How Big Ass Fans Reduced Time Spent on Impact Analysis by 80% with OCTOPAI
The Largest Manufacturer of High Volume, Low-Speed Fans Simplifies a Spaghetti Web of Data in Seconds with OCTOPAI
Big Ass Fans is a manufacturer of massive ceiling fans and lighting systems headquartered in Lexington, KY, with global offices in Australia, Canada, and Singapore. Their fans cool large spaces, such as factories and barns, by moving large volumes of air at a low speed.
Big Ass Fans came to Octopai with several needs, namely seeking ways to streamline its metadata workload, locate data sources and clear up redundancies and duplicates in business reporting. At the time, the company was also coming to grips with forthcoming migrations that posed to be a gigantic headache.
Digging up the data from its roots: Where is this data coming from?
Meet David, Senior Data Architect at Big Ass Fans. Business users ask David all the time, “Where did you get that data from?” In the past, this kind of question was almost always followed by sighs of annoyance from the rest of his business intelligence (BI) team, who were all too familiar with what finding the answer to this question entailed. Let’s just say it wasn’t a walk in the park.
Why not? Because tracing data back to its source is extremely difficult and tedious. Luckily, David and the team began using Octopai’s automated data lineage tool to map the data flow in seconds.
Am I seeing double?
Another issue Big Ass Fans’ BI team was dealing with was:
“Every once in a while, on Salesforce or our ERP, we’ll decide that we’re not going to use a field anymore. Then we’ll start using a different field.”
“So what happens? You’ll end up seeing 3-4 fields – essentially the same – but with different names, for instance, standard_cost, standard_cost_new, standard_cost_original. Obviously, this creates a lot of confusion.” David said.
Since bringing on Octopai for automated metadata management, any team member can conduct impact analysis quickly and easily whenever someone wants to make a change, like the cost example we just mentioned. Going forward, they can map any dependent objects and ETL processes that would be affected by the change, and reduce risk. Whew!
“…I can go into Octopai and see which jobs will be affected, then update and re-map them. And I can also find out which Power BI reports will get impacted.”
–David @ Big Ass Fans
Co-opting OCTOPAI for different types of users
The BI team was loving Octopai because it saved them tons of time, and when the developers heard about it, they wanted in too.
They wanted to start using Octopai on Power BI when creating dashboards or analyzing existing dashboards and their sources. However, they didn’t know anything about data lineage and transformation.
After just an hour of training and tinkering with the tool, the BI developers logged into Octopai and were able to locate everything they needed.
For a mind-boggling future migration
In the midst of considering a future transition, Big Ass Fans have been working with SSIS, SSRS, SSAS, Power BI. However, they want to eventually move their entire database to Snowflake and get a new ETL tool.
“This migration will be like doing a heart and lung transplant at the same time, and we want to ensure everything is compatible. We can make the moves easier with Octopai, knowing that our data will be cleaned up and make a smooth transition.”
–David @ Big Ass Fans
Simplifying boatloads of data and multiple systems with OCTOPAI
The BI team handles an enormous amount of data, and Octopai eases their jobs. The team saves time and headaches with the automated discovery and lineage capabilities that enable them visibility into the data flow that they never had before. This has spillover to the rest of the business, too.
So why did Big Ass Fans decide to work with Octopai as its metadata management partner?
There were 3 main reasons:
- Implementing changes pain free – Making changes manually, with all the streams of lineage and data discovery requests, could take the team hours, days and sometimes longer. Octopai automation saves tons of time and reduces risk.
- Migration – They’re in a decision-making process and cleanup phase prepping for the migration process. When they’re ready to migrate, Octopai supports their move.
- Root Cause Analysis – Finding the source of an error now requires no manual data mapping and is now completely automated with discovery and lineage.