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Data Virtualization and Digital Agility

This Articles originally appeared in the September/October 2016 issue of ITProfessional Magazine.
 
"Data lakes” has become the new buzzword for organizations dealing with never-ending and increasingly complex and costly requirements for using all of their data sources to produce value. Whether that value is in analyzing past performance, predicting customer needs, automating processes, or creating new products and services, the building block of any of these value streams is data—in all of its shapes, sizes, speeds, formats, quality, and richness...
 

Earley Information Science Team
Earley Information Science Team
We're passionate about enterprise data and love discussing industry knowledge, best practices, and insights. We look forward to hearing from you! Comment below to join the conversation.

Recent Posts

Designing AI Programs for Success - a 4 Part Series

Recorded - available as on demand webcast AI is plagued by inflated and unrealistic expectations due to a lack of broad understanding of this wide-ranging space by software vendors and customers. Software tools can be extremely powerful, however the services, infrastructure, data quality, architecture, talent and methodologies to fully deploy in the enterprise are frequently lacking. This four-part series by Earley Information Science and Pandata will explore a number of issues that continue to afflict AI projects and reduce the likelihood of success. The sessions will provide actionable steps using proven processes to improve AI program outcomes.

The Missing Ingredient to Digital Transformation: Scaling Knowledge Communities and Processes

The holy grail of digital transformation is the seemingly conflicting goals of high levels of customer service and pressure to reduce costs. “Digital Transformation” has become an all-encompassing term – in a piece in this column about customer data platforms, I asked whether the term has lost its meaning: The phrase “digital transformation” can mean anything and everything — tools, technology, business processes, customer experience, or artificial intelligence, and every buzzword that marketers can come up with. Definitions from analysts and vendors include IT modernization and putting services online; developing new business models; taking a “digital first” approach; and creating new business processes, and customer experiences. The overarching objective of a digital transformation program is to improve end-to-end efficiencies, remove friction from information flows, and create new value streams that differentiate a company’s offerings and strengthen the customer relationship. Having assisted large global enterprises with building the data architecture, supporting processes, and governance for multiple digital transformations, in my experience, there are two broad classes of initiatives that seem to get funding and others that miss the boat in terms of time, attention, and resources.

4 Reasons B2B Manufacturers need Strong Product Data

There are many manufacturers who have started to take the leap forward in the digital space, but there are still a great number who rely solely on their distributors to manage their product data. We are going to look at 4 key reasons why its so important that manufacturers own their product and dedicate the time and resources to build it out.