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Upcoming Webinars

Jun 27 DAS Webinar: Enterprise Architecture vs. Data Architecture

DATE: June 27, 2019 TIME: 2 PM Eastern / 11 AM Pacific PRICE: Free to all attendees This webinar is sponsored by: About the Webinar Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key inter-relationships between data, process, applications, and more. By abstracting these assets in…

Jul 9 DataEd Webinar: Data Modeling is Fundamental

DATE: July 9, 2019 TIME: 2 PM Eastern / 11 AM Pacific PRICE: Free to all attendees About the Webinar Because every organization produces and propagates data as part of their day-to-day operations, data trends are becoming more and more important in the mainstream business world’s consciousness. For many organizations…

Latest Blogs by Industry Experts

Is It Time to Replace OCR with AI?

Click to learn more about author Jasmine Morgan. Document processing is a necessity, yet it consumes so much time that every large organization is striving to find ways to automate it. However, any solution to be feasible needs to be as accurate as possible, especially in the case of financial documents. Old-school OCR Until AI became an option, simple optical character recognition (OCR) could not operate properly unless strict rules and…

Rearchitecting Legacy Systems for a Cloudy World

Click to learn more about author Melanie Achard. As organizations become increasingly comfortable with cloud native and DevOps technologies, they have begun using the cloud for newer systems—but moving legacy systems currently on-premises to the cloud still makes them uneasy.  Over the last two years, the “lift and shift” approach—the idea of taking legacy systems and solutions and moving them to the cloud as-is—has been widely discussed throughout the technology…

Going for Golden Copy: Tips for Improving Your Master Data Management

Click to learn more about author Richard Mohrmann. Um, yes, we are still talking about reference data. While it certainly seems like a topic that should have been resolved long ago, here we are still talking about why reference data seems like such a difficult nut to crack. There are reasons. At the highest level, organizations usually break data down into two categories: reference data and transaction data. Reference data…

Case Studies

What is...?

What is Data Curation?

Data Curation, as defined by The University of Illinois’ Graduate School of Library and…

What is Ontology?

Ontology is often considered a subset of taxonomy. An ontology: Is a domain; contains…

What is Taxonomy?

Taxonomy represents the formal structure of classes or types of objects within a domain.…

Most Recent Articles

ETL vs. Data Preparation

Extract, Transform, and Load (ETL) technologies, managed exclusively by IT, have until recently been the primary tool used to combine data from multiple sources and thus provide the ability to drive important business decision making for organizations. But, with the advent of self-service data preparation, business users and subject matter experts (SMEs) can find those insights on their own. “In some organizations, each data engineer/IT resource is expected to support…

Impact of Data Quality on Big Data Management

As the available industry literature suggests, Data Quality (DQ) is seriously hindering the success of many Big Data projects. However, it is apparent that without an organized movement in favor of Data Quality for Big Data, nothing will actually happen to change the current scenario. In an interview with the CEO of Informatica, Anil Chakravarthy, reveals how the lack of DQ can inhibit innovation in information technology. The two major…

IDERA Webinar: Lean Data Modeling for any Methodology

To view just the slides from this presentation, click HERE>> Original Air Date: June 18, 2019 This Webinar Sponsored by: About the Webinar With changes in software development methodologies, the role of the data modeler has changed significantly. In many organizations, data modelers now find themselves on the outside looking in, relegated to documentation “after the fact” rather than active participation in database design where the true value is added.…

The Third Generation of Graph Databases

The graph database, very simply, is a database that recognizes the “relationships” between data to be as important as the data itself. A graph database is designed to hold data while not limiting it to a pre-established model. The data in such a database shows how each individual entity is connected with or related to others. A graph database “natively” embraces relationships while other databases compute relationships at the time…

Deep Learning Demystified

The “deep” in deep learning refers to the number of hidden layers involved in the design. Deep learning is a way of training artificial intelligence (AI) to recognize specific data, such as speech or faces, and to make predictions based on previous experiences. Unlike machine learning, which organizes and sends data through predefined algorithms, deep learning develops and uses basic algorithms to screen the data, and then trains the AI…

Data Governance and Data Architecture: There is No Silver Bullet

In terms of a market perspective, Data Governance has increased in visibility partly because of the increase in security breaches, data security issues, and compliance requirements for various industry regulations. To secure and manage data properly, it helps to manage it at a higher level and know which of your data is sensitive in the first place. Having the foundation of a solid Data Architecture is fundamental, because without it,…

Latest Industry News

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