SMECWhat is Data Analytics?

What is Data Analytics?

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Importance of Data Analytics

Data analytics can be described as the analysis of the raw data which is collected. Data is required for several purposes in the business sector and data plays an important role in many organizations. Data is required to take proper business decisions and in order to do this, the quality of the data should be good. So the analysis of the data is really important. By doing the data analysis we would be able to determine the pattern and the quality of the data. Basically in the data analysis, the data would be inspected, cleaned, transformed, and modeled.

Why data analytics is required in an organization?

The major purpose of data analytics is to collect a huge amount of data, and this information is used to carry out several processes in an organization. Data visualization can be easily carried out by analytics, we can determine the quality of the data. In case there is any situation arises in an organization then it can be checked by analyzing the data.

Descriptive analysis can be done to determine what has happened. Diagnostic analysis can be done to determine the problem and predictive analysis can also be done to determine how it has happened and prescriptive analysis can also be done to take decisions to solve the problems. During the data analytics, data would be checked to determine the current requirements, and based on that several decisions would be taken.

Many organizations are utilizing data analytics to take proper decisions which would make a good impact on their business. Many researchers and scientists are also utilizing data analysis techniques to check the data models. Data analysis can also be utilized to determine the pattern of the data and this can be utilized to achieve efficient operations. Almost all the business sectors are utilizing data analytics small scale, large-scale, and middle-scale organizations are also utilizing the data analytics features to achieve quality operations.

So the major role of a data analyst in an industry is to find and create connections with different data sources. So several connections are required to collect the data. Google, Facebook, and most social media collect a lot of data from their users. Several mobile apps and social media would collect a lot of data from us. If we check some e-commerce websites such as Flipkart or amazon.

While utilizing these apps to search for several products we will get various suggestions based on what we have searched on other social media platforms. So that’s the importance of the data. Social media is sustaining because of the collected data. Data plays a great role in most social media platforms.

Data Analytics
data analytics

What are the major roles and responsibilities of a data analyst?

As a data analyst one should be capable enough to collect the required data and also must be able to do the analysis of it. Should be a data junkie and must have knowledge regarding python, HTML, Javascript, C/C++, and SQL. There are many skill set which is required for data analysis, and some of them are Excel, data-based systems such as SQL, communication and visualization, Maths, Statistics, and machine learning. So these are the skills required for a data analyst to get placed in major MNCs.

Data analysts must be capable to determine the proper data which is required to carry out the data analysis. Should be able to gather the required data from several sources. The collected data must be checked and should determine its quality. These collected data must be organized and structured in a way that they can be utilized for the analysis.

Must be able to collaborate with others during the work and thus data can be collected, integrated, and also can be arranged for the data analysis. Must be capable enough to create the analytical models and also should access the findings. These findings or the data results must be provided to the relevant members of the organization so that they can take the required action based on that.

What are the different types of data analytics which is utilized in organizational processes?

Descriptive type

In this type of data analytics, the data would be checked to determine the changes in the industry. The collected data would be based on each of the industry types for example the data collected by an IT firm would be different from the data which is collected by an Automation industry. So each organization would require data regarding their own sector and the quality of the data should be checked also the collected data must be organized. In the case of a digital marketing firm, it would require to understand the data regarding the type of customers they have and also must be able to know how their service helps their customers, etc.

Diagnostic type

In this type of data analytics, we would be able to determine the problem, or how it has happened in that way. In the case of a software development organization, this kind of data analytics would help them to determine why they have not acquired the profit that they have targeted. They would be able to determine the required marketing strategy for their organization based on the collected data. This kind of analysis would be helpful for almost all organizations.

Predictive type

As the name implies this type of data would be useful to determine what could happen in the future based on the collected data. So the accuracy of this type of analytics would be based on the amount of data that is collected. So this type of analytics would be carried out by many organizations to determine their profit or loss.

Perspective type

In this type of analytics, several decisions would be taken based on the collected data. Collected data would be checked and then proper precautions or actions would be taken based on the data. The accuracy of this would be based on how the data is acknowledged.

What are the major industries that utilize data analytics?

  • Banking
  • Healthcare
  • Finance
  • Social media
  • Energy retail
  • Manufacturing
  • Aviation
  • Retail

What are the major job roles in the data analytics sector?

  • Data scientist
  • Data analyst
  • Data Architect
  • Statistician
  • Database administrator
  • Business analyst
  • Data and analytics manager

Author – Ashlin A J

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