Let’s be real, data teams are drowning in manual work. On average, they’re spending around 70% of their time just trying to keep things in order — documenting datasets, tagging them with the right classifications, and writing tests to maintain quality.

But here’s the thing, it never really gets done. The moment you think you’ve caught up, something changes. New data gets created, existing data changes, old documentation becomes outdated, and the cycle starts all over again. It’s frustrating, it’s draining, and honestly, it’s not sustainable.

There has to be a better way.

That’s why we’re excited to introduce Collate AI AutoPilot, a breakthrough expansion of Collate AI to automate manual data management tasks. Let AutoPilot automate these manual tasks so you can focus on more strategic work.

By leveraging AI to combine automated data ingestion with intelligent assistants that handle documentation, tiering, and quality testing, Collate AI AutoPilot helps data professionals move away from repetitive, manual maintenance work that could take weeks, so they can focus on higher-value analytics and innovation projects that make the most of data and AI.

This post dives into the challenges facing data teams, and reveals how Collate customers are using the time freed up by AutoPilot to address more strategic initiatives. Initial customers say using the AutoPilot application is like adding team members to continuously maintain data hygiene.

Real-World Data Team Challenges

Today’s data teams must cope with the daunting challenges related to rapidly increasing quantities of data. They need different workflows to extract different types of metadata from different data sources, not only for initial onboarding but also for ongoing updates and operations. Challenges include:

• Documentation backlogs: Teams often deal with hundreds of tables that require documentation, but have limited time to complete the work.

• Ownership questions: It can be difficult to identify who owns specific data assets, leading to issues about data accountability and compliance

• Quality uncertainties: Concerns about data reliability and testing status often emerge at critical moments.

• Priority challenges: It’s hard to focus on the truly important data assets when everything seems high priority.

• Scaling limitations: Data assets are growing much faster than team size, leading to unsustainable workloads and the risk of team burnout.

• Knowledge gaps: Critical information about data fields is often concentrated among specific individuals, creating bottlenecks and risking disaster if that expertise is lost.

These challenges force many data professionals to spend the majority of their time on maintenance rather than innovation. Additionally, many data teams simply don’t have the necessary resources to address these data hygiene issues. This can create crushing technical debt that affects data analysts, scientists, and business users who rely on the data, eroding trust in the decisions based on it.

AutoPilot Enhances Data Team Productivity

To address these challenges, Collate AI AutoPilot delivers automated AI-powered metadata management to help data professionals focus on higher-value work. The application functions as an extension of your team, handling routine tasks while you concentrate on work that requires your specific expertise.

The AutoPilot application ingests all relevant metadata with a single click, while its AI Agents automatically generate descriptions, tiers, and data-quality-test recommendations, and a dashboard displays the amount of metadata generated.

Let’s take a closer look:

Streamlined One-Click Setup

AutoPilot simplifies the onboarding process with a truly straightforward setup — connect your data source and activate AutoPilot with a single click.

AutoPilot’s Metadata Ingestion Agent automatically extracts comprehensive metadata from your data sources. There's no need for complicated workflow configuration or manual extraction processes. You can then choose to run this extraction at your chosen intervals to make sure your metadata is up to date.

Intelligent AI Agents for Continuous Improvement

The core value of AutoPilot comes from the power of three AI Agents that set up and continuously maintain your metadata:

1. The Documentation Agent analyzes data patterns and relationships to automatically generate accurate table and column descriptions that enhance understanding and usability, and help data teams find the right table for a given use case. Manually creating this content consumes significant resources, so many data teams never get around to it, leaving data practitioners to struggle to understand their data.

2. The Tiering Agent monitors usage patterns across your organization to identify important tables, using tiers to prioritize assets based on business value. If you don't tier your data, you don't know what your important data is in order to direct your resources for discovery, reliability, uptime, and monitoring.

3. The Quality Agent quickly identifies patterns and constraints across similar tables to create appropriate tests that catch issues before they impact business decisions. It might recommend a particular test on a field with Social Security numbers or SKUs to ensure they’re formatted correctly, or that there are no numbers in a first-name field. If you don’t know the quality of your data, how can you trust the information shown in your executive dashboards?

These AI Agents are run on initial data onboarding, as well as scheduled on an ongoing basis to ensure the ongoing maintenance and updating of your metadata as your data evolves over time, without manual intervention.

The impact of AutoPilot can be seen through detailed Service Insights Dashboards that continuously quantify time savings and productivity improvements, displaying:

• How much metadata has been automatically generated by Collate AI, and how much manual work has been avoided

• Your business’ most-used and most-important data assets

• The distribution of sensitive data (such as PII) across your organization

• Cost analysis of resource-intensive queries, which helps identify additional optimization opportunities

• Data-quality health metrics across services

To see AutoPilot in action, watch the short video below:

Benefits for Data Teams

AutoPilot’s productivity improvements center around:

Fewer data requests and support tickets: With tables and columns thoroughly documented with up-to-date descriptions, data platform teams begin their day with fewer help requests to find data and explain data.

Reduced fire-drills and bug fixes: Proactively identifying data quality issues reduces the number of urgent issues that need immediate attention from data teams — reducing system downtime and improving quality of life for data professionals.

Improved self-service and democratization: Data analysts, scientists, and business users have better documented, prioritized, reliable data that they can understand more thoroughly, with confidence that they have the right data and that they are using it correctly.

Increased strategic contributions: Most importantly, teams using AutoPilot report shifting their time from repetitive metadata maintenance and management tasks to strategic data initiatives and innovation. As one data engineer at a Fortune 500 company noted: "AutoPilot effectively expands our team capacity, with automated processes handling routine tasks overnight, so we could focus on what grows the business."

Experience AutoPilot Today

Collate AI AutoPilot is like having additional team members, helping you elevate your metadata management while saving you time and resources. AutoPilot is available in Collate AI now as part of Release 1.7, and it will take you less time to get started than you spent reading this blog post. A subset of AutoPilot capabilities is also available for the open source OpenMetadata project.

To get started, Collate customers and OpenMetadata users can begin using AutoPilot now to automate manual metadata management. You can try out Collate AI AutoPilot in the product sandbox with demo data, or by signing up for Collate Free Tier to test with your data. Visit the Collate AI AutoPilot documentation to learn more.