Traditional BI makes it very difficult for people in the business who know the story behind the data to actually gain direct access to the data. Instead, they submit data requirements to IT and when IT does finally deliver the data, it is typically only a subset or incomplete data, and in the wrong format. When data gets lost in translation, business users become frustrated, abandon analytics altogether, and operate on hunches and guesses. Fortunately Tableau solves this problem through its Self Service BI paradigm whereby any user in the organization can quickly gain direct access to the data needed, with flexibility to create any visualization imaginable (goodbye Excel!). But wait, there is more. Tableau has partnered with Pivotal to add a social element to these Self Service BI capabilities, whereby people in the business, data scientists, and IT can come together as a team to collaborate around data sets, visualizations, predictive models, and more to uncover new and better insight. The result – Big Data No Longer Lost in Translation.
Click inside to watch 11 Tableau customers talk about how Self Service BI has changed the way they do business
I spoke with Ted Wasserman, a Product Manager at Tableau to learn more about the value of their technology and partnership with Pivotal.
1. Let’s first talk about Tableau. Describe what part of the analytical process Tableau fits in and what problems it solves?
Our CMO Jeremy Burton is a visionary, always at least three steps ahead of the pack. I identified this gift early on, recalling Jeremy’s ability to excite a very calm and composed Technology Marketing team at Oracle 12 years ago through innovative ideas. I knew he was on the rise – Big and Fast. Yes, pun intended. Today, Jeremy’s vision at EMC is not only to harness Big Data to build a data-driven Marketing organization, but also to inspire other organizations to do the same in their Marketing departments through EMC’s Marketing Science Lab.
The Marketing Science Lab, built on EMC Big Data technology, provides a 360 degree view of customers in order to better understand their behavior and sentiment and improve marketing effectiveness. The Marketing Science Lab is not only accessible to EMC Marketers, but also presents itself through a highly visual dashboard application at EMC’s Executive Briefing Center in Santa Clara, CA. EMC’s Michael Foley leads the Marketing Science Lab and provides us with more insight into how this Big Data project is transforming EMC’s business and making everyone in Marketing addicted to analytics.
1. Can you describe the Big Data technology behind the Marketing Science Lab?
The announcement of OpenChorus Project a few months ago provided a glimpse into the upcoming EMC Greenplum Chorus Release 2.2 release and its superb integrations to accelerate Big Data time to value. Chorus Release 2.2 provides a single platform whereby users now gain direct access to filtered and clean Twitter feeds from Gnip, perform advanced analysis faster with the on-demand assistance from expert Kaggle data scientists, and share insights seamlessly through Tableau advanced visualizations.
Chorus 2.2 is now available for free download, with the same code base also available through the OpenChorus Project download. For those of you not familiar with Chorus, it is the only collaborative Data Science platform that streamlines the complex analytic process, enabling users to quickly create their own sandboxes, and easily collaborate around data sets, analysis, and findings. Additionally, open sourcing Chorus brings greater freedom. Anyone can download the source code and get started, modifying and extending it to any environment. This also promotes an ecosystem of applications and startups around Big Data applications, bringing extensibility into the product at a much higher velocity than we would be able to achieve on our own. For example, the release of Greenplum Chorus 2.2 includes valuable contributions from partners I mentioned earlier – Gnip, Kaggle, and Tableau. Have I peaked your interest to download Chorus 2.2? Here is a Q&A I conducted with Logan Lee, Director of Product Management at EMC Greenplum, to prepare you for success.
1. What are the system requirements or pre-requisites for Chorus 2.2?
Yes, Data Scientists do speak. In fact, the Data Scientist I spoke with for this blog piece is articulate, business savvy, and well polished. The term ‘mad scientist’ still applies to Data Scientists, as they are addicted to the iterative process of using knowledge, assumptions, and intuition to generate results from unruly data. The difference is that these information churners are not locked away in a lab, experimenting with data in isolation. Instead, they put themselves in the shoes of the business, and work with them to turn abstract business ideas into to tangible business value such as new revenue streams or improved operational efficiency.
Noelle Sio is a leading member of the EMC Greenplum Data Science Dream Team. My interview with her confirmed that Data Scientists are not just nerds, but rather, cool intellects with a diverse set of technical and interpersonal skills.
What skills are needed to be successful data scientist?