Data & Analytics

Companies today are transforming themselves into digital businesses at an accelerating rate. Acquiring data, making it ready, and using advanced analytics in real time is the key to a successful digital business. Moving from today’s limited, time-delayed, on-prem business intelligence to on-prem or cloud-based real-time actions requires a new approach.

At the heart of the digital transformation is real-time data and analytics. Moving from databases to Data Lakes creates significant opportunities for quick and effective data management, lower IT costs, accelerated data capture and integration, and data delivery and advanced analytics across all types of data in a single environment.

Data warehouses and marts were built for reporting,
but Data Lakes are built for advanced analytics.

RCG helps clients realize value and develop expertise using Data Lakes in their business. RCG’s philosophy is that the purpose of Data & Analytics is:

  • Analytics should be used for Value Realization (analytic results that measurably increase revenues or decrease expenses including real-time analytics using advanced analytics like statistical analysis, relationship/graph analysis, machine learning, and AI);
  • Creating accurate analytics requires Data Lake Development (developing data ready to be used without any additional preparation or manipulation supporting many different data types, analytic use cases, machine learning, advanced analytics, and more with Data Lake curation for managing data in a Data Lake);
  • Developing trustworthy data requires Data & Analytics Management (the management process that ensures business data and analytics are ready for advanced and automated real-time actions with effective governance and data management); and

If an organization has problems in these areas, it needs to perform an Advanced Analytics Strategy (the Roadmap to realizing business value from data and analytic areas of opportunity and identifying additional opportunities to make use of advanced and automated analytics operating on Data Lakes). RCG also works with organizations to develop Proofs of Concept (PoCs), Pilot Projects, and Data Lake Stand-Ups. These services demonstrate and accelerate the use of Data Lakes and show the value that can be realized from them.

Big Data