Use Hunk on Splunk to enhance enterprise security and make good business decisions
Big data is a term used for data sets so large or complex that traditional data processing applications are inadequate. It is one of the fastest growing types of data and requires a massive amount of storage to collect and retain the unstructured and poly-structured data. It is also used to analyze and reveal patterns, trends and associations, relating to human behaviors and interactions. Organizations have been gathering big data and storing it for a long time without an easy means to derive intelligence from the data.
Hunk on Splunk can help organizations wrangle their data by using the Splunk platform to communicate with big data stores like Hadoop and NoSQL. Through this integration, Splunk Enterprise Core ingests any machine data from the data stores and Hunk on Splunk uses virtual indexes to decouple the storage tierfrom the data access and analytics tiers. This then enables Hunk to transparently route requests to different data stores. Hunk uses data on read, which means the unstructured data is easily read during search time across different data sets.
The WWT Hunk on Splunk Workshop is a two- to four-hour strategic discussion and whiteboard session focused on identifying your companies business and security challenges. WWT experts customize the session to meet your companies’ specific areas of interest, which may include:
- Business Analytics and Intelligence – understanding and making agile business decisions based on the data derived from inputs into Hadoop and extracted by Hunk search queries across disparate data sets and types.
- Security Analytics – using the big data for security to derive historical and prospective analytics from machine data and correlate historical with real time data to hunt and investigate attacks occurring in the enterprise.
Hunk on Splunk can be used in a variety of ways to enhance security by providing historical and retrospective analytics and help make good business decisions by building models and using machine learning. Machine data is used to providesecurity analysts with a means to do investigative, forensic, retrospective and historical analytics to determine the method of attack. It is also used to help business analysts gain insights by understanding trends, patterns and gaining intelligence to better enable agile business decisions.