Modern data quality approach
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
Home
Vanitha
Top 4 Benefits of Modern Data Quality
The goal of a data quality program is to build trust in data. However, trust is an expansive, and often ill-defined term that can include… Read More »Top 4 Benefits of Modern Data Quality
4 pillars of modern data quality
The need for high-quality, trustworthy data in our world will never go away. Treating data quality as a technical problem and not a business problem… Read More »4 pillars of modern data quality
What is Modern Data Quality?
With the growth in data and the adoption of cloud architecture or hybrid with data spread across cloud and on-premise, both producers and consumers of… Read More »What is Modern Data Quality?
What is trustable data? Why do you need it?
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.
Best practices to maintain high data quality
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.
10 steps to data profiling for successful data discovery: Part II
Before embarking on the data profiling exercise, an analyst must prepare by going through a data profiling analysis.
How to build your data quality team
As the adage goes, a workman is only as good as his tools. There is no disputing that, but you can never overlook the power… Read More »How to build your data quality team
Challenges and Best Practices of Data Cleansing
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.
Five Steps to Data Profiling for Successful Discovery
Data profiling focuses on examining and analyzing data, followed by creating a useful summary of that data.