Technology/Services

‘Fast Data' to Overtake Big Data?

Investment growing in real time vs. batched analysis

SUNNYVALE, Calif. -- As the demand for insightful customer information grows, retailers are starting to hear about—and invest in—a more immediate version of data analytics, one that taps into “streaming” vs. “batched” or historic data, according to a new study.

Examining the adoption rate of “fast data” over “big data” analytics, a study from OpsClarity found that 92% of companies surveyed across a number of channels and verticals, including retail, are planning to invest in real-time analysis technology.

While many current analytics applications focus on batch processing, the study found that most businesses are looking to adopt stream-processing technologies aggressively within the next year. According to the survey, 89% of software developers, architects and “DevOps,” or development and operational professionals, currently use batch processing.

“With new fast-data technologies, companies can make real-time decisions about customer intentions and provide instant and highly personalized offers, rather than sending an offline offer in an email a week later,” said Dhruv Jain, CEO and co-founder of OpsClarity, a monitoring solution specific to fast-data services based in Sunnyvale, Calif. “It also allows companies to almost instantaneously detect fraud and intrusions, rather than waiting to collect all the data and processing it after it is too late.”

The survey, involving software developers, architects and DevOps professionals found that 79% plan to reduce or eliminate investment in batch processing and 44% cite lack of expertise on new data frameworks to analyze data-pipeline failures.

While so-called “big data” is associated with collecting, storing and analyzing large volumes of data, the analysis is usually done in offline mode, using historical data, OpsClarity officials said in a press release. The survey also revealed a shift in the use of data processing and analysis to serve core customer-facing applications, as opposed to only historical analytics such as big data to optimize internal business processes and aid future decision-making. When asked what the key business drivers are to leverage both fast data and big data, 32% said these powered core customer-facing applications, while 29% said these technologies powered analytics to optimize internal business processes. Thirty-nine percent said both.

“Real-time data and stream processing are becoming central to how a modern company harnesses data,” said Jay Kreps, CEO and co-founder of Confluent, a Palo Alto, Calif.-based streaming-data company. “For modern companies, data is no longer just powering stale daily reports—it’s being baked into an increasingly sophisticated set of applications, from detecting fraud and powering real-time analytics to guiding smarter customer interactions.”

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