Analyst Report: Part 3 of 9, Data Integration: Removing Silos & Operationalizing Your Data

On Big Data

This is part 3 of a 9-part report, access all other parts here:

Part 1 – Data Connectors
Part 2 – Virtualized Data Layers
Part 4 – In-Memory Database/Grid Platforms
Part 5 – Data Warehouse Platforms
Part 6 – Business Intelligence (BI)
Part 7 – Business Intelligence on Big Data/Data
Part 8 РBig Data/Data Lake Platforms 
Part 9 –¬†Data Management and Governance

Strategy & Business Considerations

Organizations that must bring together operational data from in-house line-of-business systems and enterprise applications, such as enterprise resource management and customer relationship management, and integrating them at the right granularity, will need good integration technology to pull it off.

Integration technologies require work and investment but they ensure data is blended in a precise way that ensures a much higher quality of data for downstream analysis. Required skill sets range from good logical thinking and a comfort level authoring visual workflows to hardcore coding skills and an understanding of relational database operations.

Table of Contents

  1. Summary
  2. Strategy & Business Considerations
  3. Technical Considerations
  4. Technology Evolution & Landscape
    1. Data Integration Subcategories
  5. About Andrew Brust
  6. About GigaOm

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