Automated Data Quality Checks - Learn Data Science with Travis

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Automated data quality checks are essential processes that ensure the accuracy, consistency, and reliability of data within various systems. By leveraging automated tools and scripts, organizations can efficiently identify and rectify data errors, reducing the risk of misleading insights and costly decisions. These checks can be integrated into data pipelines, such as ETL (Extract, Transform, Load) processes, to validate data as it flows through the system. Automation not only saves time by eliminating manual checks but also enhances trust in data-driven analytics, allowing teams to focus on deriving valuable insights rather than troubleshooting data issues.

Automated Detection of Data Quality Issues

Towards Data Science

This article is the second in a series about cleaning data using Large Language Models (LLMs), with a focus on identifying errors in tabular data sets. The sketch outlines the methodology we’ll explor...

Transforming Data Quality: Automating SQL Testing for Faster, Smarter Analytics

Towards Data Science

How to test the quality of SQL and resultant dataset against the business question to increase trust with customers Photo by Caspar Camille Rubin on Unsplash When it comes to software development, th...

Automating Data Validation in Your Pipelines: Python Scripts for Error-Free ETL

Python in Plain English

Ensure Data Quality with Automated Validation Checks in Your ETL Process Photo by Anastassia Anufrieva on Unsplash Data quality is the cornerstone of reliable analytics. In today’s data-driven world,...

Layers of Data Quality

Towards Data Science

With the recent surge of interest in generative AI and LLMs, data quality has received a resurgence of interest. Not that the space needed much help: companies like Monte Carlo , Soda , Bigeye , Siffl...

Your Data Quality Checks Are Worth Less (Than You Think)

Towards Data Science

Over the last several years, data quality and observability have become hot topics. There is a huge array of solutions in the space (in no particular order, and certainly not exhaustive): dbt tests SQ...

Don’t Fix Bad Data, Do This Instead

Towards Data Science

Story From The Trenches A few years ago, our data platform team aimed to pinpoint the primary concerns of our data users. We conducted a survey among individuals interacting with our data platform, an...

Stop Overcomplicating Data Quality

Towards Data Science

Three Zero-Cost Solutions That Take Hours, Not Months A ‘data quality’ certified pipeline. Source: unsplash.com In my career, data quality initiatives have usually meant big changes. From governance ...

Data Quality Auditing: A Comprehensive Guide

Towards Data Science

Data quality auditing is an indispensable skill in our rapidly evolving, AI-empowered world. Just like crude oil needs refining, data also requires cleaning and processing to be useful. The old adage…...

Stop Firefighting Data Quality Issues.

Towards Data Science

Data quality assessment is the first step toward understanding and improving your organization's ability to sustain high-quality business processes.

Should I Check the Quality of My Data Every Day?

Towards Data Science

Improving Data Quality Is a Balancing Act between Time and Cost Continue reading on Towards Data Science

What is Data Quality?

Towards Data Science

Data Quality defines how data sets can be trusted, understood and utilized effectively for their intended purpose. In Supply Chain Management, data plays a crucial role in detecting issues and making ...

Apply Data Quality Checks at These 5 Points in Your Data Journey

Towards Data Science

Improve Quality of Your Data by Applying These Checks in Your Journey Continue reading on Towards Data Science