Platfora CEO: How we deliver sharper analytics faster

CEO Ben Werther tells how Platfora's Hadoop-based solution upends old-fashioned, inflexible business intelligence processes

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An approach to enabling fast, unbounded BI
Platfora has rethought the status quo of big data analytics. It begins with the Hadoop Data Reservoir (HDR), which is our vision for how Hadoop can be used effectively within the enterprise as a single, central repository where all enterprise data can reside. The HDR serves as both the storage and the source of data for what we refer to as self-service analytics. It provides processing for data preparation and advanced analytics, ultimately eliminating data silos and reducing costs.

The integrated platform we developed to support a new era of self-service analytics helps to remove the obstacles to business intelligence described earlier by enabling an "interest-driven pipeline" of data controlled by the end-user. The end-user -- typically a business analyst -- can access raw data directly from Hadoop, which is then transformed into interactive, in-memory business intelligence. There is no need for a data warehouse or for separate ETL (extract, transfer, load) software and the headaches described above.

Platfora's integrated platform includes three key elements:

  • Data sets: Data sets form the foundational layer of the platform and are representations of raw data in Hadoop. They can be brought into Hadoop very easily and are cataloged and searchable in the Platfora Data Catalog. IT teams can maintain standard and commonly used data sets, and end-users can import their own data sets to join into the data model.
  • Lenses: Platfora automatically transforms massive datasets into highly responsive, in-memory Lenses, which function as on-the-fly data marts. Platfora's high-performance query engine scales out horizontally across multiple physical or virtual servers by distributing these columnar-compressed aggregates of data. Essentially, Platfora drives the Hadoop cluster to generate Lenses modeled to answer questions being asked by end-users. If the data necessary to answer the questions is not in the Lens, the end-user can create a new one without intervention from IT. Lenses in the Platfora platform are personal in-memory data marts that have been pulled out of Hadoop and presented to the end-user; they are refined and updated based on the specific needs of the user. Lenses are automatically refreshed when new data is added to Hadoop.
  • Vizboards: The front end of Platfora's integrated platform is a Web-based business intelligence application called Vizboards. Through Vizboards, users can analyze data from Lenses and organize relevant findings in a format that will be easily understood by stakeholders. Vizboards, which are based entirely on HTML5, function as Web-based canvases where business analysts can easily explore data and build visualizations, gaining insights and collaborating with others.

A new era of self-service analytics
Platfora's solution is designed to help businesses experience the increased dimensionality of their raw data. End-users can easily explore a broad spectrum of data or conduct fine-grained analysis, without having to start an entirely new analytics process. Additionally, organizations no longer have to worry about deciding up front what questions they will want to ask of their data later. Platfora also helps to support timely and efficient collaboration around business intelligence, which is important for businesses that want to exploit big data insights quickly for competitive advantage.

A core goal in designing the Platfora solution is to empower business analysts in enterprises to explore big data in ways not previously possible -- or never even considered before. Our vision for self-service analytics is also driven by the ideal that business users should have access to all of the data they need, without limitation, and be able to explore and combine internal and external data sets to answer questions that have not been possible or practical in the past. At the same time, data administrators retain the flexibility to set access controls to ensure data remains secure, as appropriate.

When business analysts are able to flag and share insights and easily "contribute back" to the organization, the enterprise can achieve greater agility. Just as important, when IT is no longer burdened by big data demands -- and these responsibilities become simple, highly routine processes -- teams are free to focus on adding value to the business in other ways.

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