Most companies realize the benefits of real-time data, but cost and complexity hinder adoption. This is according to DataStax based on a new research report.
It is common today to monitor servers and logs in real time. The early days of computing looked different. The data was regularly processed on schedule, also known as “batch processing”.
Bank transfers were collected during the day and made at night. For example, systems remained available during business hours for urgent requests. Networks and processors are now fast and affordable enough for continuous operation. The data from the weather sensor is processed in the weather report without delay. Almost every bank allows real-time online payments.
DataStax recently spoke with more than 500 IT professionals in the United States. About four in five indicated that real-time data is essential to revenue and productivity growth. 71 percent of professionals see a direct link between revenue growth and real-time data usage. “Real-time data is oxygen,” said Greg Sly, senior vice president of infrastructure and platform services at Verizon.
Most organizations agree on the benefits of real-time data, but adoption remains a challenge. A system that has run on batch processing for the past 20 years can rarely be transferred to real-time data in a single day. In addition, some organizations do not have an infrastructure at all to process data in services and products. Companies struggle with cost and complexity.
“While the benefits of real-time data are widely recognized, survey participants face barriers to using real-time data,” said Bryan Kirschner, Vice President of Strategy at DataStax. “For example, data complexity, data cost control, and accessibility.”
Giant providers, such as Netflix and Amazon, are leading the way with real-time data. Higher revenue and IT budgets make it easier to process data in real time, but according to DataStax, small businesses can also be started.
Efficient data stacking is one of the biggest barriers to real-time application development. DataStax provides ready-to-use data stacks. Developers receive guidance and infrastructure to develop applications in real time.
One of the clients is Siggy.ai, the developer of the Shopify app that delivers relevant products to web store visitors in real time. Siggy.ai runs on DataStax Astra DB, a database-as-a-service solution based on Apache Cassandra.
Another example is Alpha Ori, an analytics service provider for shipping companies. Alpha Ori software predicts machine maintenance and optimizes fuel consumption. Data from systems on ships is processed in real time using DataStax Astra DB.
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