Data analytics is becoming very on-trend. It is in such demand that a great number of people are
becoming interested in learning more about it. A job that is promising, rewarding and comfortable is
what is attracting the youth towards it. Online courses are offered by many institutions in the field of
data analysis. The field is considered to be quite vast and so it is necessary to understand different types
of analysis.
This article discusses the various types of data analytics that exist as of today. Read below to understand
which type may suit you best and to decide accordingly.
1. Descriptive Analysis:
This is a type of analysis that explains the how of a problem. It describes everything that has
happened over a period of time. For Example: A manufacturing unit collected data regarding the
operation of its machines for a year, descriptive analysis, then assisted the management team in
preparing the information in such a way that it then told them the number of times the
machines were run, the amount of output that was generated and the time intervals for their
operation.
2. Diagnostic Analysis:
This type of analysis lays emphasis on defining the reasons behind an event that has occurred. It
goes a step beyond descriptive analysis. For Example: In the same situation noted above,
diagnostic analysis would lay emphasis on telling the management team why a machine broke
down or how many machines were working at their full capacity. This would provide the output
from all machines in the manufacturing unit which would define which specific machines were
leading to any inefficiency.
3. Predictive Analytics:
Such an analysis tries to create hypothetical situations to present possible reasons for a problem
that might have occurred or for the current situation. Such an analysis makes assumptions about
a current situation and then attempts to predict the future. For Example: based on the current
records of the machine operations of a business, the predictive analysis can make a conclusion
that the production would increase over time to economies of scale. This information is
extracted with the help of trend analysis.
4. Prescriptive Analytics:
This is a cautionary type of data analytics. It suggests various ways in which a company can
operate to ensure they are working at a safe level without being affected by external factors.
For example: If in the problem noted above, the analysis draws conclusions that machines are
getting older and could lead to unsafe working conditions for the employees, then the analysis
would recommend that new machines be installed.
Conclusion:
It is not mandatory that an analysis needs to be carried out in isolation. A combination of analysis is also
done by the analysts. Such analysis needs to have a problem statement defined. Therefore, an analyst
needs to know all the different types of analysis to perform them effectively. Many institutions help
students get trained in this field.
Resource Box:
ExcelR is a company that has been dedicated helping students who want to learn data science and enroll
in data analytics courses. They have special courses designed for students to help them understand the
basics, the intermediate and the professional levels of data analytics all through online expertise help.
Students only need to join the data analytics certification coursefrom ExcelR.
