Real World Application of Data Fabric to Address Access to Distributed and Fragmented Enterprise Data Across Data Silos.


Data engineering tasks demand a significant amount of attention from data scientists. It is widely acknowledged that activities like data collection, organization, cleaning, and data prepping are amongst the least enjoyable aspects of their work. Reducing this burden is crucial not only for the productivity and satisfaction of data scientists but also for enabling broader access to data across the enterprise.

Based on our extensive experience in driving business transformation, we have identified three key challenges that need to be addressed:
• Limited availability of convenient access to distributed global enterprise data for ad hoc querying.
• Inconsistent utilization and representation of data.
• Gaps in knowledge regarding the flow of business data within the enterprise.

To overcome these challenges, we employ the data virtualization approach. This approach conceals the complexities associated with accessing data from the underlying data systems, including their formats and structures. Unlike traditional Extract, Transform, Load (ETL) processes that require data to be collected into a separate repository for transformation, data virtualization enables on-the-fly transformation and aggregation without data replication. By connecting in real-time to the underlying data sources, data virtualization ensures that business users receive up-to-date data within their applications. Moreover, the view-based nature of data virtualization facilitates agility when adding, removing, or modifying underlying data sources.

Our approach significantly reduces the initial effort required for accessing relevant data, allowing data scientists to allocate their time towards high-value analysis rather than searching for and cleaning data. We have successfully demonstrated the ability to generate valuable data analytics products within a matter of days, as opposed to the prolonged timelines of weeks or months.


Mano is a seasoned technology executive with over two decades of expertise dedicated to business transformation through strategic technology deployment. His extensive background in enterprise architecture showcases a wealth of knowledge in crafting cognitive solutions across diverse industrial sectors. In his role as the Chief Architect and CTO of CRM Transformation, Mano spearheaded the engineering of a hybrid analytic platform that has left a lasting imprint on business outcomes. His visionary leadership has played a pivotal role in driving numerous artificial intelligence-driven transformation projects within the Customer Relationship Management (CRM) domain. With an unwavering commitment to innovation and a proven track record of delivering impactful results, Mano stands at the forefront of leveraging technology to propel organizational evolution and success.

Open Data Science




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