
5 Reasons Data Quality Initiatives Fail
As more and more enterprises recognize the value of data analytics and data-driven decisions, the challenges associated with poor data quality have been brought to the forefront. As business leaders...
As more and more enterprises recognize the value of data analytics and data-driven decisions, the challenges associated with poor data quality have been brought to the forefront. As business leaders...
Executives at large enterprises have understood the value of data and data quality for years, but that awareness has been pervading an ever-broader spectrum of organizations. As the volume and...
The goal of data democratization is to enable free flow of information that powers business agility – anybody can use data at any time to make decisions without barriers to data access or...
Large organizations are faced with a rapidly growing volume of data. To make matters more challenging, the velocity of that data has also increased dramatically. Businesses that can master data...
As enterprises benefit from the rich array of business applications available today, they also struggle with an increasingly difficult problem. With so many different applications and data sources,...
As we begin the third decade of the 21st century, data science is entering a golden age. Artificial intelligence and machine learning have matured, and cloud technologies are providing the robust...
The number of connected devices has expanded rapidly in recent years, as mobile phones, telematics devices, IoT sensors, and more have gained widespread adoption. At the same time, big data analytics...
Business leaders have long understood the vital importance of knowing their customers’ preferences and aspirations and building lasting relationships with them. Responsiveness to customer needs...
Precisely recently released version 2020.1 of the Spectrum-branded data quality products that enhance interoperability, user experience, and scalability. Together, these products lay the foundation...