Interview with Ben Gardner of AstraZeneca Image by Gerd Altmann from Pixabay Ben Gardner’s experience working with drug discovery teams goes back two decades, when… Read More »Scaling FAIR data sharing in an R&D culture
Image by 10302144 from Pixabay Eric Baum in his book What Is Thinking? defines understanding as “a compressed representation of the world.” Another word for… Read More »A neurosymbolic AI approach to learning + reasoning
One of the efforts our Dataworthy Collective will be ramping up in 2024 involves standardizing the building of logical knowledge graphs at the level of… Read More »Why FAIR data assets are essential to AI data management
Modern data quality practices leverage advanced technologies, automation, and machine learning to handle diverse data sources, ensure real-time processing, and foster collaboration across stakeholders. They… Read More »Difference between modern and traditional data quality
As companies gather seemingly endless data streams from an increasing number of sources, they start to amass an ecosystem of data storage, would-be end-users, and… Read More »Data observability vs data quality
An organization with 1000 employees, in 2022, has an average of 177 SaaS applications. Most of these applications store data relevant to their needs, However,… Read More »Modern data quality approach
Trustable data can be defined as data that comes from specific and trusted sources and is used according to its intended use. It is delivered in the appropriate format and time frames for specific users.
With the world’s data multiplying in leaps and bounds, every organization is trying to make better business decisions in marketing, product development, and finance using insights from the data they hold. The value of businesses today can be measured by the quality of the data they hold.
Before embarking on the data profiling exercise, an analyst must prepare by going through a data profiling analysis.
One of the biggest challenges that businesses face with their datasets is duplication. Teams encounter thousands of rows in the customer dataset, knowing that their… Read More »The art of removing duplicates from your organizational data
