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Digital Integration: Overcoming Enterprise Data Challenges

  • Digital Integration: Overcoming Enterprise Data Challenges-

    Islands of Disparate Data

    Data islands are created as a byproduct of operational and project moment-in-time decisions not made in the context of a larger data strategy. Layering of legacy systems conjoined with newer technologies and a lack of governance for data systems also results in data-related islanding of internal departments and work groups.

    This can lead to a limited purview and inhibit collaboration. Data gets siloed, whether it is enterprise data, equipment data inside an organization, or data across different organizations. This fragmentation makes data discovery difficult and presents complex technical and organizational challenges.

    When the data is scattered throughout manufacturing plants and the enterprise, integrating and analyzing it manually becomes resource-intensive and tedious. To extract meaning and value from data, new systems are required to handle the challenges posed by the volume, velocity, and variety of these Big Data sets.

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Digital Integration: Overcoming Enterprise Data Challenges

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  • Digital Integration: Overcoming Enterprise Data Challenges-3

    Islands of Disparate Data

    Data islands are created as a byproduct of operational and project moment-in-time decisions not made in the context of a larger data strategy. Layering of legacy systems conjoined with newer technologies and a lack of governance for data systems also results in data-related islanding of internal departments and work groups.

    This can lead to a limited purview and inhibit collaboration. Data gets siloed, whether it is enterprise data, equipment data inside an organization, or data across different organizations. This fragmentation makes data discovery difficult and presents complex technical and organizational challenges.

    When the data is scattered throughout manufacturing plants and the enterprise, integrating and analyzing it manually becomes resource-intensive and tedious. To extract meaning and value from data, new systems are required to handle the challenges posed by the volume, velocity, and variety of these Big Data sets.

Digitizing operations has become an imperative for the modern industrial corporation.  Technological progress in computing, sensing, storage and communications technologies has made it easier, faster and cheaper for organizations to accelerate adoption of Big Data and asset management technologies. 

However, with the growing volume of data from assets and operations, there are significant challenges that asset-centric companies need to overcome to reap the benefits of digitization. In this slideshow, Shefali Patel, director of strategy and marketing, GE Digital, discusses the challenges inherent in working with large volumes of data and how to successfully leverage enterprise data.