Most Read This Week
Industry News Desk
Leverage Data Source Discovery By @Attivio | @CloudExpo #BigData #DevOps #Microservices
Data source discovery is the engine that drives Big Data analytics
By: Stephen Baker
Oct. 5, 2015 08:00 AM
Leverage Data Source Discovery to Become a Data-Driven Organization
As enterprises capture more and more data of all types - structured, semi-structured, and unstructured - data discovery requirements for business intelligence (BI), Big Data, and predictive analytics initiatives grow more complex. A company's ability to become data-driven and compete on analytics depends on the speed with which it can provision their analytics applications with all relevant information. The task of finding data has traditionally resided with IT, but now organizations increasingly turn towards data source discovery tools to find the right data, in context, for business users, data scientists, and BI analysts. These tools provide self-service data access speeding time to insight.
Data Source Discovery: The Great Divide
According to Forrester, organizations spend 80 percent of any analytics initiative on data integration. That means only 20 percent remains for developing business insights. And it can be even less. One data manager from an investment bank noted that data discovery and integration consumes upwards of 90 percent of every analytics program his firm undertakes. Sound familiar?
Moreover, 80 percent of data integration is spent on data source discovery - identifying and profiling data sources. So 64 percent of an entire analytics project can be consumed by a process that typically only scratches the surface of potentially usable data. As much as 90 percent of information stored by organizations today remains unknown and untouched.
As more connected devices and the Internet of Things (IoT) send us ever larger volumes of data, the importance of data source discovery can't be ignored. That would mean ignoring critical insights that improve decision making - and leaving substantial revenue and cost savings on the table. The lack of good tools for data source discovery continues to narrow the process bottleneck between data managers who own the data and business users who need access to it.
Failure: The Consequences of the Data Process Bottleneck
Success: What Does a Data-Driven Organization Look Like?
Data source discovery is the engine that drives Big Data analytics. It sets the stage for greater revenue, profitability, and operational efficiency.
Reader Feedback: Page 1 of 1
Subscribe to the World's Most Powerful Newsletters
Today's Top Reads