What is the relationship between Data Analytics, BI and Machine Learning?

Organizations have always had the need to collect data, process it and generate utility from it. In short, they do Data Analytics. The problem is that, with digital transformation, unimaginable amounts of data are now being handled, so taking advantage of it is no longer as easy as before.

Therefore, benefits of business intelligence and machine learning are so sought after to exploit high volumes of data in less time, especially if you take into account that the 60% of employees need hours and even days to make a decision based on the data collected.

Now, there are also organizations that have technology that allows them process and analyze data in seconds. If you want your organization to be part of that group of companies, start by taking a look at what is machine learning, analysis of data and business intelligence, and what is the relationship between them.

What is Data Analytics

It is a process where large amounts of data are cleaned, transformed and modeled to discover useful information for business decision making. Currently it is also known as big data analytics.

It works in a similar way to everyday life: you choose the path to take and the departure time to get to work at the scheduled time. It is not random, but the result of an analysis of factors such as distance, route, previous experiences, etc.

The same thing happens within an organization. To make a decision, you need to obtain valid internal and external data, which can be:

  • Structured: They usually come from databases and are easily accessible (CRM, ERP ...).
  • Semi-structured: It is easily accessible data, but it needs more preparation and can come from social networks, sensors, mobile devices, among other sources.
  • Unstructured: They come in the form of phone calls, pictures, videos, or emails.

This data is constantly stored in a lake of data through the batch load (periodic charges) or in streaming (in real time), so that you can always make decisions based on updated information.

In this way, the big data analytics takes all the internal and external data that affect the reality of a company, accommodates them, categorizes them and turns them into useful data so that they can then be used in processes of machine learning or business intelligence (BI).

What is Machine Learning

After the data analytics has fulfilled its function, the machine learning or machine learning to provide a deeper, faster and more complete vision of reality.

Here "trained" algorithms are used to identify patterns and useful characteristics in decision making, and to make predictions on new data. The better the algorithm, the more accurate the decisions and predictions will be, so that the company can anticipate risk factors, make better purchase choices, etc.

Business intelligence: a complementary step

The business intelligence or BI take advantage of the data lake to transform data into practical information. Thus, it can serve as a basis for formulating business strategies.

The tools of Business Intelligence present analytical results in the form of summaries, dashboards, reports, graphs, tables and maps to provide detailed information on the state of the business.

So what do Data Analytics, BI, and Machine Learning have to do with it?

Data Analytics is the first step to take advantage of Business Intelligence benefits and the Machine Learning; In other words, the discipline of data analysis encompasses that of business intelligence and machine learning.

Likewise, the most explicit relationship between these three concepts is that they all represent material to improve the business, based on the patterns and other dynamics that the data reveals.

Although both business intelligence and machine learning have to do with massive data analysis, they do so from different flanks and technologies:

Business Intelligence Machine Learning
Mathematical methods are used to analyze the data. The software teaches itself to analyze the data.
Helps identify business opportunities and guide strategies. It uses intelligent decision-making systems previously programmed.
Convert raw information into useful information for the company. Use data mining to develop predictive models.
It does not depend so much on the algorithms of the software as on the skills of the analyst. It depends a lot on the algorithms, especially the initial ones.

In this scenario, the cloud computing It is also playing a fundamental role, allowing the use of all these solutions from the cloud, accessible at all times and in a secure way. By completing the process in its entirety, your company will be able to access reliable and current information in seconds.

In Codster, You will find the technological solutions and services you need to take advantage of the benefits of data analysis, machine learning and business intelligence.

Alejandra Correa

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