George Mathew knows a thing or two about building analytic applications aimed at line-of-business users. Until last year he was a top executive inside SAP’s Business Objects division.
One of his jobs at SAP was to guide the company’s business intelligence strategy as emerging technologies like Hadoop, in-memory computing and other innovative approaches to data processing fundamentally change the way the enterprise thinks about analytics.
In fact, my colleagues spoke with Mathew at SAP Sapphire in 2011 inside theCUBE, where he discussed then SAP’s approach to BI in the age of Big Data.
Since then Mathew left the German software maker to join Alteryx, a Silicon Valley firm that in some ways shares a similar mission with SAP Business Objects – to empower line-of-business users with powerful analytics – but does so in a very different fashion. Where SAP has built its own in-memory analytics engine (HANA) and is building out a portfolio of out-of-the-box analytic applications, Alteryx offers a single, self-service platform that enables data scientists and business analysts to integrate data and build end-user analytic applications themselves via a simple visual interface.
The core pillars of the platform are its computational engine that allows data scientists to explore, integrate and analyze data from any number of sources — such as Hadoop, relational databases, and social networking APIs, both on-premise and in the cloud – and its graphical user interface, which presents data sources on what Mathew likens to a canvas. Data scientists and analysts just drag and drop icons to integrate data sources and build applications.
Once designed, analysts can publish the new analytic applications to either public or private cloud servers, where end-users can access them. There are also security and authorization capabilities built into the platform.
Alteryx counts a number of household names as customers, including McDonalds. The largest fast-food chain on the planet uses Alteryx to build analytic applications that bring together internal transactional data, outside data on competitors, and demographic data from Experian and the US Census. McDonalds’ analysts use the applications to decide where and when to open new restaurants.
During a recent call, Mathew showed me a demo of the product, building a simple Twitter analytics app and publishing it on the fly. It was fairly intuitive and definitely abstracts away the complexity of traditional, often hand-coded data integration and application development. More sophisticated data scientists and others may find the GUI format denies them some of the granular business logic control that coding allows them, however. Still, for most organizations the Alteryx platform could prove useful as they look to turn all the time, effort and money they’ve invested building Hadoop clusters and other Big Data infrastructure into value-add applications without having to hire an army of Big Data rocket scientists.
Alteryx offers free trial version of its platform for download if you want to check it out here.