Artificial Intelligence (AI)

Enterprises are entering a new era governed by data. The use of artificial intelligence (AI) in business intelligence (BI) is becoming a part of everyday business. As a result, the importance of AI has increased exponentially. Thus leading IT providers have gone beyond the creation of conventional software and have developed holistic platforms with the potential to largely automate business intelligence and analytical processes.

In the near future, business intelligence environments can therefore be expected to become the most important areas of application for AI technologies.

Thematically, AI and business intelligence are highly compatible. They adhere to the common philosophy of “data yields information, which leads to informed decisions.” In conjunction with innovative business dashboards, advances in predictive and prescriptive analytics will further revolutionise the use of business intelligence. Companies will be able to break free from the time-consuming process of sifting through data to uncover and forecast trends and proactively respond to costly problems. This saves time and resources and generates competitive insights.

In our highly networked world, every digital interaction – from a phone call to a card payment to every website visit – contributes to an ever-increasing flood of data. Even everyday objects such as refrigerators, cars or textiles constantly generate massive amounts of data. We are talking about Big data. But what should we do with all of this data, which in many places is swimming around in databases, or so-called data lakes?

With business intelligence or BI software such as QlikView, Qlik Sense, Microsoft PowerBI or Tableau, existing (i.e. historical) internal and external business data are interlinked, visually processed and rendered evaluable in an interactive manner. The knowledge thus gained offers companies clear starting points for the optimisation of business processes, product and service portfolios or customer relationships. However, BI users must be able to ask the right questions of BI systems and develop optimal KPIs (key performance indicators) or reports in order to derive the right conclusions for future-oriented measures from the evaluations.

At this point, in tandem with machine learning AI can go a decisive step further.

Artificial intelligence (AI) allows computers and machines to “think and act like humans”. AI-based software has therefore already introduced enormous changes to the business world. Even if the general future is unclear, AI-based BI tools are certainly indispensable for a competitive presence in the business of tomorrow.

Artificial intelligence and AI-powered BI systems can convert business data into real-time stories and reports. Dashboards alone will no longer suffice in the future. If, for example, data from x number of different sources flows into BI, AI-based systems help to individually adapt the knowledge to the needs of the company.

With AI-supported business intelligence, it is also possible to gain real-time insights and always ensure access to the latest data. In this way, despite the extremely high speed and rapid growth of data, strategic decisions can be made quickly and effectively. Business intelligence tools provide powerful dashboards using AI. These in turn provide the managers with business insights that they urgently need for their trend-setting decisions.

Data is growing at an unprecedented rate these days, which means that companies have a flood of data but cannot adequately exploit its benefits. AI-based BI software specifically helps to break this data down into manageable insights.

Machine learning, as part of AI, is the generation of new knowledge from experience in the form of data. An AI system learns from examples (e.g. historical data) and after a learning phase can generalise and apply them to new cases. For this purpose, algorithms build a statistical model based on training data. These algorithms recognise patterns and regularities in the training data and apply them later, for example to predict forecasts.