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ClearStory Data Empowers Business Analysts with Apache Spark 1.6 Advances

ClearStory-Data-LogoClearStory Data, the company bringing business-oriented Data Intelligence to everyone, announced advancements and core improvements in the upcoming release of its native Apache Spark platform. With Apache Spark 1.6, ClearStory further boosts fast exploration of insights on big, diverse data when business users need unrestricted data discovery and free-form exploration to answer new questions. The resulting advantages for global enterprises are intuitive answers in ClearStory Interactive StoryBoards™ that leverage more data and more sources to immediately answer critical business questions at speeds that are not achievable with traditional BI solutions and last-generation architectures.

As businesses grapple with larger, more sophisticated and more diverse data, they struggle to reach new insights that are timely and relevant. Data modeling on large and wide data sets poses a monumental challenge and time-consuming task. Resulting delays to critical insights and a loss of key business information can materially impact a business. When blending all the complex sources together to reach amplified insights, it’s an even more daunting task that takes weeks with traditional solutions.

ClearStory’s Apache Spark-native solution delivers business insights from diverse, large-scale data at speeds that enterprises in competitive, fast-moving markets demand. For example, mass-market retail, packaged good companies and life sciences analysts can now compare many thousands of different brands across global regions at very high speeds. It’s now viable to explore and keep abreast of hundreds of millions of data points that are constantly changing and need to be explored to see new insights.

ClearStory Data, powered by advancements in Apache Spark 1.6, provides the fastest way to access, harmonize and blend, and explore data to uncover business-ready insights through:

  • Increased on-demand query performance: Benchmarks on the new Apache Parquet reader show a nearly 2X improvement in scan throughput. This update results in a significant boost in query and ad-hoc exploration performance, enabling ClearStory users to discover insights on large data almost 50 percent faster.
  • Improved efficiency of large-scale data processing and Intelligent Data Harmonization™: Apache Spark 1.6 introduces dynamic memory management that automatically tunes execution and cache-memory allocations at runtime. 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 otherwise would be challenging and time-consuming in traditional BI to be achieved in a user-friendly application.
  • Faster insights on fast-changing data: Users will be able to harness the power of immediate, actionable insights on real-time data streams. The streaming and ML advances in Apache Spark 1.6 accelerate complex data discovery on large data streams.

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,” says Ali Tore, CPO of ClearStory Data. “Apache 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.”


Download insideBIGDATA: An Insider’s Guide to Apache Spark


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