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Alation + Soda: Dynamic Data Quality with the Data Catalog By Talo Thomson

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The merge of Alation and Soda allows for potent data-quality capabilities to be integrated into the data catalog, empowering you to fully leverage your metadata.
The post Alation + Soda: Dynamic Data Quality with the Data Catalog appeared first on Alation.

Alation and Soda are thrilled to announce a new partnership, which will bring potent data-quality capabilities into the data catalog. Soda’s data observability platform empowers data teams to discover and collaboratively resolve data issues quickly.

By leveraging Alation with Soda, organizations are equipped to answer key questions, such as:

Are critical datasets healthy and up-to-date?
Does the quality of this dataset meet user expectations?
What are the downstream and upstream dependencies?
Do we have end-to-end data pipeline control?
What can we learn about our data quality issues?
How can we improve and deliver trusted data to the organization?

Alation surfaces valuable metadata, so users can quickly and confidently answer these questions with total confidence and trust. With this integration, organizations can fully harness the power of their metadata to maintain pristine data pipelines and serve high-quality data to a broader range of users.

Unified Teams

One major obstacle presented to data quality are data silos, as they obstruct visibility and make collaboration tough. Soda provides end-to-end observability and data quality monitoring tools that grant crucial visibility. This enables modern data teams to discover, analyze, prioritize, and resolve silent data issues before they get out of hand.

Testing is key to the solution. Soda equips data and analytics engineers with a simple way to automatically test data every time it is transformed, which ensures data pipelines are more reliable. This allows data teams to easily stop a pipeline and quarantine bad data before there is a downstream impact.

Defining good data across all personas, too, is essential. With this integration, data consumers (such as data and BI analysts, data scientists, and data product managers) can define service level agreements to establish data quality expectations and standards for “good quality” data. Users can run quality checks with their own custom business rules, self-created monitors, and alerting mechanisms in Soda.

This means the alerts and monitoring information appear directly in the data catalog, so users don’t need to shift context or dashboards. It also means they get the data-quality information they need to use data with confidence.

Find, Understand, Govern, and Trust Data with Alation + Soda

Alation is powered by Soda’s real-time, data quality insights, which enable data teams to easily find, understand, and trust the data they use to build data products. Soda prescriptively solves the problem of discovering the silent data issues that matter; it gives data teams a central platform to track and score the health of data across core quality dimensions.

These data-quality tools give customers the foundation to build a rock-solid data management platform. This integration enables data users within organizations to continuously:

search and discover data
grant everyone self-service access to data
automate and federate data governance
trust and understand the data

As data teams use data to build data products, metadata in the data catalog empowers them to better understand and trust the data they leverage.

Good Data is Just a Search Away

Use the following interactive demo to explore how Alation + Soda surface critical data quality information and help you be more proactive in your governance efforts.

See for yourself how Soda embeds data quality features into the Alation Data Catalog with this interactive demo.

How does the integration help stewards? Data stewards can now receive an email alert notifying them of a data issue: the “orders” table has a data quality error. Soda automatically sets Alation’s trust flags if a data quality rule fails. This will automatically notify stewards and anyone “watching” this table.

The “Monitor Status Overview” provides a summary that shows the total number of data quality rules, both at the table & column level, and their current status. “Dataset Level Monitors” are the table level data quality rules and status that Soda is tracking. Here we can see that the table data quality rule “Ship date Should Always be later than order date” is failing.

Accelerate Root Cause Analysis

This integration empowers users to “play detective” to explore quality issues and uncover their source. Within Alation you can see how the result of the rule has been evolving over time and then deep-dive into the failed rows; this allows you to troubleshoot and conduct root cause analysis more quickly and efficiently.

Combine the data quality alerts from Soda and automated lineage from Alation to significantly speed up root cause analysis. Using Alation’s lineage capabilities, you can see if there are tables upstream, which may be related to the root cause of this issue. You can also see the impact on downstream objects and generate a Downstream Analysis impact report if needed.

Track your data-quality progress on all enterprise data. Alation Analytics is a reporting database that surfaces usage data about the data catalog users; it tracks progress towards your organization’s goals for applying data quality rules coverage. You can see a customized dashboard that pulls data from Alation Analytics and displays the historical progress of data quality rules coverage. Alation Analytics comes out-of-the-box, ready to help you track your Key Performance Indicators (KPIs).

Get Started

Curious to see what Alation + Soda in action? Check out this demo to see for yourself.

Eager to get started? Learn how Alation + Soda can help your organization manage metadata throughout the product lifecycle, by contacting a member of the team.

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The post Alation + Soda: Dynamic Data Quality with the Data Catalog appeared first on Alation.