Harnessing AI for Smarter Business Decisions: 4 Types of Data Analysis

The role of artificial intelligence in decision-making processes.

4 types of data analysis.
How can you harness the power of artificial intelligence to make your business decisions based on detailed data and even more relevant? We’ll take a look at the types of data analysis and how they can be supported by AI, as well as the tools that will revolutionize the way you view data.

Data analysis

4 types of data analysis supported by AI
The most important types of data analysis that artificial intelligence can support are:

Descriptive analysis – also known as descriptive analysis, is the simplest form of analytics. It involves collecting and organizing historical data, i.e. on what has already happened in the company. It usually does not need to use artificial intelligence. AI is used only when very large amounts of data are being analyzed, or when analysts expect artificial intelligence to uncover new patterns that have not been studied before.
Augmented analytics – is a tool that supports analysts in tasks such as compiling data for analysis or visualizing results through various charts, tables and presentations. Based on the AI-prepared data, an analyst can more easily conclude the collected material without the help of a team to input and classify information. One can help here with the free ChatGPT tool, or use freemium options such as Visme or Datawrapper.

Predictive analytics – focuses on finding patterns in existing data so that more accurate decisions can be made based on it and potential risks can be identified. Artificial intelligence uses statistical modeling, machine learning (ML, Machine Learning), and Data Mining techniques to predict future events.
Prescriptive analytics – otherwise known as prescriptive analytics, like all the above collects data on past situations. However, its purpose is the most complex, and its operation is the most dependent on artificial intelligence. This is because it is about indicating the best behavior in a given business situation.

4 decision making areas supported by AI
Artificial intelligence is used for both simple but labor-intensive data analysis decisions and those that require handling large data sets. These include:

Entering documents into databases – even in situations where they are delivered to the company in paper form or contain incomplete or poorly structured data, AI can accurately organize the information and decide which collection the document belongs to,
answering questions asked in natural language – decision-making makes artificial intelligence able to accurately respond to questions asked, and take the initiative by asking follow-up questions,
Business process management – in the case of incomplete data, AI can decide to move on to one of the cliques of alternative next steps included in the process map
Process automation – the action of artificial intelligence enables the automation of workflows between the various programs serving the company.