Driving a Data Driven Culture via Product Analytics
September 22, 2017
Driving a Data Driven Culture via Product Analytics
Score 10 out of 10
Vetted Review
Verified User
Overall Satisfaction with Treasure Data
Today, we use Treasure Data to manage the ingestion of our product data across the organization. It allows us to unify event data, metadata around our customers, and external data we may collect via surveys, etc. Treasure Data powers daily reports that are used internally by 200+ people throughout our organization to get a pulse of how our products are being used and tracking towards success.
- Workflows is a fantastic product that is configurable to bypass the need for specific extraction APIs, but flexible enough to chain together and manage jobs.
- The GUI allows you to easily switch between Presto/Hive, share queries with other analysts and maintain an audit trail of past jobs.
- The Bulk Integration library allows you to easily add on additional datasets that may further enhance the 360-view of the customer.
- Today, Treasure Data does require some technical expertise, especially as it relates to new features. I appreciate that the approach allows a quick time to value but does require coding expertise.
- I would love if Treasure Data had the ability to connect workflows with Github easily via the GUI.
- Additionally, I would love better search functionality to easily mine past jobs rather than paging through them via the console.
- Treasure Data has a tremendous positive ROI on our business in two ways. First it has allowed us to be more efficient and responsive. Second, it has allowed us to take more of a consultative position with our customers to elicit insights and guide discussions.
- One unexpected way is the capability of Treasure Data to help audit monitor past jobs. This isn't something that I had expected to be so powerful but having a link to point people to is extremely helpful (compare to a Redshift query that was run without an audit trail).