Data Aggregation Project Preparation: 10 Best Networking Practices
With the continued increase in human- and machine-created data pouring in from more devices than ever, the demand for more efficient data management is also on the rise. A growing number of enterprises have begun testing and deploying new software that specializes not only in data management, but also analytics. The industry's newest data management packages claim to offer increased productivity, competitive advantages and significant operational cost savings. However, as these companies begin to employ data aggregation to gather market intelligence and perform competitive analysis, there are many factors that IT managers should take into consideration. This eWEEK slide show examines 10 of those factors based on information from Isai Shenker, vice president of Product Management at Connotate. Connotate’s data extraction software feeds enterprise applications with competitive intelligence, financial intelligence, compliance, credential checking, and market research.
Identify the Sources of Data
With the vast amount of irrelevant data floating around behind the firewall and across the Web today, it is more important than ever to take a good look at the sources of the data collected. This will ensure the data analyzed is indeed relevant to the business.