Datameer and Tableau have teamed up to offer connections between big data and visualization analytics. Tableau customers can now leverage self-service big data analytics to augment legacy reporting and visual discovery capabilities. The two companies made the joint announcement on Tuesday, and a Datameer connector to Tableau software can help users consume, shape, enrich, and visualize data for all of their big data needs.
Datameer’s CEO Stefan Groschupf explains: “We purpose-built Datameer to have an open architecture so that we can easily augment our product to address customer feedback, or adapt to market changes. With our Tableau connector, our goal is to make it even easier to look beyond structured data to do so in Datameer, and then seamlessly visualize in Tableau.”
The partnership between Datameer and Tableau addresses common big data challenges and lets users leverage Hadoop in a self-service environment. Users can integrate within a familiar spreadsheet-style interface, and prepare and analyze all of their structured and unstructured data in Datameer with just one click and open it automatically in either Tableau Desktop or Tableau Server.
Combining Datameer and Tableau makes even the most common big data challenges self-service:
- Point-and-click data integration, including more than 70 pre-built systems and data connectors
- Big data blending driven by an interactive spreadsheet UI, not involving IT-changing schemas, and without taxing on your production system
- Simple data transformation with more than 250 pre-built analytical functions
- Event-based data analytics help users discover hidden behavioral patterns
- No advanced analytics coding required; clustering, decision trees and more are all drag-and-drop
In Datameer’s official press release, the company says: “In today’s data-driven business climate, both strong visualizations and rich analytics are incredibly important. There’s a clear need to distil large amounts of complex data into something tangible and quickly consumable. However, the immense amount of groundwork required to produce those insights in traditional business intelligence solutions mean businesses often settle for small data analysis.”
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