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Generative AI vs. Traditional AI

Traditional AI, also known as “classical AI,” is known for being rule-based and dependent on stringent programming for its intended output. These techniques revolve around the manipulation of symbols and logical reasoning to perform tasks.  Key methodologies include rule-based systems, where knowledge is encoded in the form of “if-then” statements, enabling machines to make decisions […]

Choosing a Data Quality Tool: What, Why, How

Data-driven organizations are in a race to collect the information that modern analytics techniques rely on to generate insights and guide business decisions. The ever-growing flow of data into business systems challenges companies to devise new techniques for ensuring the quality of the data as its quantity skyrockets. Data quality tool vendors are rising to […]

A Brief History of Data Ethics

In this digital age, where data is an increasingly integral asset for every organization, the ethical implications surrounding data collection, storage, and usage have become prominent. The evolution and history of data ethics is a complex journey that connects technological advancements with societal values and legal frameworks. Understanding this evolution requires examining key historical milestones and the […]

Six Common Digital Transformation Challenges

During digital transformation, one of the most formidable challenges organizations face is resistance to change and the complexities of effective change management. Human nature often gravitates toward familiarity and routine, making any deviation a source of discomfort. This psychological inertia can stem from various factors including fear of job loss, perceived inadequacy in new skill […]

Improving Data Quality with Data Stewardship

To get value from data, data stewards must understand and apply business requirements. When business ambiguity arises about how to best serve data stakeholders, data stewards need to know how to find out this information and with whom to speak. By doing so, stewards can align fit-for-purpose data with business needs and improve data quality. Data stewards understand […]