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Foundations of Data Science

Data manipulation, analysis and data management combine with scientific methods, processes, and systems to extract knowledge or insights from large amounts of data Introduction The phrase “data science” is akin to the proverbial elephant and the eight blind men – each one imagining what an “elephant” is by what he feels in the small area to which he has access.

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Integrating Enterprise Information Management with Project Management

Integrating the components of enterprise information management into a project centric organization can be challenging, but it is essential for successfully using data as an asset. Introduction One the challenges with implementing Enterprise Information Management (EIM) is integrating and gaining traction in a project centric organization.  For companies with a more formalized Project Management organization, the organization views corporate work

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Data Drives the Digitization of Insurance

Data generated by The Internet of Things is having a major effect on insurance companies’ approaches to enterprise data management Introduction Even before the use of computers, data was at the heart of the insurance business.  Unlike other enterprises that sell a tangible product, insurers sell a promise. In exchange for your premium dollar today, the insurer promises to pay

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Ensuring Speed, Flexibility and Agility with Self Service Analytics

Introduction Today’s digital world and fast paced business environment demands pervasive, timely analytics. Organizations must deliver speed, agility and ease of use for data access and analytics. In response, business intelligence (BI) and analytics teams are shifting to a more agile, self-service model that enables greater user access to data and the ability to create and perform individualized reports and

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Enterprise Architecture Defined

Samuel B. Holcman An enterprise architecture (EA) is a series of conceptual blueprints that defines the structure and operation of an organization to enable strategic progress. Enterprise Architecture (EA) explicitly describes an organization through a set of independent, non-redundant artifacts, defines how these artifacts relate with each other, and develops a set of prioritized, aligned initiatives and roadmaps to understand

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Concepts and Uses of Open Data

The use of open data is becoming more popular. Data management professionals should develop familiarity with the concept, use, and challenges of open data. Introduction The concept of open data is not new, but its use is becoming more prevalent as the availability of sources, and the validity of those sources, grows. Problems often arise because these sources are commercially

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Improving the ROI of Big Data and Analytics through Leveraging new Sources of Data

Investing in new sources of data can help to unravel complex customer behavior and improve key analytical insights Introduction Big Data and Analytics are all around these days. Most companies already have their first analytical models in production and are thinking about further boosting their performance. Far too often, they focus on the analytical techniques rather than on the key

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The Poor State of Data Quality and a Solution

A CONVERSATION WITH TOM REDMAN : Anne Marie Smith, Ph.D. Data quality has been a continual challenge for almost every organization for many years. In this recap of a conversation with Dr. Thomas C. Redman, he offers a possible simple solution. AMS: Subscribers to Data Management University should study “Only 3% of Companies Data Meet Basic Quality Standards” published September

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Differences Between Text and Big Data

Text and Big Data are not synonymous, regardless of attempts to force them to be considered as similar.  One of the questions that vendors love to ask (and to confuse people with) is combining / mixing Big Data and text.  The confusion becomes apparent when the question “Isn’t text the same thing as Big Data?” arises. The short answer is that

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Is Data Theft Your Biggest Information Governance Nightmare?

Data theft is a serious risk for every organization, regardless of industry or size. Establishing a strong Information Governance framework to defend against this risk is an essential practice. Introduction According to the Washington Post, Insurance Journal and other business sources, a recent study Data Theft by Employees Affects 69% of Businesses of 208 organizations revealed 69 percent “experienced an attempted or realized data

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