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.
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Data Lifecycle Management
Data Lifecycle Management focuses on data governance, data cleansing and quality, and data stewardship. The rubric applies to articles that focus primarily on the high-level preparation, flow, and use of data through an organization, rather than with one single facet such as storage or analysis.
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.
How to Automate Data Cleaning, in a Nutshell
Data scientists spend 80% of their time on data cleaning and exploratory analysis. What if you could automate most of this? What if data scientists… Read More »How to Automate Data Cleaning, in a Nutshell
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.
The art of removing duplicates from your organizational data
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 Standardization: Define, Test, and Transform
What is data transformation? Simply put, data standardization is the process of transforming data values from an incorrect format to a correct one.
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.
Reengineer Business Decisions Granularly with Automated Data Collection
Businesses, whether big or small, know that understanding data is essential to making informed decisions that impact the organization’s bottom line.
DSC Webinar Series – Its Time to Turn Data Chaos into Order.mp4
The amount of customer data available to brands has absolutely exploded in the past decade, giving brands an opportunity to create personalized experiences. But with… Read More »DSC Webinar Series – Its Time to Turn Data Chaos into Order.mp4