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Wipro’s Data Discovery Platform

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Wipro’s Data Discovery Platform

Building intelligent enterprise with pertinent insights

Wipro’s Data Discovery Platform works at the confluence of the technology and business nerves of data-driven organizations. It is an exploratory analytics platform, hosted on the Google Cloud Platform and is offered in an Insights-as-a-Service model that makes it easy for organizations to consume insights and not worry about the tools, technologies involved in getting there.

Highlights:

  • Set of open source and Cloud technologies in a single platform architecture to accelerate the data-to-decisions value chain.
  • Enables analytical experiments with data of any volume, variety and velocity to derive insights, leveraging the suite of services offered by the Google Cloud Platform.
  • Modular, ‘app-driven’ model enables flexibility and scalability to meet the growing needs of a data-driven intelligent enterprise.

Move towards an insights-driven intelligent enterprise with Data Discovery Platform:

Insights on: 

  • What happened?
  • Why did it happen? 
  • What will happen? 
  • What should I do about it? 

Delivered through

  • Business data stories 
  • Visualizations 
  • Analytical models 
  • KPI libraries

Packaged components

  • Data ingestion
  • Data wrangling routines
  • Canonical data models
  • Workflow
    • Advanced visualizations – Vivid and intuitive representations of insights delivered through business data stories 
    • Accelerators for automation – Integration of accelerators across the value chain of data science process such as data exploration, data wrangling, model validation, and data management 
    • Vertical focused apps – Use-cases that provide pertinent insights for focused industry problems 
    • Advanced algorithms – Open source focused platform. Integration with H2O.ai that enables advanced algorithms for AI /ML 
    • Real time – API based access to prebuilt models and data that allows real time analytics implementation 
    • Unstructured data – Designed to handle high volume, variety and velocity of data across structured, text, audio, and image data

Range of analytics

  • Descriptive - Analyze past events from historical data and the patterns it creates
  • Diagnostic – Mine historical data to analyze past performance and examine possible reasons for success/failure
  • Predictive – Analyze data to determine the probability of a future event
  • Prescriptive – Recommend decisions and options for a future event to yield success or mitigate possible risk

Key benefits

  • Enable an insights-driven enterprise
  • Faster time to market
  • Reduced TCO
  • Increased “analytical throughput”
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