How can Collibra enhance its Data Catalog to improve data discovery and understanding for business users?

Introduction

To enhance Collibra's Data Catalog for improved data discovery and understanding by business users, we need to analyze the current product, identify pain points, and propose targeted solutions. I'll approach this by examining user segments, analyzing their journey, and developing innovative solutions that align with Collibra's strategic goals.

Step 1

Clarifying Questions (5 mins)

• Looking at Collibra's position in the data governance space, I'm thinking about the primary use cases for the Data Catalog. Could you help me understand the most common scenarios where business users interact with the catalog, and what types of data they're typically searching for?

Why it matters: Determines the focus areas for improvement and helps prioritize features. Expected answer: Business users often search for financial data, customer information, and operational metrics for reporting and analysis. Impact on approach: Would tailor discovery features to these specific data types and use cases.

• Considering the evolving data landscape, I'm curious about the current data sources integrated with Collibra's Data Catalog. Can you share insights on the types and volume of data sources typically connected, and if there are any integration challenges users face?

Why it matters: Influences the scope of discovery improvements and potential technical constraints. Expected answer: Multiple sources including databases, data lakes, and SaaS applications, with challenges in real-time updates and metadata consistency. Impact on approach: Would focus on improving source integration and metadata synchronization features.

• Given the importance of user adoption in the success of data catalogs, I'm interested in understanding the current user engagement metrics. What are the key performance indicators you're tracking, and how do they compare to industry benchmarks?

Why it matters: Helps identify areas of low engagement that need improvement. Expected answer: Tracking metrics like daily active users, search frequency, and time spent in the catalog, with room for improvement in certain areas. Impact on approach: Would prioritize features that directly impact these engagement metrics.

• Thinking about Collibra's broader data intelligence platform, I'm wondering how the Data Catalog fits into the overall product ecosystem. How do users typically move between the catalog and other Collibra tools, and are there any integration points we should consider enhancing?

Why it matters: Ensures that improvements align with the overall product strategy and user workflow. Expected answer: The catalog serves as a central hub, with users often moving to data quality and lineage tools for deeper analysis. Impact on approach: Would focus on seamless transitions and consistent user experience across tools.