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Common Master Data Management (MDM) Pitfalls

Leaders need to trust data within the organization to make sound business decisions. So, many turn to master data management (MDM), a solution to get and keep uniform and accurate data that increases business value. Yet, according to Gartner, 75% of all MDM programs across organizations fail to meet business objectives. Moreover, this trend has worsened since 2015, […]

AI Governance Best Practices

AI governance is meant to promote the responsible use of artificial intelligence for the betterment of humankind. Artificial intelligence has proven itself quite useful in completing a large variety of tasks quickly and efficiently. Unfortunately, it can also be used to support criminal behavior or to create and distribute misinformation. AI governance is an effort […]

Fundamentals of Data Virtualization

Organizations are increasingly employing innovative technology called “data virtualization” (DV) to tackle high volumes of data from varied sources. Data virtualization is widely used in enterprise resource planning (ERP), customer relationship management (CRM), and sales force automation (SFA) systems to collect and aggregate multi-source data. From multi-sourced data acquisition to advanced analytics, this technology seems […]

3 Key Benefits of Pragmatic Data Modeling

In 2024, companies have developed a renewed interest in the benefits of Data Modeling, engaging in pragmatic planning and activities around diagramming requirements. Organizations want to document data architectures to get good Data Quality and overcome challenges.  Notably, the resolution to each data incident has risen significantly by 15 hours between 2022 and 2023. Furthermore, 80% of data executives and business leaders say cultural impediments […]

Data Privacy vs. Data Security

Data privacy refers to a framework of laws, protocols, and controls designed to protect personal data from unauthorized access and use. It encompasses a range of information, including but not limited to names, addresses, financial details, social security numbers, and online activities. Data security refers to the controls, protocols, and industry standards designed to protect digital […]

Creating a Data Quality Framework

An organization can define its Data Quality goals and standards, and the steps needed to accomplish those goals, by creating a Data Quality framework. Creating it includes an assessment of the organization’s current Data Quality. A Data Quality framework can be described as an instruction manual for improving the quality of the data. With a […]