational Model, a chief architect at Teradata on the Teradata DBMS and European managing director of database associates. He teaches popular master classes in big data, predictive and advanced analytics, fast data and real-time analytics, enterprise data governance, master data management, data virtualization, building an enterprise data lake, and enterprise architecture.

Please note that TDWI Premium Membership, while encouraged, is not required to attend this TDWI Denmark chapter meeting. If you value the information and networking opportunities you experience at TDWI Chapter events, you can further empower your career by becoming a TDWI Premium Member. TDWI Premium Membership arms you with a powerful, comprehensive, and constantly growing selection of industry research, news, online content, and peer networking opportunities developed exclusively for Premium Members. TDWI Premium Members also receive discounts on TDWI conferences, seminars, and CBIP exams.
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For more information about TDWI Premium Membership, contact membership@tdwi.org.

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