At this week's Data & AI Summit Europe 2020, hosted by Databricks, Fivetran earned the ISV Partners Innovation Award. The award recognizes how Fivetran has collaborated with Databricks to empower data professionals by accelerating time to insight with Delta Lake and the Lakehouse architecture for the modern data stack.
Powering the modern data stack
Together, Fivetran and Databricks enable customers to:
- Focus on core business value, not data engineering for data pipelines. Fivetran automates data ingestion. That’s particularly important for SaaS and other cloud services where the APIs and schemas constantly change. Fivetran keeps up with the changes so you don’t have to worry about building and maintaining data pipelines.
- Accelerate time to insight. Fivetran delivers reliable, ready-to-query data in a number of ways:
- Normalized tables. The data behind SaaS applications and cloud services is typically not easily intelligible for analytics purposes. Fivetran Connectors automatically generate normalized schemas into Databricks and correspondingly well-documented entity relationship diagrams for data sources like Salesforce, Oracle Eloqua, NetSuite and 150+ others.
- Historical tables. With Fivetran history mode, data professionals can capture the type-2 slowly changing dimensions of the source tables of their choice. Simply select the configuration and set the synchronization time. Fivetran does the rest, making it easy to analyze historical data.
- Aggregated tables. Fivetran dbt packages for sources like Salesforce, Marketo, GitHub, Zendesk and more provide prebuilt, open source transformations to deliver the important aggregates you require.
- Easily orchestrate trusted data sets (upcoming). In partnership with Fishtown Analytics, the maintainers of dbt, Fivetran plans to:
- Deliver dbt packages for the most popular SaaS applications and cloud services, such as Salesforce, NetSuite and Marketo, giving customers ready-made, customizable aggregations.
- Orchestrate dbt jobs for Databricks using the new SQL analytics offering. That means data analysts will be able to run end-to-end data pipelines for big data analytics on their Lakehouse architecture in SQL, including transformations on Databricks.
Easy setup for automating data ingestion and historical data analysis
Fivetran continues to make it even easier to ingest data into Databricks. For example, customers don’t have to worry about setting up a staging area. Fivetran does that all for you with minimal configuration required. And historical data analysis is a snap, requiring just some simple configurations, rather than building and maintaining schema design and data pipelines. Take a look:
Making big data analytics accessible to everyone
Fivetran is additionally excited with plans to help make Databricks more easily accessible to data analysts and BI professionals. Databricks has announced its new Databricks SQL offering, empowering data analysts and BI professionals to more easily access data within Databricks via their favorite BI tool such as Tableau, Looker, and others via SQL. Fivetran plans to support this soon, including updates to the Fivetran dbt packages for Databricks SQL compatibility.
Joint customers include Red Ventures, Prodigy Games, Slice — and even Databricks itself. The combination of Fivetran and Databricks helps customers improve collaboration and allows them to scale big data analytics at a faster pace. Customers regularly report that the Fivetran zero-maintenance data integration service saves the equivalent of 2-3 full-time data engineers per year. As Jason Ordway, Chief Technology Officer at Slice, puts it:
With Fivetran, we have all of our data centralized and syncing in near-real-time so we can do advanced data science, create machine-learning models and conduct predictive analysis.
Michael Hoff, SVP of Business Development and Partners at Databricks, echoes the sentiment:
Fivetran allows our data engineering team to focus on core business instead of data pipelines.