Conventional data discovery utilizes dashboards, visualizations, search, and other tools to determine appropriate data for integrated, targeted use cases. Smart data discovery techniques, on the...
Data lakes are quickly becoming a hot topic as enterprises determine how best to organize and access the large volume of data they have been generating. Data Lakes are attractive for several...
Regardless of the ROI of any data-centered solution, upper level management will not support it unless it adheres to governance and security conventions. By definition, data governance formalizes...
The Need Unstructured data is all around us: in news stories, web pages, journal articles, social media posts, patents, research reports, presentations, and a variety of other sources. These items...
Data lakes are no longer anomalies. Consolidating all of an organization’s data—unstructured, semi-structured, and structured—into a single repository for integration, access, and analytics purposes...
Recent developments in big data technologies have significantly impacted the prowess of contemporary analytics; the most profound of these involves the deployment of semantically enhanced semantic...
Legacy applications that have exceeded their useful life can be expensive to maintain. They often require specialized skills and old versions of software and hardware to support. But, they can also...
Mike Atkin of the EDM Council speaks eloquently about the "perfect storm" for data in Financial Services. Two converging forces, regulatory reporting requirements and the need for customer insight,...
Data integration projects can be time consuming, expensive and difficult to manage. Traditional data integration methods require point to point mapping of source and target systems. This effort...
Driving business value from your data often requires integration across many sources. These integration projects can be time consuming, expensive and difficult to manage. Any short cuts can...
