Harnessing Streaming Data Integration to Become a Data-Driven Enterprise

There is currently a surge in business investing in various types of analytics to solve their business challenges and achieve competitive advantage. The best analytic insight requires large amounts of data from multiple sources, which can then be feed through AI, ML, and analytics processes to garner new insights and make better decisions, as the amount of analytics storage highlighted in the chart below.

To obtain this data, businesses are turning to streaming data ingestion and integration to collect data about their operations, products, and services, and transform their companies' capabilities.

omdia dc storage chart 2020

Streaming data integration is based on technologies that move data in real-time from multiple sources across on-premises and cloud environments. The accumulation of quality data integrated from multiple operational sources and then centralized into a highly scalable repository is pivotal to data processing and obtaining meaningful insights.

Another challenge often encountered around managing multiple real-time data streams is the requirement to perform real-time data format transformation to a common format. Modern streaming data pipelines allow for this data transformation to be performed on the fly, maintaining real-time analytics processing.

On April 8, join us for an Omdia webinar, in which we'll discuss a modern data architecture for data collection, transformation, monitoring, and delivery of real-time data streams for analytics processing. The webinar will be led by Dennis Hahn, Senior Analyst, Data Center Storage, Omdia.