Most organizations see the benefits of real-time data, but costs and complexity hold back adoption. A new research report by DataStax sheds light on the state of real-time data in business.
Real-time system monitoring solutions are commonplace today. The same can’t be said for the early days of computing. Data was regularly processed at scheduled times, also known as batch processing.
Bank transfers were registered during the day and processed at night. As a result, systems remained available for urgent applications during business hours. Today, networks and processors are fast and affordable enough to run continuously. The data from a weather sensor is processed into a weather report without delay. Almost every bank allows real-time Internet payments.
DataStax recently interviewed more than 500 IT professionals in the United States. Roughly four out of five indicate that real-time data is essential for revenue growth and productivity. 71 percent see a direct link between revenue growth and real-time data usage. “Real-time data is air”, said Greg Sly, SVP of infrastructure and platform services at Verizon.
Challenges
Though most organizations agree on the benefits of real-time data, adoption remains a challenge. A system that ran on batch processing for the past 20 years can rarely transition to real-time data in a day. Moreover, some organizations have no infrastructure to process data into services and products at all. Companies struggle with costs and complexity.
“While the benefits of real-time data are widely recognized, survey respondents identified barriers—such as data complexity, controlling data costs, and data accessibility—to leveraging real-time data”, said Bryan Kirschner, vice president, Strategy at DataStax.
Solutions
Enormous service providers like Netflix and Amazon are ahead of the curve. High revenues and IT budgets make it easier to handle real-time data, but according to DataStax, smaller companies can adopt real-time data analytics as well.
An efficient data stack is one of the biggest barriers to real-time app development. DataStax provides turnkey data stacks. Developers receive a guideline and infrastructure for real-time app development.
One of the customers is Siggy.ai, the developer of a Shopify app that recommends relevant products to webshop visitors in real-time. Siggy.ai runs on DataStax Astra DB, a database-as-a-service based on Apache Cassandra.
Another example is Alpha Ori, an analytics provider for maritime companies. Alpha Ori’s software predicts machine maintenance and optimizes fuel consumption. The system data of ships is processed in real-time using DataStax Astra DB.
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