High-Frequency Decision Making: Embracing a Competitive Advantage

Because business doesn’t happen in neatly defined batches of time, there’s a big advantage to being able to make decisions in real time to respond to events in the moment. As a result, companies want new applications that incorporate low-latency processing to impact events as they happen.

New, exciting stream-based technologies are changing what’s possible, providing approaches that enable organizations to deal with low-latency decisions and respond to changing conditions.

In fraud detection, for example, the ability to analyze data and make a decision with very little delay allows organizations to mobilize quickly enough to shut down fraudulent activities before large losses occur.

Think about it this way: if you are only using big data for building models to periodically optimize a process, you’re running an “after-it-happens” business. To compete in today’s environment, you need to have powerful applications at your fingertips that can leverage data in the moment in order to make an impact on business operations in real time.

This ability can be thought of as “high-frequency decision making.” Consider these companies that are using high-frequency decision-making applications to stay ahead of the game, reduce costs, and mitigate risks:

-- A video advertising platform company provides publishers with technology and data so they can select, in real time, the best video advertisement to play at the right time for the right person. The company uses a converged data platform to house all their data in one place -- operations, support, sales, and other groups use the data repository to meet their business-related objectives.

-- A large hospital chain uses an event-based platform to handles real-time patient data, medical histories, and other data to improve patient care. The data platform brings together the high volume of structured and unstructured healthcare data into one central repository. Multiple groups in the organization can inexpensively store and access this data simultaneously, all within a secure HIPAA-compliant, Hadoop-enabled architecture.

-- A semiconductor manufacturer is able to use its converged data platform to improve yield management by leveraging real-time machine sensors for vibrations, heat, etc. The company can determine quality problems and correct issues much faster with this real-time analysis.

-- A leading worldwide provider of oil equipment, components, and services uses its big data platform to perform real-time analysis to optimize oil and gas drilling and production. The platform efficiently ingests and stores all time-series data from any source within the organization and makes it widely available to tools that talk Hadoop or SQL.

These examples are actual, deployed applications that are transforming organizations across a wide variety of industries, including manufacturing, telecommunications, government, advertising, entertainment, health care, life sciences, and financial services.

The key to these kinds of transformational applications is a converged data platform that eliminates separate data clusters. By eliminating silos, all of the data is available for applications to manipulate it in a wide variety of ways. By using the same platform to underpin operational applications, you can continuously update your models and make adjustments to business functions as things are happening. Instead of running a batch process to push out an updated model, you can adjust the model on the fly.

Event-based data flows drive these applications. Whether you’re collecting machine sensor data to predict failures or making offers to customers, a converged platform and event-based data flows are what enable these powerful use cases.

Forward-thinking companies such as those we’ve mentioned are able to differentiate themselves by taking advantage of a converged platform and converged processing. By bringing the processing to the data and harnessing these data flows, these organizations are able to analyze and understand this flowing data in context. That’s what data agility and high-frequency decision making are all about -- empowering the decision makers of the enterprise.

About the Author

Steve Wooledge is vice president of product marketing for MapR Technologies. Steve was previously vice president of marketing for Teradata Unified Data Architecture, where he drove big data strategy and market awareness across the product line, including Apache Hadoop. Steve also held various roles in product and corporate marketing at Aster Data -- an innovator in big data analytics -- prior to being acquired by Teradata. He can be reached at swooledge@maprtech.com.


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