The right data blending toolsets enable your organization to access, integrate, cleanse, and consume data in record time and with a high degree of accuracy and security. With Impetus Data Blending solution that replaces a traditional ETL approach with a modern self-service driven data blending approach, enterprises can accelerate time-to-insight.
This solution brief explains how Impetus Data blending solution provides data quality controls, including baked-in security, and superior workload control via pause, quick resume, recover and other data pipeline controls.
Enterprises are demanding business value from Big Data. As a result, the ability to blend petabytes and exabytes of data from historical and streaming sources becomes a necessity and data warehouse modernization becomes a top priority.
Because the data warehouse is often thought of as the heart of an enterpriseâ€™s Big Data and analytics strategies, modernizing it has a potentially powerful and very positive effect on the bottom-line impact of new technologies, platforms, tools, and practices. No matter what modernization strategy is in play, all data warehouses require significant adjustments to the logical and systems architectures of the extended data warehouse environment.
Download the Forrester report â€˜The Next-Generation EDW Is The Big Data Warehouseâ€™ to get more insights on Data Warehouse Modernization.
Enterprises can use StreamAnalytix to take full advantage of the worldwide Open Source movement with a fully pre-tested and supported platform.
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Big Data Cluster Management Solution (Ankush)Ankush Cluster Manager is a web-based solution for Big Data cluster provisioning and management. It is an Open Source solution that offers multiple vendor support with support for multiple clusters and technology under one roof.
Kundera, an Open Source project backed by Impetus Technologies, is a JPA-based object-relational mapping (ORM) tool that facilitates the transition from RDBMS to NoSQL or NewSQL data stores while reducing the core challenges faced by Big Data application developers.