Four Ways to Ensure Quality Data
Companies have access to more data today than ever before, but if the quality is questionable, so are any inferences from it. As the old
Companies have access to more data today than ever before, but if the quality is questionable, so are any inferences from it. As the old
Precise endeavors must be done to exacting standards in clean environments. Surgeons scrub in, rocket scientists work in clean rooms, and data scientists…well we try
Artificial intelligence and machine learning can generate quality predictions and analysis, but first require organizations be trained on high quality data, starting with the six
AIOps solutions have become critical for businesses looking to improve service reliability. See why effective orchestration, correct implementation and above all, good data are the
Many large enterprises use one form or another of a supply chain application to help manage their supply chains. Supply chain vendors have been touting
Artificial intelligence and machine learning (AI/ML) holds tremendous promise for improved efficiencies, automation, and valuable insights that can drive business value. Machine learning (ML) is
Real artificial intelligence (AI) is all about reality and causality, and how it is reflected in digital mentality and cyberspace or virtuality. There are two
The volume of data that is available to companies today is significantly greater than ever before. The velocity of that data, moreover, continues to increase
Organizations adopt data science with the goal of getting answers to more types of questions, but those answers are not absolute. Business professionals have traditionally
When it comes to information gathering, one constant remains: video is central to the goal of assembling and disseminating intelligence across the globe. Every size
How can you build a data-driven culture and spur digital transformation without thinking through who should be responsible for your data? Let’s do that together.
Data quality is considered as the highest commandment in data management. And it’s with a strong purpose. Only data of high quality is useful data,