Introduction

Databricks Marketplace is a powerful platform for data providers to list and sell their data assets. To effectively manage and optimize your listings, it's essential to utilize the system tables within the Marketplace. These tables offer valuable insights into consumer interactions and can help you enhance your sales strategy.

What Are System Tables?

System tables in Databricks provide detailed records of various activities related to your data assets. Specifically, for the Marketplace, these tables live in the system.marketplace schema and include information about listing access and consumer actions.

Types of Marketplace System Tables

1. Listing Access Events: Records the consumer information for completed request data or get data events on your listings.

2. Funnel Events: Records impressions and actions taken on your listings.

Real-World Use Cases

1. Identifying Top Requesters

Understanding who your top requesters are can help you tailor your offerings and marketing efforts. For example, if you notice a particular company frequently requests your data, you might consider reaching out to them for a more tailored offering or partnership.

SELECT consumer_name, consumer_email, count(*) as requestCount
FROM system.marketplace.listing_access_events
GROUP BY consumer_name, consumer_email
ORDER BY requestCount DESC

2. Monitoring Listing Performance

Tracking the number of requests for each listing helps identify which data assets are in high demand. This information is crucial for deciding where to focus your resources and potentially adjusting your pricing strategy.

SELECT listing_name, consumer_cloud, count(*) as requestCount
FROM system.marketplace.listing_access_events
GROUP BY listing_name, consumer_cloud
ORDER BY requestCount DESC

3. Analyzing Consumer Actions

Understanding the different types of actions taken by consumers on your listings can provide insights into how they interact with your data. This can help you optimize your listing descriptions and improve the overall user experience.

SELECT event_type, COUNT(*) as occurrences
FROM system.marketplace.listing_funnel_events
WHERE listing_name = `{{listing_name}}`
GROUP BY event_type

4. Tracking Recent Consumer Requests

To stay on top of the latest trends and consumer interests, you can monitor recent data requests. This helps in identifying emerging trends and responding quickly to new demands.

SELECT event_date, provider_name, listing_name, listing_id, consumer_delta_sharing_recipient_name, consumer_cloud, consumer_region, consumer_name, consumer_email, consumer_company
FROM system.marketplace.listing_access_events
WHERE event_type = 'REQUEST_DATA'
AND event_date >= date_add(current_date(), -10)

Conclusion

Leveraging the power of Databricks Marketplace system tables enables data providers to gain valuable insights into consumer behavior and optimize their listings. By regularly analyzing this data, you can improve your sales strategy, enhance customer satisfaction, and ultimately increase your revenue.