Further Simplifying Big Data Analytics
In the past we’ve talked about simplifying big data analytics and the 80:20 rule for data analysis. Most organizations spend 80% of analytics efforts running and optimizing the business and 20% on advanced analytics, which includes advanced data mining, algorithm development and advanced predictive modeling.
Hadoop has seen very good adoption for big data analytics, specifically batch analytics for large datasets, and many organizations have initiatives to use it for advanced analytics and optimizing the business. Unfortunately, those organizations are struggling to derive value from their Hadoop implementations. They’re finding that analysis takes too long and requires specialized talent. Another issue is that getting data into Hadoop is difficult, getting meaningful analysis even more challenging.
In the past few months, we’ve introduced some innovate products for big data, including Splunk Hadoop Connect (bi-directional movement of data between Splunk and Hadoop) and Splunk DB Connect (enrich unstructured data with structured data), but our quest didn’t end there. At Splunk, the goal is always to make analysis easier and help end users derive value from the data, and analyzing data sitting at rest in Hadoop is still difficult.
To address this, we recently announced Hunk: Splunk Analytics for Hadoop, a new beta product. Hunk is a brand new offering that builds on Splunk’s big data analytics expertise. It enables companies to use the Splunk Search Processing Language (SPL) to create visualizations, dashboards and share reports on data in Hadoop.
With Hunk, users will be able to quickly start conducting meaningful analysis on data and derive value from their Hadoop implementations. Just point Hunk to your existing Hadoop cluster (Hunk is currently certified on Cloudera, Hortonworks and MapR distributions) and start finding insights without complicated programming or advanced analytics talent.
I am very excited about this product. Having dealt with large and untapped data at companies like eBay, and having talked to number of Hadoop users, this will clearly help expedite analysis of data in Hadoop and provide insights that will move the needle for the business. For analyst dealing with digital data, this is very exciting. Splunk provides real-time insights into web/mobile/social channels and can facilitate movement of data to cheaper storage. If data from digital channels is in Hadoop, Hunk can provide analytics without writing complex code, visualizations and sharing help democratize the information. Finding actionable insights from data in Hadoop just got easier with Hunk.