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Deriving Value from Data Before It Goes Dark

Bruce_Reading_VoltDBIn this special guest feature, Bruce Reading, President and CEO of VoltDB, discusses the importance of capturing value from your data long before it goes dark. He explains how organizations can implement a fast data approach in a data pipeline before losing the value of real-time information to minimize the storage of dark data while maximizing the business value of real-time enterprise information. Bruce brings nearly 30 years of experience building teams and creating business value in a variety of strategic roles including sales, marketing, asset management, mergers & acquisitions and operations. Before joining VoltDB, Bruce was senior vice president and general manager for Compuware Corporation (formerly NASDAQ:CPWR). Bruce received his BS in Economics from McMaster University.

Every enterprise wrestles with how to harness the potential impact of company data, but the reality is that as enterprise data continues to be created at an epic scale, too much of this data is stored and rarely classified and accessed to provide significant business value.

Gartner defines dark data as, “The information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes.” As that data continues to increase, it consumes valuable storage resources and overhead costs.

Some of this data is classified after it gets into the data pipeline to support Big Data analytics. This helps the organization tremendously, because it means less dark data in the data lake and the ability to analyze historical data to derive management insights to improve business operations.

But unstructured and semi-structured data lacks tags, metadata or other schema, and once this data gets into Hadoop or another big data store, it is difficult and costly in terms of both time and IT resources to understand its value without extensive analysis.

The reality is that this approach is a post-facto attempt to enrich data after it gets into the data pipeline so it can be analyzed and leveraged as historical data. At this point is has lost the value of real-time data and days, weeks, or even months have often gone by from the time the organization ingested the data to the time it is available to analyze and take action based on the information.

It’s much more efficient to derive value from data before it goes dark by implementing a fast data solution in a data pipeline to ingest and analyze data in real time. This allows the enterprise to take action, automatically implement transactions, and make decisions based on information available in live data streams. Rather than losing time waiting for data at rest to be classified and made available for Big Data analysis, the enterprise can immediately analyze and act on real-time information, based on defined business policies.

The enterprise can gain instant insight into sales, production and distribution trends, and capitalize on opportunities to create value by leveraging instant insights to shape products and services and steer marketing and sales campaigns.

Any batch approach to storing, classifying and analyzing data can prove to be too little, too late for today’s agile, real-time business requirements. To maximize the potential business impact of your data, you need to capture value from your data long before it goes dark, understanding and executing business impact with precision, in milliseconds, on every piece of data that arrives at your door.

Well in advance of your data being buried deep in your IT infrastructure, you can harness the power of every data point that touches your company. Companies are already building next generation data pipelines that are seamless extensions of the intensive applications and analytic pipelines that exist today.

Utilizing a single fast data platform you can realize the operational richness and data interactivity of a traditional database with the speed and impact of real-time analytics. You can know what each of your customers want right now, can detect fraud and assess risk in real time, and gain immediate insights to shape management decisions that will nurture sales and drive business growth.

 

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