Big Data

Data Mining Trends

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We often talk about how the field of data analysis and machine learning is constantly evolving. To succeed, you need to keep up with new trends.

Tableau Software has published a list of 10 global trends in business intelligence for 2022. What awaits us?

1. Interpretable Artificial Intelligence

Companies understand the value of artificial intelligence and machine learning, but require openness and transparency. People want to be sure they can rely on AI findings. They want to understand the algorithms of work and the logic of decisions. A balance is needed: AI and machine learning – only under the guidance of a human.

2. Practical analytics

To save time, data should be placed where it interacts with. Anyone who works with data should have access to it. Analytics is gradually becoming a part of all business processes.

3. Ethics and data

Public and private companies endeavor to regulate the use of personal data. Governments are tightening digital ethics and privacy laws, and consumers are closely monitoring the use of personal information. Companies that do not pay attention to privacy risk losing customers.

4. Data collaboration

More and more companies are agreeing on cooperation in the field of data. This helps them to achieve their goals faster and more efficiently. Commercial companies often partner with research centers and non-profit organizations.

5. Natural Language

People need to communicate with data in natural language to make analytics more accessible. Language is used to support analytic conversation. An analytic conversation is a conversation between a person and a system about their data. When data can be acted upon as a human being, the data analysis process is greatly accelerated and gains new quality.

6. Smart BI platforms

BI platforms have become available and are used by many companies. BI platforms are a business analysis tool that allows project participants to analyze live data and create visual reports.

7. Data storytelling

Numbers, graphs and charts are no longer enough to report analysts. The result of the data analysis should tell you why the data is exactly the same and what to do with it next.

8. Greater focus on employee interactions

Data needs more than just analysis and reporting. On their basis, specific solutions to business problems should be developed. You need a well-built communication system for analysts and employees who will use the results of data mining in practice.

9. Soft skills of data analysts

Soft skills are now important in any field, data analysis is no exception. Data analysts are increasingly required to understand the company’s industry, to be able to explain simply and clearly, and to communicate.

10. Analytics in the cloud

All analytics are gradually moving to cloud storage. It’s fast, convenient and accessible from any device.