Alation & Bigeye: A Potent Partnership for Data Quality

Alation and Bigeye have partnered to bring data observability and data quality monitoring into the data catalog. Read to learn how our newly combined capabilities put more trustworthy, quality data into the hands of those who are best equipped to leverage it.

Data quality can spell the difference between a business’ success… or failure. Bad data has caused organizations to make many costly mistakes. A recent Gartner survey estimated that the average cost of poor quality data for a single business is $12.8 million per year. And IBM has found that in just the US, businesses lose $3.1 trillion each year due to poor data quality.

How can data leaders address these challenges? People in organizations need a single platform that helps them identify quality data and proactively improve it. They also need a means of detecting low quality data, and a system for alerting those affected.

This platform should:

• Connect to diverse data sources (on-prem, hybrid, legacy, or modern)

• Extract data quality information

• Monitor data anomalies and data drift

• Track how data transforms, noting unexpected changes during its lifecycle

• Provide intelligence about the quality of information to all users (business and technical) through a single pane of glass.

Alation and Bigeye have partnered to deliver this platform. Together, we’ll help people in leading organizations make data-driven decisions with confidence.

Providing Quality Data to Everyone

As a platform for data intelligence, Alation boasts open APIs with which Bigeye can easily integrate. This integration empowers all data consumers, from business users, to stewards, analysts, and data scientists, to access trustworthy and reliable data. These users can also gain visibility into the health of the data in real-time.

Data teams use Bigeye’s data observability platform to detect data quality issues and ensure reliable data pipelines. Bigeye automatically monitors the data, looking at nine categories of potential issues (from freshness to format), as well as more than 60 data quality metrics, and intelligently adapts to changes in the business. If there is an issue with the data or data pipeline, the data team is immediately alerted, enabling them to proactively address the issue.

Alation’s Data Catalog: Built-in Data Quality Capabilities

With Alation’s Data Catalog, users get a consolidated view of enterprise data assets and corresponding data quality. Customers enjoy a holistic view of data quality metrics, descriptions, and dashboards, which surface where they need it most: at the point of consumption and analysis. Trust flags signal the trustworthiness of data, and data profiling helps users determine usability.

Furthermore, the Alation Data Catalog helps people understand how to apply data. It does this by supplying important context, such as other relevant data, plus common filters, joins, and queries for a given asset.

These details show people how to use the data accurately and compliantly. Robust data lineage empowers data engineers to quickly identify all upstream and downstream impacts of a particular data asset, so they can address the full scope of the problem.

Summary

The Alation Data Catalog serves data consumers through a single pane of glass; this lets them easily determine if they can trust the data and use it right away. Bigeye’s data observability platform detects data quality issues and ensures reliable data pipelines. Together, Alation and Bigeye help organizations make data-driven decisions with confidence by providing all data users, regardless of technical skillset, with access to quality data.

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