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5 Business Intelligence trends you need to be prepared for

Business value in data is nowadays recognized by many companies. This directly translates into a growing demand for BI specialists and professional tools that facilitate data processing, analysis and visualization. Which direction is Business Intelligence heading towards?

5 Business Intelligence trends you shouldn’t ignore

Business Intelligence or Big Data teams have become permanently established in the organizational structures of many companies, and the business value hidden in the data available in the company is now recognized by almost every entrepreneur. Therefore, no one is surprised by investing in experienced experts in data analysis or visualization, as well as in modern programs and analytical platforms that enable automation of analytical processes and take them to a completely new level. What trends dominate the Business Intelligence industry today?

The world of BI has long been moving towards democratization of data access and maximum simplification of the various stages of data cleansing, analysis and visualization. All this is to enable end users, namely the management, maximum flexibility and adaptability to their needs.

For what changes should you prepare your business?

There are many new and continued trends in the area of Business Intelligence, but the most important ones, according to DS Stream, include:

1. Augmented Analytics

The concept appeared already in 2017, but it is still a strong trend for which it is worthwhile to properly prepare your business. The idea is very simple and aims to democratize access to the data and business values that are contained in them. How? Among other things by means of machine learning or natural language processing, which effectively automate analytical processes and at least partially exclude data specialists from them. As a result, decision-makers in the company are no longer so dependent on analysts and can easily acquire and analyze the necessary data themselves in order to make decisions even faster and stay one step ahead of the competition.

2. Embedded Analytics

Embedded analytics are indispensable for achieving profitable growth faster. We are talking about technologies and solutions that also aim to democratize access to data and analysis results – not only from the perspective of end users but also from the perspective of other applications. Interactive dashboards, giving the end user (not only the management) a lot of freedom to aggregate or filter data, are in their hands an extremely powerful tool. They not only support the decisions made by managers, but also optimize processes, identify problems and take appropriate corrective measures in almost real time. In addition, they also reduce the workload on analysis teams, which can use the time saved to work on more advanced analysis or continuous improvement of existing platforms.

3. Data Storytelling

Collecting and cleansing data as well as creating a precise model are undoubtedly important and very time-consuming, but all these activities are undertaken for one purpose – to verify a specific hypothesis and on its basis formulate appropriate conclusions for business. It is therefore necessary not only to answer the question of what happened or may happen, but also to explain why. Modern BI platforms enable storytelling with data and guide the end user through the whole analytical path – starting from a big picture and gradually moving to more granular data, thus presenting the reasons for the observed phenomenon (e.g. decrease in sales of a specific product category in the analyzed region).

4. Process Automation

Data analysis, although it requires a lot of knowledge and technical competence, also includes a number of repetitive and unfortunately very time-consuming tasks. Thanks to the use of modern technologies, including tools for process automation, many of these tasks can already be completely eliminated and thus free up resources in analytical teams, thanks to which they will be able to focus on key stages of the entire process – i.e. searching for specific business problems, formulating appropriate hypotheses and drawing conclusions from conducted analyses, which will effectively support management decisions.

5. Artificial Intelligence

In the context of trends, it is also worth mentioning the further increase in importance and level of use of artificial intelligence in the world of Business Intelligence. We are talking about using AI and ML in the process of preparing data for analysis or creating predictive models.

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