Software shop finds Tableau, Snowflake, Fivetran combo 'a million times better'
Learn how Inverse-Square adopted integrated, automated analytics
“One of the big selling points for our custom application-development services is that we can eliminate manual reporting for our customers," says Business Analyst Patrick Laskowski of Inverse-Square. The software firm, founded in 2011, has now reached a critical size where they too can leverage the industry best practices they often recommend to their clients. Rather than manual reporting in Excel, Inverse-Square adopted a modern data stack consisting of Tableau, Snowflake, and Fivetran for their own internal analytics.
“Inverse-Square builds customized, unique software applications—for equally unique customers, who can’t find ‘that thing.’” (Patrick Laskowski, business analyst, Inverse-Square)
Before the Tableau/Snowflake/Fivetran combination, Inverse-Square had been running its reports in Excel—which required manually importing its LiquidPlanner customer-project files, along with QuickBooks Online data, into “constantly changing” spreadsheet models. A time-consuming process that made trend-analysis incredibly time consuming.
“Fivetran just does our job for us, and we can do more with less,” Laskowski says. At the same time, the Tableau analytics platform has replaced and outpaced Excel at Inverse-Square. In essence, the company came to achieve more with a centralized, automated data stack than its previous process of one-off reporting. Laskowski is able to take advantage of Fivetran automation to easily "update our Quickbooks tables in Snowflake. Then, using Tableau, generate reports to track revenue, profit over time, etc.” Beyond that, by centralizing their data sources into Snowflake, "I can combine LiquidPlanner customer information and QuickBooks together...two data sources that previously didn’t join easily.”
"Building custom software is like building custom vehicles. You've got bicycles, and you've got spaceships."
Located in Indianapolis, Inverse-Square is a custom-software firm that develops applications for clients that can’t find software solutions out in the open market which can meet their highly specific requirements. Perhaps not surprisingly, says Business Analyst Laskowski, “Every single system that we have is brand new, and a unique challenge in its own right.”
Building unique software solutions that range from the simple "bicycles" to complex "spaceships," Inverse-Square is primarily a Microsoft shop, relying heavily on the .NET platform. One example project is a marketing-operations system for a “huge medical-devices company. The system runs 24 hours a day and serves markets worldwide.” Another major Inverse-Square application runs “probably thirty-million dollars of show cattle” through an auction system. The customer is about to celebrate its “fifth big fall season” using the custom cattle-auction application.
Challenges: Manual and time-consuming. Limited analytical scope. No trend-analysis.
Prior to implementing Fivetran cloud data pipelines to link its separate financial and customer-project data sources to a Snowflake warehouse, Inverse-Square was producing all their management reporting in Excel. Although Excel is highly flexible, the tool provides few automations.
When fresh data became available, the old process required exporting QuickBooks Online data, along with LiquidPlanner project-management files, and importing those data streams into Excel. Most reports would then need to be recreated—resulting in lost employee time and reduced Operations team productivity. Additionally, the standalone reporting capabilities of QuickBooks were limited and ultimately unable to provide the analytical scope which Laskowski and management had come to require. There was no practical way, for example, to create and run saved queries which could link internal financial data in QuickBooks with “external” customer-project information in LiquidPlanner.
Last, but, by no means least, was the aforementioned Excel “flexibility” problem, which kept rearing its head at Inverse-Square: “All that flexibility with Excel meant that we rarely looked at the same chart for more than a month or two at a time,” Laskowski says. “Then we’d start over and look at something new.” In short, the lack of automation and predefined views meant that trend-analysis was not possible. So that, in effect, “there was no way to reward people for their good behaviors or to grow from any errors.”
The solution: Automatic replication. Fast and accurate. Spanning all data sources.
After no more than a five-minute setup, Fivetran was able to replicate all of Inverse-Square’s application data into the columnar Snowflake cloud warehouse, and then move their analytics layer into Tableau. The Fivetran cloud pipelines are zero configuration, zero-maintenance, and 100% managed.
Fivetran core concepts: Inverse-Square called upon Fivetran to solve its data analytics challenges by reaching out to their financial and project-management systems to grab relevant QuickBooks and LiquidPlanner data—at the schema or table level, depending on the integration. Each Fivetran integration has a different way of connecting schemas and tables. Learn more about core concepts >>
“Previously, data and visualizations were always changing” since Operations had a practice of holding onto its former Excel spreadsheet-report models for no more than one to two months at a time. But, now that Fivetran has centralized LiquidPlanner and QuickBooks data in Snowflake, “we can leave these things in place,” Laskowski says.
Webinar: Why use Fivetran to connect your data sources to Snowflake? Find out how and why rapid-development platform Outsystems chose Fivetran to connect its cloud data sources to the Snowflake warehouse. So that the company could take advantage of integrated analytics to enhance business decision-making—by using up-to-date information refreshed automatically from all its data sources. Watch the webinar
Before Fivetran, Inverse-Square Operations had to regularly export LiquidPlanner and QuickBooks Online data and import it into Excel for reporting purposes. Now, after Fivetran, the data replication process is automatic. And fast. So that, today, Laskowski can use the power of Tableau analytics to query predefined views of consolidated data, in the high-performance columnar Snowflake warehouse, to review trends, reduce costs, and seek out new revenue opportunities with customers.
Using Fivetran, you can sync data into cloud warehouses as frequently as every five minutes. But, since Inverse-Square bills clients monthly, having no need for real-time updates, the company’s QuickBooks tables replicate each night, automatically, in Snowflake, together with the LiquidPlanner project files.
I think the biggest benefits of using Fivetran are to put the data “somewhere else” [in the data warehouse]. We love that we can keep our clients working “over here”...and then, when we want a report, they’ve got up-to-yesterday’s data in Tableau: accurate, but very quick. And not slowing down. I love that.”
“Now I can use Tableau analytics, having grabbed all my data, and I can create the appropriate views in Snowflake to generate reports showing revenue, profit-over-time...We can do more things, more than was possible with just the QuickBooks reporting.” Laskowski is quick to point out the performance superiority of querying QuickBooks tables after they have been replicated by Fivetran into Snowflake—compared to querying QuickBooks directly. The Tableau, Snowflake, and Fivetran combination is “a million times better,” he says. It’s “incredibly valuable.”
Fivetran enables you to make data-backed decisions—by giving your analysts easy access to disparate data sources. So they can perform advanced analytics. How? Fivetran replicates all your application, database, event, and file-storage data into your high-performance cloud warehouse—after no more than a five-minute setup. What’s the Fivetran difference? Fivetran cloud data pipelines are zero-configuration. Zero-maintenance. And 100% Fivetran-managed.
Snowflake’s mission is to enable every organization to be data-driven with instant elasticity, secure data sharing and per-second pricing, across multiple clouds. Snowflake combines the power of data warehousing, the flexibility of big data platforms and the elasticity of the cloud at a fraction of the cost of traditional solutions.
Tableau products transform the way people use data to solve problems, making analysis fast and easy, beautiful and useful. In 2020 the world will generate 50 times the amount of data as in 2011. And 75 times the number of information sources. Within these data are huge opportunities for human advancement. But, to turn opportunities into reality, people need the power of data at their fingertips. Tableau is building software to deliver exactly that.