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Arcadia Data Launches Arcadia Enterprise; Sets New Standard for Analytics and BI on Data Lakes

New Release Accelerates Insights With AI-Enabled, Real-Time Analytics on Big Data

Arcadia Data, provider of the first visual analytics and BI software native to big data, defines the next era of analytics and BI for data lakes with the general availability of its next major release of Arcadia Enterprise and Arcadia Instant. Arcadia Enterprise delivers on the promise of intelligent data lakes, enabling organizations to create billions of dollars of new value by improving access to analytics and BI for business analysts. With a data-native and AI-driven architecture designed from inception for big data, Arcadia Enterprise enables business users to easily explore data with recommendations that visualize and identify insights, enabling users to derive value with minimal IT overhead.

Priyank Patel
Priyank Patel

“Enterprises are realizing they need two BI standards — one for their data warehouse and one for their data lake. Traditional BI and discovery tools built with non-native architectures for data warehouses have failed when applied to derive value from data lakes. When we designed a native BI architecture that allows value to be realized faster than traditional BI architectures designed for relational databases, we opened the industry’s eyes to a new way of looking at visual analytics with BI, and to a new frontier regarding the data lake,” said Priyank Patel, co-founder and chief product officer at Arcadia Data. “Today’s release of Arcadia Enterprise solidifies that new standard for BI and visual analytics. With this release, Arcadia gives  business users the power to move the discovery process earlier in the value chain, learn from AI-driven recommendations and visualize fast-moving, streaming, and high-scale data all native to the data lake; enabling modern big data platforms to deliver valuable insights at tremendous scale.”

Data continues to evolve — structured to multi-structured, increased data volumes, real-time added to batch processing. Big data management platforms have evolved to handle those data changes: Technologies such as Apache Hadoop, Apache Kafka, Apache Spark, NoSQL, and public cloud storage, such as Amazon S3 and Microsoft Azure Data Lake Store (ADLS) are becoming ubiquitous. The analytics and BI tools that turn data into usable information have changed accordingly to support new levels of scalability, agility and information sharing. The new release fills the need for a second, focused analytics and BI standard for enterprises running data lakes that:

  • Offer greater scale at both the data volume and user concurrency levels
  • Handle more data formats, with ongoing changes, without significant IT intervention
  • Promote new levels of agility, self-service, and real-time analytics
Anupam Singh
Anupam Singh

“Big Data technologies continue to adapt to the changing data landscape, and the latest release of Arcadia Enterprise represents easier ways to leverage modern machine learning and analytics platforms like Cloudera,” said Anupam Singh, general manager, analytics, Cloudera. “With its native BI architecture and new features such as complex data type support and Solr support, Arcadia Data promotes analytical agility for our joint customers. We look forward to continued efforts with Arcadia Data to help customers meet their analytical requirements and accelerate their time to value.”

John Kreisa
John Kreisa

“More and more global organizations are evaluating Hadoop as a foundation for modern data architectures and are building sophisticated data lakes that create real business value,” said John Kreisa, VP of marketing, Hortonworks, Inc. “The Hortonworks and Arcadia Data partnership focuses on delivering value to customers and evolving innovation surrounding the data lake.”

Jack Norris
Jack Norris

“MapR has long been a leader in helping customers get the most value from their big data. With the latest product release from Arcadia Data, we deliver a joint offering that leverages our underlying data fabric to eliminate silos, reduce complexity and support real-time processing,” said Jack Norris, SVP of data and applications, MapR Technologies. “We believe that as data architectures continue to rapidly evolve, our partnership with Arcadia Data will ensure that all types of users will benefit.”

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