Data Analytics

Modak Nabu™ provides monitoring capabilities to data analytics teams

Modak Nabu™ provides self-service and monitoring capabilities to data and analytics teams to automate data preparation activities.

Modak, a leading provider of data engineering solutions, today announced the release of Modak Nabu 2.5. Modak Nabu 2.5 accelerates data preparation by 4x and provides faster data analytics by converging data ingestion, data profiling, data indexing, and data exploration into a unified and integrated modern data engineering platform.

“Modak Nabu 2.5 simplifies the complex process of onboarding data to different cloud environments. The newly added self-service capabilities and greater data management visibility in Modak Nabu will truly accelerate the data preparation journey,” says Milind Chitgupakar, Chief Analytics Officer and co-founder, at Modak.

As enterprises adapt to the digital-first world, data and analytics are driving key business decisions and processes. One of the major challenges for the success of data-driven initiatives is the availability of trustful and contextual data. At petabyte scale, discovering, ingesting, profiling, tagging, and transforming data, to make data consumable, takes months and sometimes, years to get into production.

By automating mundane and laborious data preparation tasks, Modak Nabu significantly reduces the time taken to make data available for analytics initiatives.

Modak Nabu™ includes active metadata as a primary driver and uses machine learning techniques such as data fingerprinting. Modak Nabu™ automates repetitive tasks and thus enables the 4x acceleration in the data journey for enterprise customers.

Benefits of Modak Nabu™:

  1. Automate data pipelines – Simplifies the process of onboarding data from a variety of sources to different cloud environments. 
  2. Automate data discovery and profiling – Democratizes access to data assets by making them accessible and understandable.
  3. Monitoring and Visibility – Provides a real-time view of the progress of data management tasks for different stakeholders, from operations to the executive team.
  4. Self-service data management – Complex data management tasks can be executed using a simple intuitive interface, with adequate governance controls.

For more such updates and perspectives around Digital Innovation, IoT, Data Infrastructure, AI & Cybsercurity, go to AI-Techpark.com.

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