If you're considering using Snowflake for your big data needs, there are several things you should know. Snowflake failures are usually caused by underlying data changes. However, the Data Engineering Podcast has a different take on data monitoring and quality. Listen to this podcast to learn more about Snowflake's data quality and monitoring capabilities. Listed below are some tips that can help you ensure your data is always up to par.
Talend Data Fabric
Talend has debuted the Talend Data Fabric, a new cloud-based platform for ensuring the integrity of information assets. It goes beyond core data integration, data quality, and data health management. Talend's latest release, Fall '21, introduces an unlimited-price Stitch ETL tool as well as native trust score capabilities for Snowflake data. Users can also now share Data APIs to perform data quality checks from anywhere.
Talend Data Fabric combines data integration, governance, and security into a single platform that provides a complete solution for analyzing, transforming, and integrating data. Built-in functionality enables data quality and security across all stages of the data lifecycle, from initial import to the final deployment. It also provides tools for data lineage, traceability, and self-service data management. Regardless of your data integration needs, Talend is designed to deliver the insights you need at breakneck speeds.
Validatar
The success of validating snowflake data has been achieved by organizations that use Validatar Cloud. With its multi-tenant architecture, Validatar Cloud automates data quality in Snowflake. With this cloud-based service, data quality teams can get started automating data quality in Snowflake right away. In addition, Validatar Cloud can nurture a culture of data quality and facilitate data governance.
While Snowflake has impressive scalability, it can hamper data quality if it's not properly validated. Validator tools allow users to visually define quality rules and gain insights into where they fail. Maintaining the quality of your data pipeline with validated data can reduce complexity and mitigate costs. Here are three reasons why validators are essential to your data quality. Let's see how they work. And how do they measure up to the competition.
Experian Aperture Data Studio
Combining global curated data with self-service data quality, Experian Aperture's Aperture ADS combines the power of big-data management with the convenience of an everyday web application. This data management solution empowers modern data practitioners to gain insights from their vast volumes of data. Available as a hosted solution or as a physical server, ADS ingests and enriches data sets from multiple sources. It should be a key part of any data management strategy.
Experian's Snowflake connection has been optimized so that large volumes of data can flow between the two systems. It can transform data within the Experian platform before being transferred into Snowflake for analytics. In addition to ensuring a seamless data migration, ADS will also standardize issues relating to data quality, making it easier for users to detect them and resolve them before they impact the data. As a result, businesses will be able to fully leverage Snowflake data.
Global IDs Data Quality Suite
To ensure the highest possible level of data quality, Global IDs' comprehensive data-quality capabilities go beyond profiling. Global IDs provides data quality controls, defined by business users and automatically generated for critical data elements. These controls act like rules and continually monitor linked data elements to identify and flag any outlier data values for further investigation. Global IDs' data-quality capabilities also handle stakeholder involvement. If a stakeholder notices an error, they can immediately escalate the issue.
Global IDs has a data quality team that specializes in helping customers achieve a high degree of data quality. This team understands the importance of data governance and data quality, and aims to provide a product that delivers the most comprehensive picture of the data environment. Its comprehensive data-quality solution is backed by robust support and is designed with confidence for companies of any size. Listed below are some of the key features of Global IDs' data-quality solution.
Snowflake Data Profiling
If you're looking to increase your business intelligence capabilities, you might want to consider the benefits of Snowflake data quality profiling. This service will help you analyze and track the quality of your data across your entire data warehouse, ensuring that it's fresh and accurate. Data quality can be a challenge to measure, so data profiling is important. Luckily, Snowflake has made its architecture compatible with a number of profiling tools, so there's no need to worry about how to use it.
With Snowflake Data Profiling, you can analyze a large amount of data in minutes. It will identify any patterns or discrepancies, as well as data ranges. Snowflake uses analytical algorithms to ensure that data matches up between different sources. Whether you want to compare data from different systems or create a new database to store data, Snowflake has the tools you need to analyze a large volume of data.
