Bill Inmon, the “Father of Data Warehousing,” defines a Data Warehouse (DW) as, “a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process.” In his white paper, Modern Data Architecture, Inmon adds that the Data Warehouse represents “conventional wisdom” and is now a standard part of the corporate infrastructure. […]
The Enterprise Data Catalog: Use Cases for Having a Time Machine
Speaking at the DATAVERSITY® Enterprise Data World 2016 Conference, Jeremy Posner, Senior Director of Data Management and Strategy at Synechron, offered the Enterprise Data Catalog as a useful tool in three use-cases: eDiscovery, Records Management, and Data Sourcing Integration Points. Posner says that the temporal database of an Enterprise Data Catalog can serve as a […]
Microservices for Big Data: Flipping the Paradigm
“Microservices are essentially applications that are broken down into small pieces. Using microservices, businesses can prevent large-scale failure by isolating problems, and save on computing resources,” commented Jack Norris, Senior Vice President of Data and Applications at MapR. Microservices are now altering a major Data Management paradigm of the last 30 years. In a recent […]
Big Data and Smart Data: Big Drivers for Smart Decision Making
“Data is not smart in its own right; rather, it’s only smart if it drives smart decisions,” says James Kobielus, IBM’s Big Data evangelist, delivering the keynote address at the DATAVERSITY® Smart Data Online 2016 Conference. He considers his core focus, Big Data, as “a subset of the broader concept of Smart Data.” Kobielus says […]
Artificial Intelligence and the Future: Should We Worry About Our Data Jobs?
Speaking at the DATAVERSITY® Smart Data Online 2016 Conference, Adrian Bowles, industry analyst, recovering academic, and founder of STORM Insights, and Steve Ardire, Merchant of Light, both talked about the future of Artificial Intelligence (AI). They addressed the question: “Will robots take my job?” The short answer could be summarized as: “Maybe.” Lower level jobs […]
Data Governance Success: How to Build a 360º Perspective
Jodi Morton is Vice President of Single Family Data Governance and Management at Freddie Mac, but “Data Governance Change Agent” might be a more accurate title. Citing from an outside auditor familiar with the company, Morton’s new Data Governance program “got more done in 18 months than in the previous ten years.” Morton spoke at […]
Data Lakes 101: An Overview
A Data Lake is a pool of unstructured and structured data, stored as-is, without a specific purpose in mind, that can be “built on multiple technologies such as Hadoop, NoSQL, Amazon Simple Storage Service, a relational database, or various combinations thereof,” according to a white paper called What is a Data Lake and Why Has […]
The Future of Analytics: Collaboration, Deep Learning, and Telling the Story
Dr. Athanasios (Thanos) Gentimis, Assistant Professor of Math and Analytics at Florida Polytechnic University sees the future of analytics as a team effort, where subject matter experts (SMEs) collaborate in teams with Data Scientists and each team member plays to his or her strengths. He also sees a reliance on Deep Learning for creation of […]
The Changing Data Governance Landscape
An industry pro since 1979, Ian Rowlands assumed that by now Data Governance processes would be done in fairly standardized, complete ways. Instead, he has discovered that while processes are defined and understood, he says they are “more honored in the breach than the observance.” He spoke at the DATAVERSITY® Enterprise Data World 2015 Conference […]
Data Monetization: An Unparalleled Opportunity for Relevance & Value
The monetization of data to influence customer purchases entails granular personalization, said Steve Rubinow, Ph.D., the Chief Technical Officer at Catalina Media Lab, while speaking at the DATAVERSITY® CDOVision 2015 Conference. Mr. Rubinow says that the personalization of data provides an incomparable opportunity that evolves shopper by shopper, device by device, year after year. This […]