The problem with specialized business intelligence software is that it stands like an airplane – and is only needed when you have a large, large company with the appropriate amount of data at your side. In general, now there are not so many specialists on the market who have tested such systems, have experience working with them and can plainly say what it is, why it is needed and what it will give after implementation.

The first and main application of business intelligence is to be able to build arbitrary reports head-on while heads of departments or members of the board of directors are conferring. One of my favorite examples is from which plant to supply vodka to stores: from a distant one (expensive logistics and 2 weeks on the road), but cheap in terms of production cost, or from the nearest (1 day), but expensive?

It is clear that you can dig deeper and answer in a week. But more often you need faster modeling and not hundreds of disparate reports, but a unified environment where a financial specialist can simply take and receive the necessary data without involving the entire IT department. There are also specific tasks that these and related systems solve.

We are not talking about specific solutions, but about what an enterprise can get from the implementation of Business Intelligence and related systems. It is clear that when data begins to be collected and analyzed, it is logical to use it in many places. The first main question is data collection, the second is the methodology of what to do with this data in general. Let’s start to figure it out.

The first is the preparation of reports. Everything is quite simple here: BI acts as a single data repository for all subsystems and knows how to combine them, process them in dependencies and produce results.

The second task is to process data and cut regular reports for all divisions of the company. From the most unusual thing – we used a BI system in order to receive data from population censuses, toss them, supplement, restore, build hypotheses, check, process and cut thousands of reports for all regions, cities and villages.

The third challenge is to speed up processing. Previously, the report was made once a month, and now in real time (this is a very, very critical difference for many areas of business).

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Roughly speaking, there is data, and there is a methodology for evaluating this data. And the model of the relationship of various components with each other.

We collect the actual data values ​​using classic Business Intelligence systems. For many, this is where BI ends – it is often a trivial problem to combine supply and production, because they are made in different places and systems.

Further, the data is driven into the model of the enterprise. The classical methodology – the same BSC – was created back in 1987, and has not changed much since then. In a sense, updates and forks are in stock, but the principle is the same everywhere. In short, the activities of the company can be decomposed into 4 components: the financial part, the client part, personnel and reserves (that is, personnel) and the development strategy. Even state-owned enterprises are assessed in the same way, only instead of profits they get into the given budget.

The beauty is in the detail. The fact is that when the company is watched by auditors or when something is discussed at the board of directors, a maximum of 20 aggregated indicators such as net revenue, turnover, etc. are usually assessed. It is these indicators that go to shareholders in reports and it is on them that recommendations are made. To evaluate not on feelings – but for yourself every day indicators in the form of numbers.

And BI allows you to take a report and not just get the “total” line, as is usually done, but see what each indicator is composed of. And then – to fasten a variety of things to the model, which are recalculated almost in real time.

The indicators cascade to people – and the motivation system is turned on. For example, if the shareholders decide that after 3 years the profit should be 20% more, then it is easy to build state A and state B. And a model of transition in 3 years from state A to the desired B. At the end of the year (quarter, day) you can see operating indicators and understand whether you are digging there or not. The metric model can decompose the entire transition process and there will be a strategic map of how to change. Each leader will have a plan to do.

Once again: there is a strategy in which it is specified at the macro level what to do. And there is the automation of operational activities – and we can work with it too.

If the Gann line is directed upwards, then we have a growing trend. If the price is below the Gann line, it means that the market is downtrend and you need to place sell positions. And vice versa. In places where the price breaks the Gann line, a change in the market trend can be expected.

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BI technologies offer a current (real-time), historical and predictive view of internally structured data across all departments in an organization, which exponentially improves understanding of operations and improves decision making.

Simply put: Business Intelligence is the process of identifying valuable trends or patterns in your data to make more effective and accurate decisions related to the goals, objectives and strategies of your business.

Since pattern recognition is a critical part of BI, AI in business intelligence plays a key role in this process. When done right, pattern recognition is one of the key features that differentiates BI experts from BI enthusiasts. By helping users find holistic ideas on their own, AI technologies are enormously helpful in pattern recognition, making the process more intuitive, more streamlined, and ultimately more accurate.

Many business intelligence concepts are implemented through intuitive, interactive tools and dashboards – a centralized space that allows you to easily dig into your data. But more on that later.

Next, let’s look at how the concepts of business intelligence relate to the inner workings of the human brain.

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