Welcome to the Data Movement Movement
How Hightouch and Fivetran work together to enable leading organizations with the capabilities necessary to move data at scale.
Luke Kline
Alec Haase
March 30, 2023
7 minutes
Data movement has been an essential component of the data ecosystem since the earliest days–yet, organizations today still struggle with integrating data across their various systems and tools.
Despite heavy investments to move data efficiently, traditional ETL platforms and point-to-point integrations have only further exacerbated the two major data movement hurdles: getting data INTO the data warehouse and then moving the transformed data OUT of the warehouse to everyday tools. These similar yet distinct challenges have long troubled organizations.
Fortunately, a new generation of data integration platforms has emerged to tackle these obstacles head-on. Among the leaders in this movement are Fivetran and Hightouch, whose partnership and product offerings are poised to revolutionize how organizations move data at scale.
In this blog post, we will dive into how these two leaders empower organizations everywhere with the tools to navigate the complex data integration landscape and achieve their goals. Welcome to the Data Movement Movement.
Fivetran and Hightouch: Better Together
In the past, moving data between systems meant building and maintaining custom integrations, integrating with third-party APIs, normalizing schemas, dealing with rate limits, etc. The reality is data pipelines are not only costly but also lead to substantial opportunity costs. Your data teams should be spending their time optimizing your infrastructure, improving your workload performance, or unlocking new insights into your data–not managing brittle pipelines.
Fivetran solved the first portion of this problem by creating fully automated connectors that could extract and ingest data from any source before transforming and loading it into a central repository–the cloud data warehouse.
This process is commonly referred to as ELT (extract, transform, load), and it's arguably one of the most crucial points in data infrastructure as it underpins everything. Without ELT, your data is stuck in source systems. With ELT, Fivetran takes data from any data source and ingests it directly into your cloud data warehouse for analytics.
ELT
Most companies fail to realize that the modern data stack isn't just a horizontal line–it's a virtuous cycle, and data flows don't shouldn't just stop at your warehouse for analytics. The data should continue to the downstream tools business teams use–via data activation.
Your business teams need and want access to the rich customer data that lives in your warehouse–and they want this data made available in their operational tools. This can include all of the transformations your data team has built in the warehouse (e.g., LTV, MRR, lead score, churn rate, etc.) or simply just additional customer attributes, last login date, pages viewed, recent purchases, etc.
Moving the transformed data out of your warehouse is just as crucial as moving data into your warehouse.
Enter Hightouch and Reverse ETL.
Reverse ETL moves data out of your warehouse and syncs it directly to downstream operational tools. The entire purpose of Reverse ETL is to ensure that every employee in your business has access to the same data and customer definition that lives in your warehouse.
Hightouch solves the last-mile problem by taking the transformed data in your warehouse and syncing it back to the tools your teams rely on, like Salesforce, Google Ads, Iterable, Hubspot, etc.
Reverse ETL
Together Fivetran and Hightouch create a continuous flow of data from acquisition, to ingestion, to activation. Since Hightouch integrates directly with Fivetran, you can schedule your Hightouch syncs to run as soon as your Fivetran jobs have finished running. This creates a fully automated and streamlined pipeline that routes data through your warehouse and back out to your operational tools. At Hightouch, we call this approach "write-once, use anywhere."
Closing the data pipeline loop
Fivetran consolidates your data and establishes a single source of truth in your data warehouse, and Hightouch makes it possible to activate the rich insights derived by your data team.
Finding ways to streamline the flow of data is critical to our growth. Using Fivetran to get information into our data warehouse and activating that data with Hightouch enables the data team to deliver even more value to our organization and customers.
Josiah Brann
Director of Engineering
•
Discovery Education
Mutual Customers
Over 230+ mutual customers are using Fivetran and Hightouch to automate, manage, scale, and close the loop between their data pipelines:
- IntelyCare, the "Uber for nurses," saved over $1M in marketing spend using Fivetran and Hightouch to power in-app personalization, ad-retargeting, and lifecycle marketing.
- Ramp, a $5B+ payment platform, used Fivetran and Hightouch to build a personalization that powers 25% of all sales pipeline.
- Imperfect Foods, the leading online grocer for eliminating food waste, used Fivetran and Hightouch to increase reactivations by 53% and decrease CAC by 15%.
- Nandos, the world-famous food chain, reduced data integration time by 75% with Fivetran and Hightouch.
- Blend, a large financial services firm, reduced the time it takes to generate reports by 50% Fivetran and Hightouch.
MDSCON
Make sure to register for MDSCON and join us in San Francisco if you haven't already. Use code MDSCON-HIGHTOUCH for 15% off when you register. We're going to be participating in many different ways:
- Breakout Session: Centralized Integrations for Centralized Data with Josiah Brann, Director of Engineering at Discover Education
- Serving Data: Join Hightouch, Monte Carlo, Snowflake, and data.world for an invite-only dinner and opportunity to network with other data leaders like yourself.
- The Data Pong After-Party: Come relax at SPIN after the conference and enjoy an open bar and some tasty treats with new and old friends.
In the meantime, check out our Fivetran page to learn how to close the loop on your data pipelines.