Artificial intelligence augments analytics provider, Kyligence, announced new cloud storage that leverages on OLAP analytics solution for big data analytics.
This new platform is based on Spark and Parquet, and uses machine learning capabilities to optimize cloud storage. Prior to this new platform, business intelligence (BI) is based on tenets with formal data sets.
The problem with BI is, it can’t be compatible with a higher volume of data, especially big data. With a big data platform, performance is enhanced and it supports interactive analysis.
The Kyligence Cloud 4 has a modern big data stack and the cloud. It’s designed for modern enterprises in need of storage for massive volumes of data, complete with scaling and smart query routing—first of its kind.
This new platform is available on Microsoft’s Azure marketplace and is optimized by Data Lake Storage. Best of all, it can scale data sources and feature computation, separate from the storage.
What’s more, the back end of the data source has a direct query for more detailed data. This is deemed to be effective for calculating the big data, focusing on the details, and minimizing the query times altogether.
Kyligence has added another layer for sub-second query response, in order to make aggregations more advanced and automatic. Unlike the outdated OLAP, the Cloud 4 has a specified cube with a machine learning-assisted approach.
In short, the machine learning capabilities shorten the response time against massive datasets with hundreds of terabytes and petabytes.
“Kyligence Cloud is a foundational technology at the heart of our centralized reporting platform build upon our Azure-based data lake. Now, for the first time, we are able to combine our data from Risk, Finance, and Treasury, creating a unified reporting layer,” said UBS CTO Brian Parone.
Bridges Data Query and Data Warehouses
The Kyligence Cloud 4 has the ability to overcome the challenges presented in querying data in different cloud environments, such as lakes and data warehouses. Through artificial intelligence and machine learning capabilities, making sense of data is improved for better business operations.
“Kyligence also solves the need for high performance, real-time analytics required by digital business. Looking forward, EMA expects Kyligence to further advanced its use of artificial intelligence in the platform to automate even more aspects of unified analytics,” said EMA research director John Santaferraro.
Cloud 4 supports 100TB data migration to a single Kyligence cube and another 1200 IBM Cognos cubes.
