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Maturing Business Intelligence with Data Governance

Data Governance (DG) ensures that enterprise data, the most valuable business asset, is preserved and used in the most efficient and safest manner. That said, Data Governance puts immense demands on organizational policies, processes, technologies, and lastly on accountable staff to develop an executable framework, from its core architecture to implementation stages. Enterprise Data Governance […]

The Future of Data Architecture

Anthony J. Algmin believes Data Architecture is moving from a time of chaos and tangles into something more clean and organized. Speaking at the DATAVERSITY® Data Architecture Online Conference, Algmin looked at past predictions, current hot topics, and predictions for the future. He is the Founder and CEO of Algmin Data Leadership. A Quick Look […]

Graph Databases: An Overview

The concept of graph databases traces back to Leonhard Euler. Euler was an 18th century Swiss mathematician who made several important discoveries in mathematics, such as infinitesimal calculus. In solving the “Seven Bridges of Königsberg” problem in 1736, Euler laid the foundations for graph theory. (He also got a fun shout-out in Hidden Figures when […]

How to Become a Data Analyst

Data analysts translate raw data into useful insights, and they are also responsible for gathering the data, organizing and analyzing it, and then presenting their findings. Data analysts are in high demand, and there aren’t enough data analysts to fill all the positions. People with the right skills can fill these positions. A degree is […]

Data Science Best Practices

When done right, Data Science delivers a lot of measurable values like improved products and services, enhanced customer experiences, sales growth, new business developments channels, and overall business efficiency. However, according to most reliable industry publications, most Data Science projects fail because the Data Science best practices are not followed. Why Do Businesses Need Data […]

Advances in Data Quality Management

Data Quality Management (DQM) is always advancing, not necessarily in terms of technological leaps, but in terms of being used more as a result of shifting business patterns. DQM is being used more and more, as organizations shift to a digital format. Other reasons for the increased use of DQM range from the lowering of […]