In today’s competitive business environment, actionable insights gained from Analytics and Big Data practices are an imperative. Organizations that leverage the power of analytics have significantly improved their business outcomes and are outperforming their competitors. The business value gained from analytics and big data enables enterprises to find new revenue opportunities, innovate faster, deliver superior quality products/ services and identify patterns to reduce fraud, as well as manage risks.

Analytics Gym®, is a consulting engagement by R Systems that identifies promising analytics use-cases, discover/ evaluate relevant data, assess technology capabilities, recommend changes and provide the right analytics approach to achieve the business goals.

Our experienced team of data scientists, analysts and expert consultants employ proven data science and analytics methodologies, by leveraging relevant data and applying the right analytics models on it, to offer your business a competitive edge in the marketplace.

How We Help

Organizations constantly seek to implement customized strategies, to extract meaningful insights from complex data sets.

DS-BuDAI® is a unique and proprietary methodology developed by R Systems that’s designed to help our clients go from raw data to actionable insights in a repeatable fashion. It blends Data Science/Analytics with a business focused strategic outlook to help ensure our clients achieve ROI from their various analytics initiatives.

The DS-BuDAI® methodology has four stages:


Business Understanding

  • Identify and engage all the stakeholders

  • Discuss opportunities with business heads/ users

  • Assess where Data Science/ Analytics can help improve the business processes

  • Identify specific promising use cases

  • Define and establish success criteria

  • Discuss risk factors


Data Usage and Understanding

  • Discover and explore existing data assets

  • Identify relevant data assets required to solve analytics use cases

  • Identify relevant data sources

  • Identify data experts/ gurus

  • Assess if existing data is readily available and usable in a single place

  • Assess if data has acceptable granularity and veracity

  • Evaluate data infrastructure and capabilities


Analysis and Assessment

  • Propose the right analytics approach

  • Identify required data transformations and quality measures for a successful analytics implementation

  • Identify existing analytics tools/ infrastructure and recommend new ones

  • Clarify what business value can be realized

  • Define POC options

  • Access the business impact of implementation



  • Understand the existing business processes where the analytics results are to be  employed

  • Define options for implementation based on business requirements & processes

  • Assess existing technologies for implementation and recommend new ones

  • Evaluate cost/ benefit

  • Benefits realization and implementation roadmap

  • Change Management issues

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