TDAN.com » Data Quality
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Get a thorough Data Quality education through TDAN's Business Intelligence articles, news, and blogs. Explore this space for articles that delve into the art and science of managing, correcting and enhancing Data Quality. The Data Administration Newsletter (TDAN.com) is an internet-based publication focused on sharing data management approaches, best practices, solutions, and technologies..
TDAN.com » Data Quality
1w ago
If you look at Google Trends, you’ll see that the explosion of searches for generative AI (GenAI) and large language models correlates with the introduction of ChatGPT back in November 2022. GenAI has brought hope and promise for those who have the creativity and innovation to dream big, and many have formulated impressive and pioneering ..read more
TDAN.com » Data Quality
1w ago
Well, of course, metadata is data. Our standard definition explicitly says that metadata is data describing other data. So why would I even ask this question in the article title? The reason I ask it is because we seem to think about and manage metadata as somehow different than “normal data” such as business operations ..read more
TDAN.com » Data Quality
2w ago
I call it a “data crime” when someone is abusing or misusing data. When we understand these stories and their implications, it can help us learn from mistakes and prevent future data crimes. The stories can also be helpful if you have to explain the importance of data management to someone. The Story After a series ..read more
TDAN.com » Data Quality
1M ago
Acquiring an existing business can be an exceptional way to make your entrepreneurial dreams come to life — or even diversify your investment portfolio. But, unless you do your research well, you’re opening yourself up to a lot of unnecessary risk. The process of due diligence involves the appraisal and assessment of a potential investment ..read more
TDAN.com » Data Quality
1M ago
In the realm of big data, ensuring the reliability and accuracy of data is crucial for making well-informed decisions and actionable insights. Data cleansing, the process of detecting and correcting errors and inconsistencies in datasets, is critical to maintaining data quality. However, the scale and complexity of big data present unique challenges for data cleansing ..read more
TDAN.com » Data Quality
2M ago
Data quality is measured across dimensions, but why? Data quality metrics exist to support the business. The value of a data quality program resides in the ability to take action to improve data to make it more correct and therefore more valuable. The shorter the amount of time between the discovery of the data quality ..read more
TDAN.com » Data Quality
2M ago
Many Data Governance or Data Quality programs focus on “critical data elements,” but what are they and what are some key features to document for them? A critical data element is any data element in your organization that has a high impact on your organization’s ability to execute its business strategy. An example is Customer Email ..read more
TDAN.com » Data Quality
3M ago
By now, it is clear to everyone that AI, especially generative AI, is the only topic you’re allowed to write about. It seems to have impacted every area of information technology, so, I will try my best to do my part. However, when it comes to data curation and data quality management, there seems to ..read more
TDAN.com » Data Quality
3M ago
Due diligence is the complex process of assessing a potential investment and ensuring it is a sound one. It involves the gathering, classifying, and analyzing of large volumes of data. Given its very nature, it’s the perfect field for data analytics, which can speed processes up and assess the quality and reliability of data. Due ..read more
TDAN.com » Data Quality
4M ago
Eric Siegel’s “The AI Playbook” serves as a crucial guide, offering important insights for data professionals and their internal customers on effectively leveraging AI within business operations. The book, which comes out on February 6th, and its insights are captured in six statements: — Determine the value— Establish a prediction goal— Establish evaluation metrics— Prepare ..read more