The term “big data” is a bit of misnomer. Big data got its name because of the large volumes of information that organizations were collecting and storing. While big data is indeed massive, it has little if any business value if you simply collect it and set it aside like paper documents in a file cabinet. Big data is only useful when you analyze it, produce insights from it, and apply those insights to your decision-making processes and business operations.

Volume represents just one component of big data. There is velocity, which refers to the constant flow of data and how that data flow is managed in near real time. There is also a wide variety of data, including the structured data from a traditional database and unstructured data such as text documents, email, video and social media messages.

Data analytics involves the methods, processes and technologies used to analyze big data to draw conclusions, identify trends and patterns, make better business decisions, and prove or disprove theories and assumptions. More specifically, the insights gained from data analytics can be used to improve operational efficiency, productivity, customer service and marketing effectiveness.

One type of big data that’s quickly growing in terms of volume, value and complexity is machine-generated data. Machine-generated data refers to information collected and generated by sensors, mobile devices, security tools and other equipment. This data provides you with a full record of transactions and activity, customer and machine behavior, security threats and incidents, and other important data. Armed with this operational intelligence, you can better understand, in-real time, what’s happening across your systems.

Machine-generated data represents most of the data in existence. When properly managed and analyzed, it can provide insights that help you enhance the customer experience, prevent fraud or a data breach, and efficiently maintain technology and equipment. However, because most machine-generated data is unstructured and produced outside the organization, it can be difficult to capture, correlate and analyze.

Splunk Enterprise delivers operational intelligence by collecting, indexing, monitoring and analyzing log and machine-generated data from any source. Splunk forwarders deploy to any device, server and equipment, and forward data in real time for analysis. With intuitive search, analysis and visualization capabilities, all types of users can analyze data from on-premises data centers, the cloud or both. There are also hundreds of Splunk applications that prepackage reports and dashboards for specific use cases.

Dell EMC recently announced a deeper partnership with Splunk to help organizations easily deploy analytics to address infrastructure and application issues, reduce downtime, and improve the customer experience. Dell EMC Ready Systems for Splunk enables organizations to combine Splunk analytics capabilities with the simplicity and scalability of Dell EMC VxRail Appliances, Dell EMC VxRack System FLEX, and Dell EMC hyper-converged infrastructure. These systems help you maximize your Splunk investment by consolidating, simplifying and protecting your machine-generated data.

Splunk Enterprise and the new Ready Systems from Dell EMC help you understand and analyze your data so you can solve business problems and identify new opportunities. Let us show you how to tap into the power of machine-generated data to drive efficiencies and business growth.

by Michael Renner, ProSys Partner Alliance Manager