Business Intelligence Software

What is business intelligence software? 

Business intelligence is software that tracks, analyzes, and visualizes all of a business’s data. These tools can connect to many types of software, including spreadsheets, accounting tools, ERP systems, CRMs such as Salesforce, and marketing automation tools. BI software then can take the data from all the services that they monitor, and put it all in one place.

A typical business dashboard in Domo.

As businesses get larger and integrate software with more of their operation, they start to collect massive amounts of data. Less-complicated statistical analysis tools like Microsoft Excel may not be able to handle such large data sets, especially as the size grows to the millions and often billions of rows. In addition, sifting through all this data takes time and requires the experience of data professionals.

With BI software, much of this process can be automated or streamlined. Most BI tools are designed to be simple, intuitive, and user-friendly; the average business user can use them without wasting too much time or experiencing too many headaches.

What features should I look for in business intelligence software?

It’s important to ensure the BI tool a business selects will actually work for the tasks they need it for. Trying to use a BI tool that’s a bad fit for a use case can be more disruptive than having no BI tool at all. With that said, here are a few features that are common among BI tools.

Data analytics allow businesses to replace bloated, poorly optimized Excel spreadsheets with clean, fast, intuitive tools. Anything that an Excel spreadsheet can do, a BI tool can do faster and simpler. These tools can also be automated. Most BI software can do things like KPIs, scorecarding, budgeting and forecasting, benchmarking, and data cleansing.

Reporting and dashboarding allow businesses to see data trends in real time. BI tools can present data in real time, while analog tools often result in delays. These tools can also connect data across an organization much faster than other tools. For example, a sales team can see and react to warehouse issues in real time, so that they don't oversell products. 

A feature that makes BI dashboarding possible is ETL (extract, transform, and load). This is the industry term for the process BI tools use to extract data from source systems, transform it into a consistent format, and load it into the BI system.

Domo's Magic ETL tool for loading information into a BI system. 

Data visualizations allow users to generate charts, graphs, and tables that represent their data visually. Most people struggle to derive insights from data unless it’s presented in a visual way. With data visualization tools, it’s much easier for the average person to find insights in a data set.

BI tools can also act as a data warehouse or a central repository for all the data used by the business. Organizations can keep their data safe within their BI tool instead of storing it in dozens of different systems and spreadsheets. When a user needs a specific data set, they can get it directly from the BI tool instead of looking for it in three separate tools used by five different departments. This data lives on the cloud, which makes it widely available, easily accesible, and infinitely scalable. 

There are some features that robust BI systems usually have but smaller tools may lack. If it's important to your business that your BI tool offers one of these features, double-check that the tool actually has the feature before you buy it.

Predictive analysis allows businesses to use their current data set to predict future trends. This function is becoming more important as organizations rely more on data to drive business decisions. This feature can be used to predict almost any future data set, from projected revenue to expected employee turnover.

Semantic analysis allows organizations to apply their data analysis tools to large quantities of text. For companies that collect a lot of text, this feature is very useful. It can be used to find trends and draw out insights just like regular data analysis tools. Some BI tools can even scrape social media sites for mentions of a brand or product and generate insights based on that data.

Profitability analysis allows businesses to forecast how a potential change or issue could affect revenue. Using predictive models, organizations can learn the expected results of changes before they put them in action.

OLAP (online analytical processing) allows for more advanced relational analysis than traditional statistical models. Leveraging the power of cloud-based systems, OLAP systems can help data experts analyze many different data dimensions at once. Users can see how different statistics relate to each other, view data from a specific viewpoint (called a ‘data slice’), and drill down to even the smallest classifications.

How complex is business intelligence software?

Businesses can select BI software that’s as simple or as complex as they need it to be. Many tools focus on user-friendliness, providing an experience that’s easy to understand for those without much technical expertise. Other tools expect the user to involve themself with the process a bit more. These tools often expect their users to have some knowledge of the coding language that the software is built on.

All BI tools need some sort of code bridge to allow them to communicate with other pieces of software. These code bridges are called Integrations. Businesses need to do some research into the integrations offered by each tool. Many BI tools offer native integrations with common business software. This means the code bridges are built right into the software; very little work is required on the user’s end.

A Jira integration in Power BI.

However, not all BI software carries native integrations for every other piece of software. In those cases, additional work will need to be done to allow the two tools to communicate. Sometimes, there are additional tools available that can build these code bridges, but other times, integration is impossible without having a development team write a code-based solution.

It’s very important to look for software that integrates well with the tools you already use. Poor integration can lead to data getting lost or trapped, resulting in  inefficiency down the line.