Data Standardization: Define, Test, and Transform

While organizations shift towards establishing a data culture across the enterprise, many are still struggling to get their data right. Pulling data from disparate sources and getting varying formats and representations of what is supposed to be the same information – causes serious roadblocks in your data journey. Teams experience delays and mistakes while carrying out their routine operations or extracting insights from datasets. Such problems force businesses to introduce a data standardization mechanism –

Why Data Cleansing Is Critical and How You Can Implement Data Cleanliness Processes and Solutions

Poor data quality is a rising concern for many business leaders as they fail to meet their targeted goals. The team of data analysts – that is supposed to produce reliable data insights – spend 80% of their time cleaning and preparing data, and only 20% of the time is left to do the actual analysis. This has a huge impact on the team’s productivity as they have to manually validate the data quality of