It’s been about a decade since Tom Montgomery and fellow Stanford University students Kyle Hency, Preston Rutherford and Rainer Castillo began hawking shorts — really, really short shorts — on the shores of Lake Tahoe. These shorts represented a backlash-of-sorts response to the huge, long and ultra-wide styles of the time. Or, as Montgomery remembers it, they were a counter attack to the “dark days of long, baggy cargo shorts.”

Now known today as Chubbies, the San Francisco-based clothier has gone from selling a few dozen pairs of shorts in Lake Tahoe to distributing a clothing line in its own branded stores, and across the globe online. It got there because Chubbies capitalizes on a martech data stack, niche consumer offerings, in addition to its out-of-the-ordinary namesake.

“We were looking for a funny, eye-catching name that no other fashion brand would call themselves. We thought Chubbies was hilarious,” Montgomery says. “Then we just started calling it Chubbies, and our friends wouldn’t let us change it. In San Francisco, the sun is barely out. When it is, we embrace it wearing tiny shorts. The brand was something that came naturally to us.”

Chubbies’ marketing efforts have advanced from combing the beaches for customers to analyzing a blend of customer data from Shopify, Klaviyo, Google Analytics, Google Sheets and more. All of this data gets commingled and replicated by Fivetran into the Google BigQuery data warehouse. That’s where advanced analytics are performed on a grand and granular scale — with the goal of understanding customer and consumer behavior.

“The mission to all of our business units is to fully understand how they are affecting our customer, and to understand their part in a customer’s life, experience, and also understand the levers they need to press to increase the value of that experience,” Montgomery says. “For us, this process is king. The data that is being fueled by Fivetran is the important part of the process that helps us optimize.”

Chubbies runs Looker as its (BI) business intelligence tool that sits atop the Google BigQuery data warehouse.

“The data we are reporting in with Fivetran into Looker is the basis of meetings as opposed to the meetings being about figuring out how to get the data,” Montgomery says.

Among its critical marketing metrics, Chubbies has data at its fingertips to analyze what ads prompted orders, and what emails lead to sales. It’s about understanding consumers’ “lifetime value and revenue implications,” Montgomery says.

Montgomery says that its Fivetran-powered martech stack enables Chubbies to gain deep insights into buying behaviors. Fivetran, he says, has enabled Chubbies to create a “holistic picture” of its operations.

“We analyze consumers from their first piece of content they see all the way through their 10th order, with any exchanges and emails along the way,” Montgomery says. “Our web analytics is about how people are behaving on the site once we get them to arrive on the site. Data with Fivetran has a been a huge driving force for us.”

Chubbies says it’s quite satisfied with the BigQuery data warehouse, and how effortlessly Fivetran moves Chubbies’ data to the warehouse. And if anything goes wrong, “Fivetran support is always available,” says Carlos Nido, a data analyst.

“We like BigQuery a lot. It’s simple with Fivetran for managing the upload and syncing process,” says Nido. “One of the nice things about Fivetran is the ease of integration.”

For an analysis on the difference between a row-based and column-oriented data warehouse, see our in-depth analysis here.

Nido explains that, prior to Chubbies adopting Fivetran, data from Chubbies’ applications had to be uploaded manually.

“Before Fivetran, all of our data was on all different platforms,” Nido says. “Everything was uploaded manually. Everybody pulled data from different sources. Now, everything lives in one ecosystem with Fivetran. We can easily analyze the data that we want. It’s plug and play with Fivetran, in what normally would consume massive engineering resources.”

Montgomery, meanwhile, says that the Chubbies bottom line is much better served with Fivetran.

“Fivetran is allowing us to make better decisions. Combined with Looker, Fivetran is providing access to data for many people at Chubbies,” Montgomery says. “They can own their own reporting. This frees up time for the data team to make more of a strategy approach, to create long-term solutions and to move away from creating reports for people.”

All in all, Fivetran offers plenty of data connectors in addition to the ones used by Chubbies. They range from AdRoll to Zuora. Essentially, these connectors are the data from business applications, files and databases that Fivetran syncs into a data warehouse for you.

(The Fivetran sales team is available to present a demo, and provide a free trial. Sign up here.)

About Fivetran: Our mission is to democratize data, to make companies data driven, and to give analysts easy access to disparate data sources to perform advanced analytics.

With as little as a 5-minute setup, Fivetran replicates all your applications, databases, events and file storage into a high-performance data warehouse. Our cloud data pipelines are zero-configuration, zero-maintenance and fully managed by Fivetran.

Using Fivetran, businesses big and small gain complete control and ownership of their data. It’s easy to join data sources, perform agile analytics, and ultimately discover valuable insights using SQL or the business intelligence (BI) tools of choice.

Chubbies sells short shorts — and bets long on data analytics enabled by Fivetran was originally published in Fivetran Blog | Ideas to Inform Your Data Strategy on Medium, where people are continuing the conversation by highlighting and responding to this story.

“Citus Data provides SalesLoft with a hosted, multi-tenant, Postgres environment without the overhead of implementing the technology ourselves. We deal with large data volumes at SalesLoft,” Sandt says. “In order to help scale our technology as we drive towards the enterprise, we identified a need to tenant our systems. Citus made this process easier on us by providing the appropriate libraries and operational infrastructure.”

SalesLoft’s challenge was how to combine the sharded tables in a columnar data warehouse, AWS Redshift, in order to perform advanced analytics. The Fivetran off-the-shelf solution was to replicate every database in the cluster individually by using a standard Fivetran Postgres connector. As a result, SalesLoft didn’t have to spend time or resources building or maintaining custom infrastructure to replicate sharded data.

“Fivetran solved the problem of getting the data into our warehouse without having to run the gambit of rolling custom infrastructure for such tasks,” Sandt says. “Fivetran effectively centralized the data for us so that we can provide insight into customer usage.”

The general strategy for replicating sharded databases is simple: Replicate each individual database into its own schema, then use a VIEW to re-combine the tables at query time. This side-steps combining the sharded data in the ETL pipeline, avoiding tricky logic that is difficult to debug and maintain. The data analysts working with the data queries the VIEW as a single logical table even though it’s physically split on disk.

This strategy leverages the fact that modern data warehouses natively handle computations across tables sharded over multiple nodes — it’s how data is stored under the hood. In practice, querying VIEWs that are UNION SELECT’s of the underlying sharded tables is highly performant. The data warehouse query planner is smart enough to avoid materializing the intermediary VIEW.

The final piece to this strategy is automating this whole process.

Fivetran handles the difficult parts by automatically detecting and syncing new schemas and tables in the source databases. A simple Python script was all that was necessary to automate keeping the VIEWs up-to-date as new schemas and tables are created in the Citus Data cluster. This can be scheduled by cron or run on AWS Lambda. Here’s a link to the VIEW creation script

“Fivetran makes it stupid simple to get data from disparate source systems into a centralized warehouse,” Sandt Says. “Fivetran has a very complete vision of the space they operate in, and the required competency with underlying database systems to get us up and running quickly.”

The Fivetran Postgres connector is just one of the dozens of connectors Fivetran offers. These connectors are the data from your business applications, and databases, that Fivetran syncs into a data warehouse for you.

About Fivetran: Our mission is to democratize data, to make companies data driven, and to give analysts easy access to disparate data sources to perform advanced analytics.

With as little as a 5-minute setup, Fivetran replicates all your applications, databases, events and file storage into a high-performance data warehouse. Our cloud data pipelines are zero-configuration, zero-maintenance and fully managed by Fivetran.

Using Fivetran, businesses big and small gain complete control and ownership of their data. It’s easy to join data sources, perform agile analytics, and ultimately discover valuable insights using SQL or the business intelligence (BI) tools of choice.

(The Fivetran sales team is available to present a demo, and provide a free trial. Sign up here.)

Replicating Sharded Databases: A case study of SalesLoft, Citus Data and Fivetran was originally published in Fivetran Blog | Ideas to Inform Your Data Strategy on Medium, where people are continuing the conversation by highlighting and responding to this story.

It only makes sense that Fivetran and SendGrid have partnered together. They each have similar missions: They deliver data on a grand scale.

Founded in 2009, SendGrid is a leading digital communication platform, enabling businesses to engage with their customers via email reliably, effectively and at scale. Fivetran builds data pipelines connecting and replicating disparate business data sources to a data warehouse — for the goal of advanced analytics on a grand and granular scale. With Fivetran, SendGrid users can co-mingle data from their SendGrid accounts with data from their other business applications to gain deep insights into all of that data.

“It was only a matter of time until Fivetran and SendGrid would become partners. SendGrid’s platform already provides engagement data in real time. With Fivetran, our customers can get even wider views into their own companies and customers,” says Elliot Goldwater, director of business development at SendGrid.

(The Fivetran sales team is available to present a demo, and provide a free trial. Sign up here.)

Logan Welley, who heads the Fivetran partnership program, agreed. “Adding SendGrid to the growing list of Fivetran technology partners was bound to happen. Each company enhances the other company, all of which benefits end users and their goal of performing agile analytics,” Welley says.

SendGrid is just one of the dozens of connectors Fivetran offers. These connectors are the data from your business applications, and databases, that Fivetran syncs into a data warehouse for you.

About Fivetran: Our mission is to democratize data, to make companies data driven, and to give analysts easy access to disparate data sources to perform advanced analytics.

With as little as a 5-minute setup, Fivetran replicates all your applications, databases, events and file storage into a high-performance data warehouse. Our cloud data pipelines are zero-configuration, zero-maintenance and fully managed by Fivetran.

Using Fivetran, businesses big and small gain complete control and ownership of their data. It’s easy to join data sources, perform agile analytics, and ultimately discover valuable insights using SQL or the business intelligence (BI) tools of choice.

Fivetran partners with SendGrid: It's all about data delivery was originally published in Fivetran Blog | Ideas to Inform Your Data Strategy on Medium, where people are continuing the conversation by highlighting and responding to this story.

Case study takeaway: Always-on customer support. Enables the “2,000-foot view.” Frees up engineering sources. Fivetran “UI is simple and streamlined.”

Urban Airship offers a platform for mobile growth services, from mobile push, email to text — all with orchestration and AI-based optimization solutions. In short, Urban Airship delivers hyper-personalized messages in real time on any channel in a customer’s martech stack.

Fivetran immediately added value to Urban Airship by transferring Urban Airship’s corporate data from a legacy third-party system into Urban Airship’s SQL Server relational database. Fivetran had the right connectors at hand and obliged immediately.

(The Fivetran sales team is available to present a demo, and provide a free trial. Sign up here.)

Olv Grolle, the director of business systems at Urban Airship, says that the service level, knowledge and support from Fivetran “was very impressive.”

“Service, that was one of the factors that won our evaluation over Stitch. It went down to the level of setting up a Slack channel with us as a means to directly connect to our Fivetran support engineers,” Grolle says. “That was very compatible with our modus operandi. We’re very happy customers. The level of support and nurturing we get is astonishing.”

This is yet another textbook example of the Fivetran always-on customer support credo. What’s more, it underscores that users of Fivetran gain ownership of their application data, even if they stop using that application.

All in all, Fivetran replicates business applications, databases, events and file storage into a high-performance data warehouse. The Fivetran cloud data pipelines are zero-configuration, zero-maintenance and fully managed by Fivetran.

Set it and forget it

Before Urban Airship settled on Fivetran, the company evaluated other platforms, but none of them met their needs. “We kept running into a myriad of problems,” says Ed Zanelli, the Urban Airship data architect.

One problem Fivetran solved was that Urban Airship couldn’t get transaction lines from its NetSuite application, one of dozens of business applications that Fivetran supports. Fivetran not only supports those transaction lines, but also offers sync frequency down to 5 minutes for all of its connectors.

“If you can’t get the transaction lines, you’re not getting anything with Netsuite,” Zanelli says.

“With Fivetran, we just set it and forget it,” Zanelli says.

Zanelli says the out-of-the-box connectors Fivetran has built for business applications function without a hitch. And, with a setup that took just minutes, Fivetran enabled Urban Airship to begin the data flow immediately.

“We are now able to correlate data across core business systems that we were not able to do before,” Zanelli says. “We’re now able to cross reference data from different business systems in a coherent way, to take that 2,000-foot view.”

Focus on data instead of replication

Urban Airship has chosen several Fivetran pre-built app “connectors.” They include Netsuite, Salesforce, Stripe and Zuora.

“Fivetran has experts in house who have managed to understand the architecture of a lot of business tools,” says Zanelli. “So now we don’t need to deal with the engineering technical side. We can actually focus on the business data.”

Zanelli added: “We were able to free up all resources working on dedicated data replication”

Grolle weighed in as well:

“If we hadn’t switched to Fivetran, I think we would still be building connections from scratch instead of understanding our business operations data. The Fivetran UI is simple and streamlined.”

Grolle echoes what many satisfied Fivetran customers say:

“Fivetran just works. You set up your replication point, and source, and target system, and that’s virtually it,” Grolle says. “It has proven very valuable. Fivetran has developed a great solution.”

About Fivetran: Our mission is to democratize data, to make companies data driven, and to give analysts easy access to disparate data sources to perform advanced analytics.

With as little as a 5-minute setup, Fivetran replicates all your applications, databases, events and file storage into a high-performance data warehouse. Our cloud data pipelines are zero-configuration, zero-maintenance and fully managed by Fivetran.

Using Fivetran, businesses big and small gain complete control and ownership of their data. It’s easy to join data sources, perform agile analytics, and ultimately discover valuable insights with the business intelligence tools of your choice.

Urban Airship says Fivetran replicates data into a warehouse as easy as "set it and forget it" was originally published in Fivetran Blog | Ideas to Inform Your Data Strategy on Medium, where people are continuing the conversation by highlighting and responding to this story.

Fivetran customers may limit the SELECT permissions to certain schemas and tables. We even let you do that all the way down to the column level with MySQL, Postgres and SQL Server. Fivetran encourages similar practices with your data warehouse, too. One important caveat is the Amazon Redshift data warehouse. If you connect Fivetran with the master/admin user, we will do routine database maintenance on your behalf: VACUUM (DEEP COPY) tables on weekends.

That said, we understand that security and convenience (accessibility) are always a trade-off, and we try to accommodate this where appropriate. That’s why we have introduced a second approach to authenticating Google Sheets when uploading them to your Fivetran supported data warehouse.

Our original implementation of Google Sheets uses OAuth for authentication. OAuth is a method for a user to delegate access for all files to which they have been granted access. Some companies, by default, give access to all Google Drive files to all employees. As a result, the Google OAuth method for Google Sheets grants Fivetran permission to access all of your company’s Google Spreadsheets, even the ones you haven’t connected to your data warehouse.

Some of our clients have told us that access this broad was unacceptable.

So we added a second method — Service Accounts for authentication. This allows users to grant access on a per-spreadsheet basis. The Service Accounts method, however, requires granting access to a domain (fivetran-production.iam.gserviceaccount.com) that is outside of your Google account domain.

There are a few caveats:

For some G Suite account holders, the practice of sharing outside the domain is banned by the security policies of their employer. As a result, these Fivetran customers must use the OAuth method unless G Suite permissions are altered to allow sharing outside the domain.

We should also note that if an employee is authenticating Google Sheets via the OAuth method from his or her own corporate Google account, the connection between those sheets will break if that employee’s Google account is terminated. This is not the case when it comes to the Service Accounts method.

Here is the Fivetran setup guide for both methods to upload Google spreadsheets to your data warehouse.

All in all, Google Sheets is just one of the dozens of connectors Fivetran offers. These connectors are the data from your business applications, and databases, that Fivetran syncs into a data warehouse for you.

Fivetran supports four column-oriented data warehouses. They include Google BigQuery, Amazon Redshift, Snowflake and the Microsoft Azure SQL Data Warehouse.

For an analysis on the difference between a row-based and column-oriented data warehouse, see our in-depth analysis here.

About Fivetran: Our mission is to democratize data, to make companies data driven, and to give analysts easy access to disparate data sources to perform advanced analytics.

With as little as a 5-minute setup, Fivetran replicates all your applications, databases, events and file storage into a high-performance data warehouse. Our cloud data pipelines are zero-configuration, zero-maintenance and fully managed by Fivetran.

Using Fivetran, businesses big and small gain complete control and ownership of their data. It’s easy to join data sources, perform agile analytics, and ultimately discover valuable insights using SQL or the business intelligence (BI) tools of choice.

The Fivetran sales team is available at sales@fivetran.com.

Fivetran announces new Google Sheets permissions, security options was originally published in Fivetran Blog | Ideas to Inform Your Data Strategy on Medium, where people are continuing the conversation by highlighting and responding to this story.

Fivetran should be your company’s default method to load business data into a data warehouse. In addition to supporting and replicating databases into a data warehouse, Fivetran also syncs and replicates data from dozens of business applications into data warehouses.

We’re constantly updating these easy-to-setup “connectors” and developing new ones. Today, we’re proud to announce the addition of the Fivetran connector for Klaviyo—a leading e-commerce marketing platform and so much more.

“With Klaviyo, you can easily segment your audience and target triggered campaigns based on things that actually happened instead of guesswork. Target based on what they actually bought, what they actually looked at on your website, where they actually interact with your emails, how much they actually spend so you can send emails they actually want to receive.”

Carlos Nido, an analyst for clothier Chubbies—which is a customer of Fivetran and Klaviyo—is quite satisfied with the Klaviyo connector.

“We are very happy with the new Klaviyo connector. It has helped us get a deeper understanding of our CRM outreach and how we re-target our repeat customer base. Off the bat, we have been able to systematically quantify the effect of mixing in a fun lifestyle email to our customers in order to keep them interested in our brand.”

Here is the link to the Fivetran documentation for Klaviyo. Fivetran provides a complete schema diagram, too. Setup, as with other Fivetran connectors, is super simple. For starters, you must have an active Klaviyo account. From the Fivetran user interface, enter the desired destination schema name and Fivetran will assist you in getting an API key. Then follow a few short steps.

Fivetran offers a pre-engineered data pipeline to centralize your business data into a data warehouse. Fivetran supports three column-oriented warehouses. They include Google BigQuery, Amazon Redshift and Snowflake. From the data warehouse, companies may embrace any business intelligence (BI) tool of their choice to conduct advanced analytics in a bid to gain deep insights into their customers and product.

About Fivetran: Our mission is to democratize data, to make companies data driven, and to give analysts easy access to disparate data sources to perform advanced analytics.

With as little as a 5-minute setup, Fivetran replicates all your applications, databases, events and file storage into a high-performance data warehouse. Our cloud data pipelines are zero-configuration, zero-maintenance and fully managed by Fivetran.

Using Fivetran, businesses big and small gain complete control and ownership of their data. It’s easy to join data sources, perform agile analytics, and ultimately discover valuable insights.

The Fivetran sales team is available at sales@fivetran.com.

Fivetran rolls out the Klaviyo connector was originally published in Fivetran Blog | Ideas to Inform Your Data Strategy on Medium, where people are continuing the conversation by highlighting and responding to this story.

There’s no magical way to keep databases in sync with your data warehouse. But some methods are better than others.

Fivetran, through heavy engineering, does it the most favorable way. Our log-based replication approach can help companies perform advanced analytics without impacting ongoing business operations. This is the most superior method of replicating changes to your data warehouse.

The databases for which Fivetran supports log-based replication include DynamoDB, MongoDB, MariaDB, MySQL, Oracle, PostgreSQL and SQL Server.

The engineers at Fivetran have worked tirelessly to develop a method that reads the logs of changes to the master database. This is the same mechanism that a database replica uses to keep up to date. This technique uses substantially less computing power compared to alternative methods such as “last modified queries” and “daily snapshots” that some of our competitors embrace.

For our more detailed discussion of “daily snapshots” and “last modified queries” read here.

Log-based replication

Under the approach of reading database changelogs, data is updated with every version of each change. This includes tables without last modified dates. This method also captures deleted information, thus bolstering your advanced analytics.

Log-based replication does not compete with other database queries because it involves reading directly from the log files. This helps to remove stress on your production systems. This approach is the closest you will get to real-time updates.

Some of the other benefits of log-based replication include having to spend less on compute capacity. And, as you scale, you don’t have to worry about your database crashing during replication because the amount of data used in the Fivetran log-based replication process is miniscule.

All of this has real-world, customer-facing consequences. Foremost among them is that the alternative methods to log-base replication can cost you business, and lots of it.

Don’t lose customers

Consider, if you will, a hypothetical use-case scenario, one in which an e-commerce site is sitting atop of the MySQL database but is not updating by the log-based replication method. If your replication service is putting huge demands on the database looking for changes, the result of this could slow down the e-commerce site.

And, as your table sizes increase, the SELECT* queries of a naive database replication approach will consume more database resources. You could be facing degrading database performance at the worst time: Black Friday — when every millisecond of response time counts. If a potential customer goes to buy something from this e-commerce site, the website might be so strained that a consumer’s purchase won’t be registered.

Consumers wanting to buy something can find themselves stalled on the shopping cart trying to press buy, yet nothing is happening. The site is frozen or at a crawl. The frustrated consumer leaves the site, and goes elsewhere. This could be avoided by choosing Fivetran and its log-based replication method.

Other points of note:

• The initial sync of a database is not and cannot be log-based.
• Depending on the amount of data being synced, we recommend that the initial sync be performed in batches, during the off hours.
• We also recommend that, once you’ve done your initial sync, set your database to retain changelogs for seven days so that, in the event of an update error, the logs will be there.

Here is a link to the Fivetran support documentation on the topic.

All in all, Fivetran offers a pre-engineered data pipeline to centralize your data into a data warehouse. Fivetran supports three column-oriented warehouses. They include Google BigQuery, Amazon Redshift and Snowflake.

For an analysis on the difference between a row-based and column-oriented data warehouse, see our in-depth analysis here.

In addition to supporting and replicating databases into a data warehouse, Fivetran also syncs and replicates data from dozens of business applications, ranging from Asana to Zendesk, and everything in between and more. At the end of the pipeline, at the warehouse level, is where companies perform advanced analytics with their business intelligence tool of choice.

About Fivetran: Our mission is to democratize data, to make companies data driven, and to give analysts easy access to disparate data sources to perform advanced analytics.

With as little as a 5-minute setup, Fivetran replicates all your applications, databases, events and file storage into a high-performance data warehouse. Our cloud data pipelines are zero-configuration, zero-maintenance and fully managed by Fivetran.

Using Fivetran, businesses big and small gain complete control and ownership of their data. It’s easy to join data sources, perform agile analytics, and ultimately discover valuable insights.

For a Fivetran demo, reach out to our team at sales@fivetran.com.

Fivetran updates warehoused databases via log-based replication was originally published in Fivetran Blog | Ideas to Inform Your Data Strategy on Medium, where people are continuing the conversation by highlighting and responding to this story.

Fountain is a startup in the growing SaaS employee applicant-tracking hiring space. The San Francisco business offers a software platform for companies — large and small — that manages, tracks, and performs much of the hiring backend process for businesses to secure hourly workers in retail, hospitality, restaurant, manufacturing, delivery and other sectors.

As with any company on the path to growing success, Fountain realized that, in today’s competitive and data-driven climate, it needed to conduct advanced analytics to gain deep and fresh insights into its customers and business model — all in a bid to keep growing and to secure new clients by offering a better product.

But Fountain did not want to waste precious resources dedicating staff to perform the burdensome ETL routine to cull the data from each of their business applications to create reports, which could often end up being stale. That’s why Fountain chose Fivetran, which made it painless to replicate Fountain’s data into a data warehouse— in near real time. After all, Fountain employs about 30 workers. So the more time they could spend on the core product, the better, says Mark Schindler, Fountain’s head of analytics and business intelligence.

“We’ve got plenty of other things to focus on, instead of using our resources to put our data into a warehouse,” Schindler says. “We have a guy who is a data scientist, who is building product-based features in the machine-learning area.”

As a relatively new company, the ability to perform advanced analytics, Schindler says, is eye opening. It’s a fundamental shift in the way the business is being maintained.

“What Fivetran is providing us, it’s something that didn’t exist for us before,” Schindler says. “We didn’t even have an easy way for our team to access how our customers are doing certain things. This is going to give us good insights into our own product.”

Analytics operating table

Schindler says he wanted his company’s business data replicated into a warehouse, on the operating table if you will, and ready for him to perform advanced-analytics surgery with fresh data. He didn’t want to concern himself or his staff about how the data reached his data warehouse, which is Google’s BigQuery.

Fivetran, he says, was an easy solution. Fivetran transformed the normally vexing and complicated process of replicating data into a warehouse, and turned the process into a “no brainer.”

“We could do the ETL ourselves, but it would be a lot of headaches,” Schindler says. “We investigated Stitch and Fivetran. Fivetran was so easy to trial and set up. It was a no-brainer. The Fivetran team did a great job, too. We easily and quickly got our data into BigQuery.”

Data management

Fivetran offers dozens of so-called “connectors.” These are everyday business applications that, with a press of a button, their data is replicated by Fivetran into a data warehouse of a company’s choice. Fountain is using the Fivetran-built connectors for Salesforce, Zendesk, Facebook Ad Insights, LinkedIn and Google Sheets. Fivetran can sync connectors every 5 minutes, giving analysts fresh, up-to-date data to query.

“This is a very sustainable product we can continue to use for the future,” Schindler says of Fivetran. “The setup process, I did on a quick telephone call. I heard that it was going to be easy. It was easier than I expected.”

What’s more, Schindler says he’s impressed with the web-based Fivetran user interface.

“The interface is really easy. You don’t have to be technical to manage this. I appreciate that. I have no gripes.”

Business intelligence

At the end of the Fivetran pipeline, companies may deploy any business intelligence (BI) tool of their choice to perform advanced analytics in a bid to gain deep insights into their customers and into their own product.

In Fountain’s case, Schindler has opted to decipher company data using Looker as his BI tool. Looker is a Fivetran business partner. Looker simplifies the data-crunching process and helps business easily create insightful dashboards.

Counter culture

Combining Fivetran and Looker, Schindler says, has revolutionized Fountain’s work culture. It has become a data-driven workforce, and has opened up the data spigot to Fountain staffers to access and manipulate, regardless of their technical capabilities.

“There’s a cultural aspect of using Looker and Fivetran. It’s inviting people to answer questions with data,” Schindler says. “This has brought in a cultural mindset for our team to develop, and to grow into a data-informed decision-making team at a company level.”

“Gut” instincts

As Fountain’s head of analytics and BI, Schindler says Looker and Fivetran have fundamentally altered the decision-making equation. Now, important issues, such as corporate direction, are being addressed more scientifically.

“We’ve gone a lot on gut. This new focus on data allows for more of a consistent, and a little bit more of a reliable and valid way of making decisions. And it is reducing the risk of the gut feeling process.” Schindler says. “If people are trusting their decisions, we won’t have too many missteps.”

Zero maintenance, zero configuration

Two of the many Fivetran core features are zero-maintenance and zero-configuration. Schindler says the Fountain team is capitalizing on those Fivetran values. He says without Fivetran, it might have taken months for Fountain to have built a data pipeline. And without Fivetran, the Fountain team would remain stuck wasting time supporting that pipeline.

“We didn’t have the team to build out the ETL. My concern was also that, we didn’t have the team to maintain it, even if we could build it initially,” Schindler says. “The easy setup with Fivetran was one thing. We set up BigQuery with just a few clicks. And the zero-maintenance piece moving forward is arguably even more valuable.”

About Fivetran: Our mission is to democratize data, to make companies data driven, and to give analysts easy access to disparate data sources to perform advanced analytics.

With as little as a 5-minute setup, Fivetran replicates all your applications, databases, events and file storage into a high-performance data warehouse. Our cloud data pipelines are zero-configuration, zero-maintenance and fully managed by Fivetran.

Using Fivetran, businesses big and small gain complete control and ownership of their data. It’s easy to join data sources, perform agile analytics, and ultimately discover valuable insights with the business intelligence tools of your choice.

For a Fivetran demo, reach out to our team at sales@fivetran.com.

After embracing Fivetran, a data-driven culture blossoms at applicant-tracking startup Fountain was originally published in Fivetran Blog | Ideas to Inform Your Data Strategy on Medium, where people are continuing the conversation by highlighting and responding to this story.

At Fivetran, our mission is to democratize data, to make companies data driven, and to give analysts easy access to disparate data sources to perform advanced analytics.

With that mission in mind, we’re continuing to release a slew of new product and feature offerings. We’re also broadening our sales-operations base to include the European Union (EU). We have just opened an office in Dublin, Ireland.

Our Dublin address is Charlemont St, Saint Kevin’s, Dublin 2, Ireland. Fivetran is compliant with the General Data Protection Regulation (GDPR) that takes force in the EU on May 25. Our Dublin office will be serving Europe, the Middle East and Africa.

Fivetran is also hiring sales professionals at our Dublin office.

We also have available sales and engineering positions at our offices in Denver CO, Oakland CA, and Bengaluru India. Check the Fivetran careers page for details.

Joining the Fivetran teams means you could work alongside our savvy and sophisticated staff whose recent accomplishments include the implementation of a 5-minute sync for all of our integrations with databases, business applications and file stores.

We’ve also designed new integrations — what Fivetran calls “connectors.” The new connectors, all in beta, include AdRoll, DoubleClick Campaign Manager, Email CSV ingestor, Klaviyo, LinkedIn Ad Analytics, Optimizely, SendGrid, Yahoo Gemini and others.

Reach out to us for a demo at sales@fivetran.com.

About Fivetran: With as little as a 5-minute setup, Fivetran replicates all your applications, databases, events and file storage into a high-performance data warehouse. The data pipeline is zero-configuration, zero-maintenance and fully managed by Fivetran.

With Fivetran, businesses big and small gain complete control and ownership of their data. It’s easy to join data sources, perform agile analytics, and ultimately discover valuable insights using the business intelligence tools of your choice.

Fivetran expands sales operations to European Union, Middle East, Africa was originally published in Fivetran Blog | Ideas to Inform Your Data Strategy on Medium, where people are continuing the conversation by highlighting and responding to this story.

Case study takeaway: Fast data replication. Easy setup without ETL. Zero maintenance. Business intelligence focused. “Revolutionary.”

Sharethrough is the industry leader when it comes to supply side, native advertising platforms. The San Francisco-based company developed the native advertising concept. Its online advertising exchange is powering more than 12 billion native ad impressions per month. It has 170 employees scattered throughout Austin, Chicago, Detroit, Los Angeles, London, New York, San Francisco and Toronto. Sharethrough’s mission is to empower publishers to control their own destiny, and they do this by developing advertising products that are consistent with the user experience of a publisher’s site or app. Sharethrough’s lengthy roster of users — both publishers and advertisers — amounts to a Who’s Who of A-listers, including ConAgra, Forbes, Intel, Microsoft, Rolling Stone, Toshiba, VICE, and a laundry list of others.

Sharethrough’s advertising exchange generates a high volume, high frequency stream of event data, and its success depends on understanding this big data stream. However, these events cannot be understood without their business context. For example, a single event contains a customer ID but does not contain additional business context for that ID, such as customer name and customer configuration. Business context, required to understand the IDs and tags encoded in each event, is stored in Sharethrough’s advertising exchange back-end application databases.

Sharethrough uses the Fivetran secure data pipeline to make this business context available for analysis. Fivetran replicates Sharethrough’s back-end application contextual data, and pipes it into Sharethrough’s central data warehouse containing the high volume, big data event stream. With both event data and business context data available in its data warehouse, Sharethrough uses business intelligence (BI) tools and ad hoc queries to understand the performance of publisher and advertiser campaigns. Analytic insights are used both operationally and strategically to ensure success of Sharethrough and its customers. This would not be possible without the business context obtained through the Fivetran pipeline.

A simple start: replicate into a faster database

Initially, Sharethrough’s use of Fivetran was very simple: to replicate a legacy MySQL reporting database into an analytical database. The legacy MySQL database had grown and become too sluggish: Ad hoc analytic queries were too slow to be of any use. To work around MySQL analytic performance limitations, Sharethrough engineers wrote carefully tuned queries that were exposed to applications through a REST API. There was very little flexibility, and no real analysis.

Sharethrough started using Fivetran to replicate this legacy MySQL reporting database into Snowflake, a modern column-oriented data warehouse. Once the legacy reporting data was replicated into Snowflake using Fivetran, the data could be queried any which way, free of the query performance limitations of the source MySQL database platform.

This use case alone would have been sufficient justification for using Fivetran, and it was very easy to set up. For Dave Abercrombie, Sharethrough’s senior staff engineer, the Fivetran pipeline “just works.”

“There’s no labor. You set up Fivetran once, and you’re done. It works. It just works,” Abercrombie says. “There’s essentially zero engineering resources put to Fivetran maintenance.”

Join business context with high volume event data

Abercrombie described how, before Fivetran was fully integrated, Sharethrough analysts would need to sift through the ad exchange application metadata to find the IDs and tags relevant to an analysis. For example, to analyze a customer’s use of a particular product, the analyst would first search the back-end application metadata database for the particular ID and tag values to use for analysis.

“Then as a second step, we would have to take those IDs and tags to the event stream database and use those to filter our event stream,” he says. “It’s cumbersome to have to look into different databases and manually pull in different information.”

However, with the Fivetran pipeline in place, Abercrombie says:

“We can use SQL to directly join events with their metadata such as customer name and product. We use Fivetran to provide the business context data that allows us to make sense of the IDs and coding in the event stream.”

“Revolutionary” roll out to all sources of metadata

Once Fivetran had proven itself in these use cases, Sharethrough decided to use Fivetran to bring all of its many business context metadata sources into the Snowflake analytic database. These included Salesforce, as well as data in Google Sheets, and a handful of other application databases. In short, Abercrombie says, the Fivetran data pipeline connects Sharethrough’s data from its supported business applications into one data warehouse.

“Fivetran allows us to unify the many databases that we used to run on our system, bringing them into a single analytic database, so that we can ask questions on a full dataset rather than on a subset,” Abercrombie says. “This was kind of revolutionary.”

Jennifer Xia, a senior business analyst at Sharethrough, says Fivetran does the heavy lifting, freeing company analysts to focus on analyzing, and easily changing course when necessary.

“All the metadata we are able to collect now and see in one place would have been hard to unify without Fivetran,” Xia says. “Research would be slower and more difficult.”

What’s more, Xia says: “Our customer teams are able to zero in on problems early, allowing us to address them before they become big problems.”

Fueling business intelligence

Fivetran has simplified the ETL process for Sharethrough. Engineers do not need to work on moving data from one database to another. With Fivetran handling the back-end application metadata transfer, engineers can instead focus on transforming this business context metadata to make it suitable for BI tools, Abercrombie says.

Sharethrough has chosen MicroStrategy as its BI tool to query its data that Fivetran replicates into Snowflake for Sharethrough, Abercrombie says.

Business intelligence tools like MicroStrategy work their magic by slicing and dicing the aggregated facts and events along business “dimensions.” Robust and relevant dimensions are key to success, Abercrombie says.

“Application metadata is not usually ideal for BI in its raw form, and usually benefits from additional transformation to bring the business context to life, and to turn it into reliable dimensions. With Fivetran handling basic data transfer, Sharethrough engineers are free to focus on the subtle logic involved in turning raw application metadata into useful and safe BI dimensions,” Abercrombie says.

The pot of gold: “pivot or persevere”

Sharethrough is in a quickly changing industry, so new products and features are continually developed and tested. This is why one of Sharethrough’s core values is “action,” defined here as learning and continuously improving by doing, with a focus on decision making and learning.

Data analysis is obviously critical to this Sharethrough culture of “pivot or persevere.” From the perspective of raw data, experimental new products are most easily seen in the application metadata transferred by Fivetran into Sharethrough’s data warehouse of choice, Abercrombie says.

When a new features are developed, Fivetran will automatically start bringing the new data into the data warehouse. “With Fivetran gracefully handling basic database transfer, Sharethrough engineers can focus on transforming raw metadata of new features into usable analytic dimensions,” Abercrombie says. All in all, the data pipeline Fivetran provides for Sharethrough plays a “pivotal role” in reaching Sharethrough’s mission.

“We will be able to get metrics right away to know whether to pivot or persevere,” Abercrombie says. “We’re very experimental. To have the ability to expose very quickly new features coming through the Fivetran metadata, that’s my pot of gold at the end of the rainbow.”

About Fivetran: Our mission is to democratize data, to make companies data driven, and to give analysts easy access to disparate data sources to perform advanced analytics.

Fivetran builds zero-configuration, zero-maintenance and fully-managed cloud data pipelines for businesses big and small. With as little as a 5-minute setup, Fivetran replicates all your applications, databases, events and file stores into a high-performance data warehouse. Analysts query this centralized data with the business intelligence tools of their choice.

With Fivetran, businesses gain complete control and ownership of their data. It’s easy to join data sources, perform agile analytics, and ultimately discover valuable insights with Fivetran.

Freed from ETL, Sharethrough mining for “pot of gold” at end of Fivetran data pipeline was originally published in Fivetran Blog | Ideas to Inform Your Data Strategy on Medium, where people are continuing the conversation by highlighting and responding to this story.