Splunk has proven to deliver real value to organizations by collecting and indexing massive amounts raw data generated from virtually any source and transforming this data into new, real-time insight. This type of detailed data being generated by machines and applications throughout an organization were previously untapped, but Splunk makes this data usable and accessible to solve real business problems such as preventing disastrous outages and service degradation.
Raw Data captured and indexed
Raw data visualized
To provide Splunk customers with yet more value, EMC and Splunk have teamed up to help customers manage the explosion of data across physical, virtual and cloud environments with a tested reference architecture for non-disruptive scalability, optimized performance, and simplified management. Download the EMC reference architecture guide to deploy a shared infrastructure for Splunk using VMware vSphere dynamic computing and EMC Isilon scale-out storage to enable higher levels of consolidation and utilization compared to traditional IT deployments.
I spoke with Hal Rottenberg, Data Center Practice Manager at Splunk to speak to the value the EMC Reference Architecture for Splunk and how this architecture addresses the rapid growth of data and users in Splunk environments.
1. Before we get into the EMC Reference Architecture, please describe Splunk and the value it provides.
Big Data: Understanding How Data Powers Big Business is yet another Big Data book to hit the market. What makes this book unique? There is practical advice and hands on exercises so that you end up with a Big Data action plan unique to your business after completion of the book. I spoke to the author, EMC’s own Big Data’s preeminent expert William Schmarzo, to explain the goals of his book and why organizations grappling with Big Data should pick it up.
1. What makes you a Big Data expert in providing practical advice for developing Big Data strategies?
To accelerate the value of Big Data, many products have been developed to make data managed in Hadoop much easier to access and analyze through SQL. First there was Hive, which provides a SQL query abstraction layer by converting SQL queries into MapReduce jobs. More recently, Cloudera announced Impala which bypasses MapReduce to enable interactive queries on data stored in Hadoop using the same variant of SQL that Hive uses. And today, EMC Greenplum announced Pivotal HD, the only high performing, true SQL query engine on top of Hadoop. Don’t be confused by these approaches, as there is a common thread – to leverage Hadoop as a Big Data platform for running SQL queries. The major difference with Pivotal HD is that now there is a single, scalable, flexible, and cost-effective data platform for all of your analytic needs.
I spoke with Greenplum Chief Scientist Milind Bhandarkar to explain this breakthrough SQL interface to Hadoop.
1. How does Pivotal HD provide a true, high performing SQL interface to Hadoop?
Everyone agrees that there is a shortage of Data Scientists. If not addressed soon, Big Data breakthroughs in areas such as healthcare, renewable energy, public sector, etc will decelerate. I am proud to say that EMC is doing its part to solve the problem by fostering Data Science development with training and certification, hands on expertise, web events, internships, and more. For example, EMC Education Services offers a 5-day Data Science and Big Data Analytics training and certification, designed to enable immediate and effective participation in big data and other analytics projects.
As a Big Data citizen, I want to motivate those thinking about moving into the world of Data Science, to take action and get trained. I met with Barry Heller, a developer for EMC’s Data Science curriculum, who leverages his extensive education and past experience as an EMC Data Scientist for curriculum development. If Barry’s story resonates and you relate in some way, I hope it inspires you to start a career in Data Science.
1) How many people have completed the EMC Data Science and Big Data Analytics training since its creation early this year?