Data analytics is the process of analyzing your business information to find valuable insights for your operations.
In practice, when we talk about data analysis, it is common for people to think of complicated formulas, text files, and spreadsheets that are difficult to understand.
Well, let's not deny it: there is something like that in data analysis, but today it is a much simpler process than before.
That's why it's so essential for today's businesses, especially in an era where digital transformation and big data offer so much.
In this article, we will explain what data analysis is, starting with the concept and importance of data for an organization, including in which sectors it can be applied. Shall we go there?
What is data analytics? How does it work?
Data analytics or simply “data analytics” refers to the uk whatsapp data process of examining data sets in search of conclusions about the information contained within them, such as patterns, opportunities, and even strategic gaps that can be exploited by the company.
Nowadays, this is a very popular process, based on the use of advanced tools to capture, store and process data.
Data analytics is one of the most important processes within Business Intelligence , a set of processes that aim to take advantage of a company's data to improve and optimize its decision-making and organizational performance.
What are the advantages of implementing data analytics in organizations?
Data analysis brings several benefits to the company, helping it to understand its customers, evaluate its advertising campaigns, personalize content and create assertive strategies for its publication, develop new products or improvements on previous launches, as well as understand its competitors and the market.
The purpose of an organization investing in data analytics is usually one: to drive business performance and improve its financial results.
This happens in several ways, such as:
Process improvement;
Anticipation of competition;
Assistance in the decision-making stage;
Greater understanding of market trends and customer behavior.
What are the types of data analysis?
Within the discipline of data analysis, it is essential to understand the different types of analysis possible in an organization. These are techniques that are used alone or together. Check out what they are:
Descriptive analysis
Descriptive analysis is the least difficult and therefore the least valuable. You are basically trying to understand “what happened.”
It is based on a method of searching and organizing historical data to identify patterns. In this case, visual tools such as pie charts or bar graphs are widely used.
Diagnostic analysis
Diagnostic analysis is the method that seeks to understand “why it happened.” That is, the reasons.
It is based on investigating past data (regression analysis) to find the root of an event or behavior identified in the first step. The goal is to find causes and correlations with key variables.
Predictive analysis
Predictive analytics, as the name suggests, seeks to predict “what will happen.”
It is carried out using statistical calculation techniques, as well as Machine Learning resources, in order to predict events or behaviors based on historical data.
It is mainly about studying patterns and trends so that it allows companies to more easily identify opportunities for the future.
Prescriptive Analytics
Prescriptive analytics is the most difficult of all, but has the greatest potential for value among the alternatives mentioned. With it, we seek to understand “how can we make it happen?”
This method relies on Artificial Intelligence tools and Machine Learning algorithms to determine recommendations and their possibilities.