Most companies recognize the benefits of real-time data, but the cost and complexity are holding back adoption. That’s 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. Data was regularly processed at scheduled times, also known as “batch processing”.
Bank transfers were collected during the day and made in the evening. For example, the systems remained available during office hours for urgent requests. Networks and processors are now fast and affordable enough to run continuously. The data from a weather sensor is immediately processed into a weather report. Almost all banks allow real-time internet payments.
DataStax recently spoke with over 500 IT professionals in the United States. About four in five said real-time data is necessary for revenue growth and productivity. 71% of professionals see a direct link between revenue growth and real-time data usage. “Real-time data is oxygen,” commented 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 challenging. A system that has run on batch processing for the past twenty years can rarely be transferred to real-time data in a day. Additionally, some organizations have no infrastructure to process data in services and products. Businesses face cost and complexity.
“While the benefits of real-time data are widely recognized, survey respondents face barriers to using real-time data,” said Bryan Kirschner, vice president of strategy at DataStax. “For example, data complexity, data cost containment, and data accessibility.”
Huge service providers like Netflix and Amazon are leading the way with real-time data. High IT incomes and budgets make real-time data processing easier, but according to DataStax, small businesses can get started too.
An efficient data stack is one of the biggest hurdles in developing real-time applications. DataStax provides ready-to-use data stacks. Developers receive a guideline and infrastructure for real-time application development.
One of the clients is Siggy.ai, the developer of a Shopify app that presents relevant products to online store visitors in real time. Siggy.ai runs on DataStax Astra DB, an Apache Cassandra-based database-as-a-service solution.
Another example is Alpha Ori, a provider of analytics services for shipping companies. Alpha Ori’s software predicts machine maintenance and optimizes fuel consumption. Data from ship systems is processed in real time using DataStax Astra DB.
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