Last October, our friends at RJMetrics introduced the beta version of their ETL service, RJMetrics Pipeline. Today, they’ve officially taken that beta tag off, and spun out the product under a new name—Stitch.
As recently as few years ago, setting up an ETL pipeline was a painful process. And even after the ETL process was up and running, it required hours of engineering time to maintain.
Today there are quite a few ETL product offerings that significantly reduce this work and the cost. We use a variety of these tools, Stitch included, here at Mode. With them, we’re able to quickly consolidate data from a variety of SaaS tools into Redshift. With our data in one place, we can perform exploratory analysis that combines data from Salesforce and our product, ad networks and Marketo, our help desk and internal bug tracking. The result? Better informed decisions.
Data consolidation is getting cheaper, faster, and easier, eliminating one of the biggest barriers to company-wide analytics adoption.
How Stitch fits into the modern analytics stack
Here are the three parts of the modern analytics stack:
- ETL: The ETL process streams data into your data warehouse. Stitch extracts data from the SaaS tools and databases that run your business—Salesforce, Heroku, Zendesk—then loads it into your analytics warehouse.
- Analytics Warehouse: This is the database where your data is stored. Stitch connects to Amazon Redshift, with support for Postgres and Google BigQuery coming soon.
- Analytics Tool: You can then connect your analytics warehouse to Mode for custom, in-depth analyses using SQL and Python.
Matt Kent, Head of Engineering and Co-founder at Sprig, says: “We have a very lean technical team, and wanted our data scientists running predictive models on food costs and optimizing our menu, and our developers focused on the Sprig app. With Stitch, we were able to get our Stripe, Zendesk, and Heroku data streaming to Redshift in minutes, and it requires zero engineering maintenance.”
Alongside with the rebrand, Stitch has also rolled out an impressive lineup of feature updates:
- Data selection
- New integrations (Square and Hubspot)
- Improved data typing for all existing SaaS integrations
- Warehouse endpoints
- Hosted data warehouses
- Data freshness metrics by exposing received and batched timestamps
Need a little inspiration?
Check out this post to see how you can use Stitch and Mode to gain deeper insights into Salesforce data.
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