ClearStory Analytics Platform Improves Data Exploration

ClearStory Data is making advancements and core improvements in the upcoming release of its native Apache Spark platform. With Apache Spark 1.6, ClearStory further speeds exploration on big, diverse data when business users need unrestricted data discovery and free-form exploration to answer new questions. The resulting advantages are intuitive answers in ClearStory Interactive StoryBoards that leverage more data and sources to answer business questions with greater speed.

"Today, data is a company's lifeblood. On-demand data discovery and fast ad hoc exploration leading to new insights and material business outcomes is now an enterprise priority versus old ways of using predetermined dashboard reporting. Businesses need fast answers using complex data that's constantly changing," said Ali Tore, CPO of ClearStory Data. "Spark 1.6 in ClearStory's platform and business-friendly application drives even faster analysis and answers with large volumes of disparate data to make self-driven data decisions."

ClearStory Data, powered by advancements in Apache Spark 1.6, enables users to improve the speed of access, harmonization and blending, and to explore data to uncover business-ready insights. According to the vendor, benchmarks on the new Apache Parquet reader show a nearly 2X improvement in scan throughput. This update results in a boost in query and ad hoc exploration performance, enabling ClearStory users to discover insights on large data almost 50% faster.

In addition, Spark 1.6 introduces dynamic memory management that automatically tunes execution and cache-memory allocations at runtime. As a result, with more memory available for complex operations and aggregations when needed, ClearStory delivers faster analytical processing and rapid data harmonization of large, sophisticated workloads that enable use cases that might be too difficult otherwise. And finally, users will be able to harness the power of immediate, actionable insights on real-time data streams. The streaming and ML capabilities in Spark 1.6 speed complex data discovery on large data streams.

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