Data Analytics: What is it and how does it work?

Data Analytics is the process of collecting, processing, analyzing, and interpreting detailed information from data. This process has many aspects and approaches and is widely applied in industries, from business, and science to social science fields.

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What is Data Analytics?

Data Analytics is a process that spans collecting, processing, analyzing, and interpreting detailed information from data. Accordingly, the biggest goal of this work is to convert raw data into the most understandable and intuitive information.

Because of the above characteristics, this is a job that has great applications and importance for businesses in optimizing and minimizing investment risks. At present, this work is more important than ever because of the rapid change and development of the market.

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How many types of Data Analytics are there?

Data Analytics is a job that specializes in analyzing raw data and turning it into understandable information. From here we can divide this work into 4 main levels including:

Descriptive analytics

It is the process of analyzing data information that has taken place in the past over a certain period depending on the scope of analysis.

Collecting this data is aimed at providing comparative and aggregated results for investment planning as well as limiting risks that have appeared in the past.

Diagnostic analytics

Is the process of analyzing data by asking problems and asking why about developments that have occurred in the past. From here we can use past data to analyze and give the most accurate answers to the questions posed previously.

In other words, it is through this process that we can drill down into the details to find the causes of past problems.

Predictive analytics

Is the process of analyzing data based on the results of descriptive and diagnostic analysis to help detect future trends. In the simplest terms, this process is a specialized tool for prediction.

Besides the value it can bring, predictive analytics is just an estimate, the accuracy depends greatly on many different factors.

Prescriptive analytics

This is the highest level and is also considered the most difficult in Data Analytics work because it requires taking appropriate actions and predicting possible future results. In simple terms, in prescriptive analytics, you need to answer the question of what should happen and how to make it happen.

Although difficult, this stage is very important in determining the next direction of an entire business and is a level that big CEOs like Michael Saylo, Jamie Dimon,… have a clear grasp of.

How does Data Analytics work?

Because of its complex nature, Data Analytics work also requires operating according to a specific process as follows:

• Identify data: With raw data having a very large amount, the first step needs to be selected and grouped according to a certain standard, as a direction for data collection to be more effective.
• Data collection: Based on the previous selection and grouping criteria, collect relevant data from all possible sources.
• Organizing data: After data collection is complete, this data will be separated and reorganized into groups for analysis.
• Check data: The nature of the collected data is still raw data, so it needs to be checked and erroneous data removed.
• Data Analytics: The main process of analyzing data at 4 main levels including descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics

What benefits does Data Analytics bring?

As mentioned before, Data Analytics brings many benefits to businesses because it is the most effective tool to:

• Businesses optimize strategic decisions.
• Helps businesses better understand customers and their needs.
• Increase marketing efficiency and optimize costs for businesses.

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Conclusion

Finally, together we have learned all the most detailed and easy-to-understand information about the concept of Data Analytics. Thank you for taking the time to follow and see you again in other content from AZcoin.