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4 new features help you control your pipelines

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August 14 · Issue #31 · View online
Stitch
// Product updates
We’ve added four new features to help you customize and control your ETL processes and improve your data workflow:
  • advanced scheduling
  • post-load webhooks
  • notification extensibility, and
  • API key management.
Read all about them in our blog post.
We also have several new integrations available in open beta: Asana, Chargebee, Help Scout, LivePerson, MailChimp, and Sage Intacct. Also available are a revamped Recurly integration and Microsoft SQL Server with log-based replication.

Check out the Stitch changelog for details on other new features, including support for Facebook API v3.3, the inclusion of disputes data replicated from Stripe, and upgrades to our NetSuite integration.
// Talend update
Stitch is part of Talend, and our colleagues in the mother ship just released a new version of the flagship cloud data ingestion platform Pipeline Designer. Pipeline Designer can meet the needs of businesses that want to run transformations in their pipelines or support streaming data. Its serverless back end provides scalable, cost-effective data processing. Users can collaborate on building pipelines to increase productivity. And it offers a host of other groovy features.
Pipeline Designer can read and write to applications, databases, and data storage services, including:
  • Amazon Redshift
  • Snowflake
  • Azure SQL Data Warehouse
  • On-premises databases (Oracle, Microsoft SQL Server, MySQL, MariaDB, PostgreSQL)
  • Azure Data Lake Storage Gen2
  • Amazon S3
  • Azure Blob Storage
  • Apache Kafka
  • Salesforce
  • Marketo
// From our blog
The Stitch guide to choosing a business intelligence tool
Our guide to choosing a BI or data analytics platform, developed through what we’ve learned from working with thousands of companies to power their data infrastructure.
Why and how we migrated from Redshift to Snowflake
We made a change for our internal analytics. We’re taking advantage of Snowflake’s powerful data warehouse features and seeing better performance.
A transformation layer helps you do data modeling that scales
The transformation layer is where you take all of the raw data in your data warehouse and make it into clean tables that can generate useful insight about your business and product.
Create a map of your customers using Mode and Google Maps API
We created a map visualization that shows where Stitch customers are — here’s how you can do it too.

Browse the Stitch blog, or subscribe to our blog RSS feed to see all of our posts.
// Customer story
OrderMyGear provides an online platform for buyers and sellers of group apparel and gear. Its data infrastructure, based on a Google BigQuery data warehouse, includes SaaS platforms like Salesforce and Zendesk and internal services exposed via a REST API, with Looker as its BI tool. Read about how OrderMyGear uses Stitch and Singer to pipe all of its data.

You can learn more about how other companies use Stitch on our Customers page. Do you have an interesting Stitch use case? Send us an email and we’ll be in touch.
// From the community
A Stitch community member wondered why he was seeing different counts of rows exported from the Stitch dashboard and rows present in the tables in his Postgres destination. Our technical documentation manager has the answer.

Join the community and be a part of conversations about Stitch integrations and BI in general.
// Company updates
We’re hiring!
Stitch is looking to hire a junior software engineer. Join a top-notch team working on our data pipeline and the web services that support it.
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