We are at an inflection point in the financial services industry. The evolving and overwhelming demands of regulatory compliance have forced organizations to acknowledge the need for data governance...
Picking up where we left off in my previous post, companies have been looking to data lakes in the past few years to relieve them of the expensive and time-consuming burden of creating data...
The times they are a-changing – and changing quickly – in enterprise data management.
Recently, Michele Goetz, Principal Analyst at Forrester Research, and Ben Szekely, VP of Solutions here at Cambridge Semantics, sat down to discuss how organizations can give up the keys to their...
Exploratory analytics represents the evolution—and perhaps culmination—of conventional analytics and business intelligence options. It’s a combination of real-time data discovery and ad-hoc,...
With no inherent means of adhering to governance and security protocols, data lakes are akin to the Wild West in that they are devoid of order and consistency. Each user manipulates his or her own...
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...
Many data lake projects achieve their IT objective: cheap storage of all enterprise data in raw form, but fail in their business objective to deliver value from this data. Why? Because making the...
