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Software used to ensure accuracy and consistency of information. - Analyze data and identify incorrect values and formatting - Manually and automatically correct inaccuracies - Preserve data integrity using preventive measures
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An intelligent self- service data quality and enrichment platform.
To win in the digital economy, your data must be decision grade and of the highest quality to power your critical operations. Tricentis Data Integrity helps ensure that your data arrives intact and fit for purpose as it travels between your source systems and data warehouse to your reports, dashboards, and business processes.
Data observability is your company’s ability to fully understand the health of the data in its systems. Healthy—high-quality, reliable, and trusted—data starts with the ability to monitor and understand the five pillars of data observability at each stage of the pipeline: Freshness, Distribution, Volume, Schema, and Lineage. Monte Carlo's data observability platform connects to your existing data stack quickly and seamlessly to monitor for freshness, distribution, volume, and schema changes continuously, and immediately notifies stakeholders once data incidents are detected. With end-to-end visibility, our data observability platform generates insights that help data teams change and modify tables and schema responsibly, manage storage and compute costs, and make smarter data architecture decisions.
Soda’s mission is to empower and incentivize everyone in your organization to share and use reliable, high-quality data. Soda delivers end-to-end data quality management to detect, analyze, and prevent data issues. It's easy to integrate the Soda framework into your data stack by leveraging our extensive Python and REST APIs, to add data quality tests to your pipelines to avoid merging bad-quality data into production and to prevent downstream issues. For any organization that is building a domain-oriented, decentralized data platform to drive data cultural change, Soda bridges the gap between data producers and data consumers, whilst increasing accountability and ownership to ensure that the right people are involved at the right time. Over 100 organizations including American Family Insurance, CarTrawler, Group 1001, HelloFresh, Lululemon, and Panasonic, use Soda to guarantee the accuracy, validity, and consistency of data at every stage of its lifecycle.
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Anomalo helps enterprises build confidence in the data they use to make decisions and build products. Enterprises can simply connect Anomalo’s complete data quality platform to their data warehouse and begin monitoring their data in less than 5 minutes, all with minimal configuration and without a single line of code. Then, they can automatically detect and understand the root-cause of data issues, before anyone else.
Data observability is your company’s ability to fully understand the health of the data in its systems. Healthy—high-quality, reliable, and trusted—data starts with the ability to monitor and understand the five pillars of data observability at each stage of the pipeline: Freshness, Distribution, Volume, Schema, and Lineage. Monte Carlo's data observability platform connects to your existing data stack quickly and seamlessly to monitor for freshness, distribution, volume, and schema changes continuously, and immediately notifies stakeholders once data incidents are detected. With end-to-end visibility, our data observability platform generates insights that help data teams change and modify tables and schema responsibly, manage storage and compute costs, and make smarter data architecture decisions.
SuperAnnotate offers advanced data curation & management solutions to create healthy datasets for top-performing models. - Curate the right dataset for top-performing models Find relevant data easily and curate healthy datasets for your models. - Advanced features to guarantee data quality Monitor the quality of your data and do a faster, more thorough quality check all in one place. - Powerful data insights Get detailed information on the performance of your annotation team as well as your dataset's health. Monitor annotation trends, analyze model performance, track annotation time, and more. - More tools to boost data management & curation Similarity search: Find similar items in your dataset and assign them to annotators to compare their work Random and smart sampling: Detect the most diverse items in your dataset to make sure not to annotate duplicates Generate data: Use our data generation tools to create valuable data based on your text prompts for your specific use cases.
The iData toolkit offers an end-to-end software solution for every stage in the data certainty process. So whether you require a specific tool to support ETL, or QA for a new application, we’ve got you covered. The toolkit is based around three primary solutions: data quality, migration and transformation and test data management. IDS have engineered iData to assure 100% of the data, through 100% of the journey, 100% of the time. This gives clients and partners 100% data certainty.