Why Stream Data Integration is a Must-Have Delivery Style
February 6, 2020
In the next few years, it is projected that more than half of major new business systems will use real-time connected data and continuous intelligence to improve decision-making. You can’t have continuous intelligence without continuous data ingestion or real-time connected data for decision-making if you’re working off data that is processed in batches – you need streaming data. Integrating streaming data into your enterprise data landscape requires re-thinking your delivery methods for transporting streaming data from the source to the target consumer. Stream data integration is the way you do that.
The Exciting Challenge of Big Data
For nearly a decade, analysts and industry experts have been talking about Big Data and the impact that it is going to have on organizations. Big data isn’t an “emerging trend’ anymore – it’s a business reality. What makes big data challenging (and exciting) is that it isn’t just big, it’s also fast. Organizations are being engulfed in a growing volume of data from a variety of sources. Some of the data is transactional, but most of it is what is called event streams – digital records of things taking place in the applications and devices that make up the IT ecosystem. This event stream data is where companies can identify fascinating trends, behaviors, and relationships that can enable them to understand their operations, their environment, and their customers better.
The amount of information in event streams can be enormous, but with the proper analytics, they can lead to valuable business insights in areas like fraud detection, supply chain optimization, customer support, resource scheduling, dynamic pricing, preventative maintenance, and achieving high availability in IT systems and services. Streaming data can help you identify events, opportunities, and threats faster, so you can respond quickly to minimize risk and maximize opportunity.
What is Stream Data Integration?
A new generation of Business Intelligence is on the horizon.
Historical transaction data has been the foundation for business intelligence (BI) and analytics for decades – analyzing past trends and behaviors to predict future events. That’s great in an environment where the data isn’t changing – but in modern IT environments, systems, processes, and data sources are changing continuously. As they say in the financial industry, “past results are not an indicator of future performance.” In a rapidly changing environment, business leaders make decisions based on near real-time data. Modern business intelligence systems are.” for this type of analytics, and the prospects are exciting!
Can’t My Reporting Tools Handle Streaming Data Already?
The answer to that question is “maybe” – it depends on what system you’re using for analytics and reporting. The challenge for most organizations is that there is no “one reporting tool.” There are many reporting and analytics platforms, apps, and systems in use across the enterprise, with a widely varying level of sophistication when it comes to capabilities for handling streaming data. You can’t depend on your reporting tools to handle this for you. You need to look at an integration platform like Actian Connect and Actian DataConnect to help you manage your data streams and normalize your data before loading it into your data warehouse that your reporting and BI tools can query.
A data warehouse like the Actian Data Platform can handle large volumes of streamed data to give you affordable cloud-scale capacity, economy, and high levels of processing performance that traditional data warehouses can’t match. The integrated connectivity of Data Connect puts you on the path to DataConnect to manage more streams.
Visit www.actian.com/data-platform to learn more.
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