Summarizing the lessons she learned from her tenure in a speech earlier this month, Mary Jo White, outgoing chair of the U.S. Securities and Exchange Commission (SEC), made a convincing case that the use of data analytics has greatly contributed to a dramatic rise in successful SEC investigations of insider trading and other securities fraud.
A data mart is a simple form of a data warehouse that is focused on a single subject or functional area. It draws data from a limited number of sources such as sales, finance or marketing, and is often created and controlled by a single department within an organization. Like data warehouses, data marts implement the characteristics of governed, non-volatile, and integrated data, although the static model known to be the “truth” at the time is of a smaller scope than the enterprise scope used in a data warehouse.
The complexity of data management and advanced analytics is daunting to many organizations, but a new emerging class of software enables companies to spend less time managing their data and more time acting on the insights they provide.
With all eyes on the election at the moment, I thought I’d take a moment to discuss a topic that concerns all citizens – government transparency.
At Strata+Hadoop World 2016, the concept on everyone's mind was the Data Lake. Fortunately, Marty Loughlin, our Vice President of Financial Services, was there to discuss how Smart Data Lakes are employing semantic technology to revolutionize Enterprise data analytics in ways that traditional Data Lakes can't. Here are the slides from his presentation.
Last month, the Cambridge Semantics team set off to New York City for Strata + Hadoop World 2016, or what Wired likes to call, “the lollapalooza of big data conferences.”
Last month, Cambridge Semantics held its inaugural Life Sciences Smart Data Discovery and Analytics Forum in Boston. At this forum, leaders in Life Sciences and Big Data met to discuss the application of smart data technology to research and development, clinical trial and healthcare data to gain more actionable insights and shorten the overall product lifecycle.
A picture is worth a thousand words they say, and this remains true for data discovery and analytics. For centuries, graphs and maps have been used to help us simplify, understand and convey large amounts of data in a universal manner. And with the evolution of technology, we can now visualize increasingly complex information at lightning-fast speeds.
As organizations recognize the positive impact that big data has on a company’s performance and innovation, the position of Chief Data Officer (CDO) continues to grow in prominence across numerous industries.
Conventional data analytics utilizes dashboards, visualizations, search, and other tools to determine appropriate data for integrated, targeted use cases. Smart data analytics techniques, on the other hand, leverage linked data graphs, comprehensive data models, and a semantic standards-based approach to publish results to those same popular tools.