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Data Quality

Say Goodbye to Data Quality with ELT

ELT is a three-step process that first extracts raw, structured, and unstructured data from source databases, applications, data stores, and other repositories. It then loads that data into a data lake and transforms it as needed by analysts. Since it doesn't move the data to an intermediate staging area or transform it before loading, the extraction process is speedy. You don’t need to pick and choose what data loads into the data lake or wait for it to be processed.

5 Ways to Improve Data Quality with Teradata

In 1979, Teradata began life as a collaboration between Caltech and Citibank. Today, this enterprise software group is all about redefining business intelligence tools and data management. The Teradata Database is now the Teradata Vantage Advanced SQL Engine, The name not only highlights the evolution of the company but also recognizes that tech consumers now expect more from their tools.

What Is a Data Stack?

These days, there are two kinds of businesses: data-driven organizations; and companies that are about to go bust. And often, the only difference is the data stack. Data quality is an existential issue—to survive, you need a fast, reliable flow of information. The data stack is the entire collection of technologies that make this possible. Let's take a look at how any company can assemble a data stack that's ready for the future.

The road to data quality: Getting to customer 360 faster with Machine Learning

Read Part 1 here > Data analytics is a complex process that demands time and effort from data scientists. From cleaning and prepping data to performing data analysis, data scientists go through an extensive procedure to uncover hidden patterns, identify trends, and find correlations in data to make informed business decisions. The task of integrating, cleaning, and organizing data assets often take up the bulk of the data scientist’s time.

What is data quality, why does it matter, and how can you improve it?

We’ve all heard the war stories born out of wrong data: These stories don’t just make you and your company look like fools, they also cause great economic damages. And the more your enterprise relies on data, the greater the potential for harm. Here, we take a look at what data quality is and how the entire data quality management process can be improved.

Talend Data Inventory - Turning Data Quality into a Team Sport

Talend’s Data Inventory application enables your organization to easily collaborate across multiple business and technology functions and strengthen data integrity by centrally organizing datasets, consistently applying standardization rules and proactively correcting data errors. In this video, you will understand how Data Inventory, combined with Talend Pipeline Designer and Talend Data Preparation, extends your collaboration capabilities and enables self-service across your organization.

Our reflections on the 2020 Gartner Magic Quadrant for Data Quality Solutions

“Every organization — no matter how big or how small — needs data quality,” says Gartner in its newly published Magic Quadrant for Data Quality Solutions. However, with more and more data coming from more and more sources, it’s increasingly harder for data professionals to transform the growing data chaos into trusted and valuable data assets.