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Self-Service Analytics Use Cases

Self-service analytics offers dynamic reports to business users, who can analyze the data by sophisticated, in-built functions. This kind of user empowerment reduces reliance on IT staff. Moreover, self-service business intelligence (BI) capability may additionally equip users with external data access and built-in features to instantly generate finished reports. To use a complete range of […]

Data Architect vs. Data Modeler vs. Data Engineer

Michael Bowers, author and Chief Data Architect at FairCom Corporation, initially set out to research three careers in his presentation titled Data Architect vs. Data Modeler vs. Data Engineer  for the DATAVERSITY® Data Architecture Online 2019 Conference. The process brought him to a wealth of information he would have appreciated much earlier in his career, […]

Fundamentals of Cognitive Analytics

The journey of data analytics began with simple descriptive (review of past events) and diagnostic (analysis of past events) exercises and moved to the more sophisticated predictive and prescriptive genres,where advanced data models have enabled accurate future forecasts and actionable intelligence. And now cognitive computing has further strengthened the actionable predictive power of the machines […]

A Brief History of Data Quality

The term “Data Quality” focuses primarily on the level of accuracy possessed by the data, but also includes other qualities such as accessibility and usefulness. Some data isn’t accurate at all, which, in turn, promotes bad decision-making. Some organizations promote fact checking and Data Governance, and, as a consequence, make decisions that give them an […]

The Collective Data Literacy Gap

Every graph, data set, and chart has a story behind it. Knowing how to make sense of that narrative across an organization requires data literacy. Increasing the data literacy of smaller teams can be complicated, but equiping an entire organization is an even bigger task. So many teams bring in so many different skill sets […]

Data Architecture and Data Science: What is the Intersection?

Data Science, in practice, should ultimately combine the best practices of information technology, analytics, and business. On the other hand, Data Architecture enables data scientists to analyze and share data throughout the enterprise for strategic decision-making. Thus, without a sound Data Architecture in place, data scientists will remain severely handicapped in their abilities to develop […]

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