How to overcome complexity to deliver effective BI

Modern business intelligence has moved on from the days of painstaking connections; integration is now faster, easier, and more scalable than ever—with benefits for every single user in the business.

Organizations large and small, and industries as different from one another as retail and healthcare, have similar problems when it comes to data: there’s a lot of it, it’s everywhere, and you’ve got to figure out how to connect to, organize, transform, and democratize it across the entire enterprise.

For data teams, these things involve considerable complexity, and many feel they are wasting time figuring out the “how” rather than focusing on the “what,” which involves exploring data to uncover new value for the business. It’s this problem that modern BI addresses.

Modern BI takes a more end-to-end approach to business intelligence. It focuses on managing the entire data pipeline, from connecting it, to building out a data lake or data warehouse, to sharing data in a way that is easy for regular business users to understand and use.

It all starts with connecting data. Many organizations have many disparate systems. They might have a data warehouse or even a data lake that centralizes a lot of the data. But this is often incomplete.

The first step is making integration easier. Domo, for example, uses more than 1,000 pre-built integrations  to let data professionals easily connect new data sources through ready-to-use APIs. This can vastly improve the speed and scale at which new data projects can be built and utilized.

Once data has been connected, it’s important to organize it. This can be done through things like dataset types, dataset tags, and customizable schemas, which make it easier for users to find data and use it. Domo does this using QuickStart apps and data governance sets that can tell you all about your datasets, including update history.

Things really heat up for the business in step three: data transformation, which involves combining various data types, such as Salesforce data with, say, ERP data and marketing campaign data. This lets the business start to cross-reference and see things it hasn’t seen before.

In a traditional business intelligence model, this would be wildly complex and involve hours of time. But the modern BI approach—utilizing a single data platform layer—simplifies the process. This lets you use tools such as Magic ETL to effectively drag-and-drop data transformation components, as well as dataset views to explore data and perform simple operations.

The final step—and possibly the most important—is data democratization. This is where data is made accessible to everyone in the organization so they can build their own content and dashboards.

For data professionals, this equates to “teaching a man to fish.” It can save valuable time and resources in the long-term, with governance in place to protect data quality from day one.

With these points addressed, data can be worked and manipulated at much greater speed and scale, allowing data teams to focus more on innovation, making and breaking, and less on simple data delivery.

The difference can create immediate and impressive impact; we saw one of our customers, CTI Foods, connect to more than two dozen different data sources with hundreds of datasets in just a few weeks. If they wanted to, they could’ve even scaled to trillions of rows of data.

“Domo is a complete integrated solution coming from your source system all the way down to your production environment,” said Joshua Stan, CTI Foods’ VP of IT. “And the best part about it is you don’t have to be an IT person or know any programming languages to make it work for you. With Domo, anyone in the organization can be a data hero.”

To learn more about Domo’s data integration capabilities, click here. To see how Magic ETL helped Traeger Grills grow its business, go here.

Next up

What do you really need from your modern business intelligence solution? Find out in the Dresner Vendor Insights 2021 report.