Arcadia Data Looks to Streamline Big Data Search
Since emerging in June 2015, Arcadia Data has steadily upgraded its native Hadoop visual analytics platform to its latest hybrid iteration running both on the open-source framework and the cloud that now includes search-based business intelligence and analytics.
Arcadia Data, San Mateo, Calif., said this week its upgraded enterprise platform aims to make it easier for business users to query data via a “Google-like search interface.” The new functionality includes AI-based “guided questions” designed to recommend related database queries as well as ranking answers based on scoring questions against all available data sets. The “best answer” is displayed at the top of a list of possible query answers.
All this, the company claims, will help drive the “consumerization of data.”
Arcadia Data has previously paired its Hadoop-native OLAP “cube” of pre-aggregated data with a visualization and BI layer that’s designed to rapidly query data without moving any data off the cluster.
Arcadia Data’s web-based visual analytics tool served directly from Hadoop addresses a shortfall in many big data projects that are hampered by business intelligence and visualization tools that analyze only a limited portion of the data extracted by Hadoop and other data platforms.
Hence, the company strives to reduce data movement among proprietary platforms as a way of accelerating business intelligence tasks.
Arcadia Data said its upgraded platform is native to big data platforms, thereby eliminating data movement among separate BI servers. “This mitigates the delays and governance challenges that the traditional analytical life cycle creates,” the company said Tuesday (Sept. 4).
Along with Hadoop, Arcadia Data works natively with big data cloud stores like Amazon Simple Cloud Storage System and Microsoft Azure data lake storage as well as streaming systems like Apache Kafka. It also supports Oracle (NYSE: ORCL), Teradata (NYSE: TDC), the Snowflake cloud data warehouse and Amazon Redshift databases.