Overview
What is Datafold?
Datafold, from the company of the same name in San Francisco, is a data observability platform that helps companies prevent data catastrophes. It has the ability to identify, prioritize and investigate data quality issues proactively before they affect production.
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Product Details
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What is Datafold?
Datafold Video
Datafold Integrations
Datafold Technical Details
Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
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Operating Systems | Unspecified |
Mobile Application | No |
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Reviews
Community Insights
- Business Problems Solved
- Pros
- Cons
Datafold solves a range of business problems related to data quality and pipeline management. Users have integrated Datafold with GitHub, resulting in improved data quality and automated data testing, saving time and effort. By automating the detection of data pipeline issues, Datafold ensures data quality and saves valuable time and resources that would otherwise be spent on manual data testing. Data engineers find Datafold particularly useful for automation testing as it streamlines the development and maintenance of data pipelines. Additionally, Datafold helps streamline the consumption of data from multiple sources by providing integrations that connect different data sources in one place, making it easy to observe the data pipeline. The comprehensive suite of end-to-end testing tools provided by Datafold helps teams achieve their business objectives by ensuring data accuracy and removing inconsistent data. Overall, by addressing common data pipeline problems and offering robust testing and monitoring tools, Datafold empowers teams to effectively manage their data and achieve their business goals.
Data Quality Assurance: Users have praised Datafold as the best solution for solving data quality issues and automating data testing. Several reviewers have mentioned that they appreciate the ability to quality check data in their own way with fewer errors compared to manual testing, increasing confidence in the accuracy of their pipelines.
Streamlined Workflow: The workflow in Datafold is highly regarded by users, as it streamlines the traditional laborious process of data transfers. Many team members have been impressed by how it facilitates SQL code reviews and helps identify hidden changes in data, making their lives easier.
User-Friendly Interface: The user-friendly and intuitive user interface of Datafold has received positive feedback from multiple users. They find it easy to navigate and use, even without extensive programming experience. Real-time updates provided by the platform make it simple for data teams to track data lineage and debug issues efficiently.
Steep Learning Curve: Some users have found Datafold to have a steep learning curve, making it challenging for effective adoption and usage. Limited Integration Options: Several reviewers have mentioned that Datafold has limited integration options, which can restrict its compatibility with other software tools. Lack of Comprehensive Support for NoSQL Data: Users have reported that Datafold's support for handling NoSQL data is not comprehensive, requiring teams working with non-SQL data to seek alternative tools or workarounds.