Introduction to Data Analysis

 

1.1. Data and Statistics

Data are information collected in various form. Singular form of data is called datum. It is like natural raw resources but unlike many natural resources, data shouldn’t be preserved only but also utilized at the same time. If they are not analyzed within a stipulated time than their validity may expire and they might not be as useful. This analysis is done with proper usage of various statistical tools. Without statistics, data are just information lying around and without data, statistical tools are of no use. In other words, it can be stated that both data and statistics are interdependent, together they can be used to see future like a fortune teller and throw lights on the missing past. It helps us to detect problems and find their solution like a doctor. If statistics is the fortune teller than data is the magical spell. If data is the fuel, then statistics is the engine.

‘Data are basically information in form of text, numbers, audio, video, pictures etc.’ [1] ‘Statistics is a method of collection of data, analysis and presentation of data’[2]. Statistics is a branch of mathematics which deals with data and help us to draw meaningful insights from it. Statistics provides meaning to the data and transforms them into meaningful information. Statistics learn from data, uses data to predict future data. 

1.3. Data Analysis

‘Data analysis is a process of cleaning, transforming raw data to processed one and then model it to analyze it thoroughly and draw valuable information from it, make some useful calculation, finding trends and give suggestions/ solution to the problem in question accordingly. Data Analysis uses statistical tools to perform these tasks.’[4]It is a broader concept than the statistical analysis. It uses statistics and other concepts to perform various tasks. It is a multidisciplinary subject which uses various knowledge and tools of subject matter such as Economics, Statistics, Mathematics, Accounts, Finance etc.

Data Analysis is for everyone. Whether it is a business man, a service man, an academician, a medical student, lawyer etc., everyone deals with data on a daily basis and data by itself is of no use until they are properly analyzed and interpreted. In present world, every day, every minute a huge amount of data of different types are generating from various sources. This information is very useful resource, in fact the most useful resource which if used properly can create wonders. And thus, one needs to have a good knowledge of data analysis, in order to make proper utilization of this information.

 

1.3.1.      Data Analysis Vs Data Analytics

 

‘Data Analysis’ and ‘Data Analytics’ though sounds similar but has difference in meaning. Analysis basically describes the thing as it is or was and analytics describes how things will be in future.

 

Analysis is the beginning step of Analytics. History helps us to predict future. Historical data are the data points which helps us to analyze what the future might look like.

Whether is the pandemic or war, which the world has suddenly encountered in recent times are good examples. Decisions and precautions are to be taken on the face of uncertainty. But what could be the possible outcome or problems world might face and how could these be tackled can be answered by seeing the past experiences during Corona Virus. Also, present or recent past situation/data can show the trend of near future, for example inflation or population growth. Analysis basically involves ‘what was/is?’ while analytics deals with ‘What could /couldn’t be?’

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1.3.2.      Steps in Data Analysis

 

Data Analysis is a combination of various steps which maps the direction and shows the path from the starting point to the ending point. Just like how a doctor analyze our disease. The steps are as follows:

1.3.2.1.Descriptive Analysis: In this step, we analyze the problem statement. We here just try to find the problem, that is, “What the problem is?”. This stage helps us to understand the current stage of the variables under consideration or to understand the problem statement.

 

1.3.2.2.Diagnostic Analysis: In this process, we diagnose the cause of the problem. In this step, we analyze ‘Why has it happened?’ or ‘What could be the reason of the problem?’. i.e., we apply various analytical tools and either reject or accept the hypothesis (a statement made based on certain assumptions or information) on basis of the data drawn. Here, we reach the very root cause of the problem.

 

1.3.2.3.Predictive Analysis: Here, we predict the possible outcome of the problem. In this step. We analyze ‘What can happen if the present situation continues?’. Depending on the given data, we determine trend and predict the future outcome.

 

1.3.2.4.Prescriptive Analysis: After the diagnostic and predictive analysis we provide the possible solution to the problem in the prescriptive analytics step. In this step, we determine ‘What should be done?’[6]

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Suppose, when we go to a doctor, the first question he asks is, “What is the problem?”. Here, we state the problems we are facing i.e., the symptoms. This stage is called Descriptive Analysis stage.

On basis of the symptoms, the doctor formulates a hypothesis regarding the cause, “This could be the reason.” We often hear them say. And then suggest some test to perform in order to detect the cause of the problem. After receiving the reports, they either accept or reject the hypothesis and draw a conclusion regarding it. This stage is called Diagnostic Analysis Stage.

After the cause has been detected, they tell us what could be the future outcome of it if it continues the same way. How major could it be. This is the predictive analysis stage.

And finally, they prescribe us some medicines, exercises etc. required to check the disease and prevent it from increasing. This is the final stage, the prescriptive Analysis Stage.

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[1] Java T Point,, avatpoint.com [Website], https://www.javatpoint.com/data, ’What is Data?, (accessed 12 March 2023).

[2] ‘Byju’s, ,byju’s.com [Website], https://byjus.com/maths/statistics/, ‘Statistics’ ,( accessed 12 March 2023).

[3]Sas,  https://www.sas.com/en_in/insights/big-data/what-is-big-data.html

[4]B.Calzon, ‘Your Modern Business Guide To Data Analysis Methods And Techniques’, The datapine Blog,

https://www.datapine.com/blog/data-analysis-methods-and-techniques/, 15^th April 2023, (accessed 20 April 2023)

[5] https://www.questionpro.com/blog/data-analytics-vs-data-analysis/

[6] 4 Types of Data Analytics Every Analyst Should Know-Descriptive, Diagnostic, Predictive, Prescriptive | by Co-learning Lounge | Co-Learning Lounge | Medium

 

 

[8] https://www.datapine.com/blog/misleading-statistics-and-data/#:~:text=Misleading%20statistics%20refers%20to%20the,news%2C%20media%2C%20and%20others.

[9] https://blog.panoply.io/data-collection-how-what-when

[10] A problem well stated is a problem… (Charles Kettering Quote) - Famous Inspirational Quotes & Sayings (inspirationalstories.com)