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.
- 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:
- What happened?
- Why did it happen?
- What will happen?
- What should I do about it?
- Business data stories
- Analytical models
- KPI libraries
- Data ingestion
- Data wrangling routines
- Canonical data models
- 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
- Enable an insights-driven enterprise
- Faster time to market
- Reduced TCO
- Increased “analytical throughput”