Using BI Tools to Optimize Company Data

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Estimated reading time: 11 minute(s)

bi tools

Any organization is right to question the necessity of capital expenditures. After all, it’s essential to keep costs under control if you want to have a profitable bottom line. When viewed this way, it makes sense for stakeholders to be skeptical of spending money on new platforms or tools. At the same time, however, companies need BI in order to adequately compete in the modern economy. Using BI tools to optimize company data is one of the most essential pieces for running a successful business today.

While the previous statement might come off as a bit of an over-exaggeration, it’s really not. Before you start looking at specific BI tools for you business, you need to understand why adopting them is so important. These are some of the tops ways BI can help you optimize company data, and use it more productively:

  • Make better decisions in less time
  • Get an idea of overarching trends you wouldn’t see otherwise
  • Cut down on operational inefficiencies
  • Boost data security

As you can see, these are all some of the top priorities of enterprises. Optimizing data is so powerful because it’s a process that keeps raising your organization’s potential. So, what are some of the kinds of tools businesses should consider when looking to optimize their data?

Embedded Analytics

When thinking about modern BI tools, embedded analytics is one that has to be included in the conversation. Data analysis doesn’t just happen in one place. Furthermore, the results are by far the most useful when they can be brought to a location more convenient for users than the analytics platform itself.

Embedded analytics provides a way for users to get great data analysis, and then share it wherever it makes most sense. This can mean setting up a real-time visualization in a user’s dashboard that must be created in a more advanced BI program. In this instance, embedded analytics allows for employees to get far more detailed, continually updated information that’s tailored just for their role.

Additionally, embedded analytics can be used to pull data analysis into specialized reports, presentations, or other materials. This can make presenting new information to executives or clients much easier, while also improving comprehension.

AI-Powered BI

Many of the most advanced business intelligence tools today incorporate artificial intelligence in some form. While things aren’t quite at a 2001: A Space Odyssey level yet, it’s not an exaggeration to say AI-powered BI can literally guide you through the query process.

Artificial intelligence is playing a critical role in the development and usage of new BI tools in a few ways. Here are some of the top reasons you should consider BI that’s powered by AI:

  • You can get answers in much less time, as AI-driven platforms can search through data much more efficiently than less advanced ones.
  • AI can give personalized query recommendations based on past searches. This can lead users to epiphanies that they might not have been able to discover on their own.
  • With AI-powered BI, more users than ever are able to extract value from data.
  • Tools that use AI can provide real-time analytics, which is extremely powerful for enterprises that need to make fast decisions based on continuous inputs.

Self-Service Analytics

One of the most crucial aspects of the previous section was how AI can bring data and BI to more people. This phenomena is also known as data democratization, and is being powered by self-service analytics tools.

The term “self-service” means layman users can derive insights without having to send everything off to an analyst. This drastically cuts down the time between beginning a query and making a decision. Relational search is one type of self-service analytics that is particularly powerful. It’s immensely functional because it works the same way as searching for something in a search engine. Users can simply type in queries and receive an immediate result.

Tools like the ones mentioned are radically changing how BI can make company data more efficient. It’s wise to investigate how some of these can be fit into your own organization’s BI arsenal.