Collecting, storing, and analyzing data to achieve a business goal is by no means a new concept. However, use of the term “big data” has expanded, especially in the past decade, as mobile devices and applications and various Internet-connected assets have generated continuous streams of data in corporate networks.
This speaks to big data’s three components — volume, velocity and variety. Organizations are collecting massive volumes of data from a wide range of sources. The velocity of data streams has increased dramatically. The variety of big data includes everything from neatly structured databases to complex, unstructured data from email, video, text documents, social media platforms and financial transactions.
If an organization is unable to organize, integrate and analyze this data in a way that benefits the business, big data is nothing but a storage, bandwidth and management headache. Data analytics refers to the process of examining data, using specialized systems and applications, to uncover insights that enable faster, more-informed business decisions. Data analytics can answer queries and prove or disprove hypotheses, enabling organizations to optimize operations and productivity, better understand customer needs, improve marketing, and develop new products and services.
More Big Data Is Now Machine-Generated Data
Machine-generated data represents a fast-growing and complex piece of the big data pie. Machine-generated data is automatically created by a device or application without human intervention. Analysis of these highly diverse data sets can provide valuable insights into customer behavior and preferences, IT operations, the performance of IT infrastructure and other equipment, security threats, fraud prevention, and more.
Machine-generated data also drives the Internet of Things. With billions of Internet-connected “things” in use around the world, the vast majority of data is now generated by machines, not humans. Machine-generated data is mostly unstructured and often created outside the corporate network, making it difficult to manage.
The Splunk Solution
Splunk Enterprise simplifies the process of gathering, analyzing and acting upon machine-generated data from across the IT infrastructure, business applications and external systems. Data from all sources, whether on-premises or in the cloud, is collected, indexed in its native format, analyzed and turned into operational intelligence. Splunk Forwarders deploy to any device or asset, enabling you to search, monitor and interact with data in real time. You can correlate disparate data streams, identify patterns and exceptions, and create use case-specific reports from customized dashboards. With machine-learning capabilities, Splunk Enterprise becomes more intelligent as it processes more data.
Dell EMC recently announced an expanded partnership with Splunk and a portfolio of pre-engineered systems that are purpose-built for Splunk. Dell EMC Ready Systems for Splunk include all the resources needed to deploy and manage Splunk, helping organizations accelerate the resolution of infrastructure and application issues, reduce downtime, and improve customer satisfaction.
Big data is growing in all three of its key areas – volume, velocity and variety. Fortunately, technology that can help you extract business value from this data is becoming smarter and faster. Splunk Enterprise can help you harness the power of machine-generated data, regardless of the device or where it’s located, and Dell EMC Ready Systems for Splunk can simplify and accelerate Splunk adoption.