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Accelerite Releases ShareInsights 2.0
December 13, 2017 News analytics big data

 

Today Accelerite announced the release of the latest version of its Big Data analytics software, ShareInsights 2.0. What sets this analytics software apart is its ability to unify the big data analytics stack which in turn enables data preparation (ETL), OLAP, visualization and collaboration through a single interface. Accelerite claims that these abilities can potentially allow analysts to perform data preparation, analysis and visualization of millions of rows and terabytes of data in minutes. Also being announced today is Insight2Action, which is an automated process that drives specific actions from insights.

ShareInsights can run natively atop any Hadoop cluster, and this can be done without making any changes. It also leverages existing Spark instances. These two abilities mean that the software can enable machine learning and predictive analytics along with self-service data discovery. ShareInsights uses interactive visualization and dashboards to enable on the spot exploration or enabling insights on other visualization tools such as Tableau. The software allows users to easily collaborate sharing datasets, data flows, and insights from multiple sources.

Additional features include:

  • Ability to leverage multiple data sources: Analyze data from virtually any data source in any format — structured or unstructured, streaming or stored, CSV, ORC or available through APIs — using a comprehensive library of built-in connectors.
  • Insight creation: Blend IT-curated data with any other data-source of choice to create powerful new insights. Integrate insights and data with external products through inbuilt APIs.
  • Data governance and security: Ensure data governance at each layer with complete visibility and tracking. Ensure data and analytics security through role-based access, authentication, versioning and audit trails. Use existing Hadoop infrastructure without any customization and eliminate data migration outside the cluster.
  • Easy machine learning deployment: Capitalize on machine learning through a vast library of self-learning algorithms using drag-and-drop controls. Pre-integrated machine learning algorithms make analysis of unstructured data painless.
  • Futureproof analytics: Ensure that the analytics work you do today remains relevant and usable as underlying platforms evolve.

Big Data analytics primarily revolves around gaining insights from the data that can help the business generate more revenue, better help customers, or run more efficiently. But once the insights are gained they need to be acted upon creating a gap between discovery and action. Insight2Action does as the name implies, automatically creates an action based off of the insight garnered. This can be customized using a simple API.

This article was originally published on www.storagereview.com and can be viewed in full

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