Why CastorDoc x Trino makes sense?

Trino, formerly known as PrestoSQL, is a fast distributed SQL query engine designed for interactive analytic queries over large datasets from multiple sources. Similar to Vertica, it is designed for speed, scalability, and reliability in big data workloads. However, the challenges faced in finding the most relevant data assets, understanding the lineage between data warehouse tables, reports, or dashboards, and maintaining data visibility and trust are common in Trino as well.

CastorDoc, as mentioned above, addresses these challenges by optimizing search through popularity and advanced filtering options, providing data lineage, and organizing metadata in an intuitive interface. Therefore, integrating CastorDoc with Trino makes sense as it will enhance the user experience by making it easier to find relevant data assets quickly, understand their lineage, and ultimately trust and have visibility in the data. This will enable businesses to make better decisions faster, which is critical in today's fast-paced world.‍

How does CastorDoc x Trino integration work?

CastorDoc ingests metadata from Trino, then transforms and displays it in CastorDoc. The displayed metadata can include table & column names and descriptions, frequently run queries, frequent users of data assets, data lineage links, data quality tests, last data table update, technical and business tags, and more. CastorDoc organizes this metadata in an intuitive interface for both technical and business users. The ingestion process would take about 30 minutes to set up, and the metadata would be available in CastorDoc the next day. It is important to know that CastorDoc does not access the data itself, only the metadata. This ensures that your data stays safe and secure while CastorDoc delivers as much value as possible.

What does CastorDoc help you with?

Castor enables you to scale your self-service analytics strategy without losing control. We are designed with real use-cases in mind :

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🔎   You work with data you don't know

Your boss asks to build a report on "Churn for Premium Users in 2021". You need to find the relevant dataset, understand the meaning of its column, and use it fast.

✅ Reduce by 95% the time to find the right data asset (source : Lyft)

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🧬   A key employee is leaving

Mike, the data engineer that built the entire data infrastructure is leaving at the end of the month. All the knowledge is in his head. He needs to write it down.

✅ 42% of the work not recovered without knowledge management (source : 360Learning)

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👩🏽‍🌾  A new employee onboarding

Elsa, data analyst, arrived last week. She has no idea what data the company stores or how it is used. She spends hours asking around to gather knowledge.

✅ New hires are autonomous after day 1

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💣  A data pipeline is late

Nelson, customer success analyst, refreshes the "daily active users" dashboard every two minutes. The data hasn't arrived yet. He wants to know what is happening.

✅ 5x less Slack messages on #ask_data

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🗺️  No one knows where personal information are

Camila, from data governance, has to map all personal information to comply to GDPR requirements. She needs a list of all data assets and their location.

✅ 70% of employees have access to data that they shouldn’t (source)

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