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
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
Data accuracy is the biggest challenge many businesses encounter in their quest to cleanse data. Having accurate data is the foundation of the usefulness of data in all its stages of use.
Data profiling focuses on examining and analyzing data, followed by creating a useful summary of that data.
According to Forbes, data scientists spend about 80% of their time on data collection, cleansing, and preparation, while only 20% of it is left for… Read More »Data cleansing for reliable analytics and business intelligence