Introduction to Data Analysis and its tools in IT Industry

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What is Data for a non-IT background person? Very easy to understand for IT Professionals, but what is Data for a person who hasn’t even peeked into the IT world? Please read further if you want to learn more about data.

The terms Data Factory, Data Lake, Data Analyst, Data Mining, Data Drilling, Data Scientists, Big Data…. Huh… What even is a Data…?

Let us find out together… What Data is, and how and why to analyze data in today’s world. Let’s take a step back and together bring the non-IT audience into the world of Data.

1. What is Data?

Data is fact/ facts, details, and/ or figure/ figures related to anything.

Let me give some examples of data to make you understand better.

Employee ID, Name, Salary, Department number, email address, etc...

Can my name, my age, my email address, your name, your age, your address be considered a Data?

Yes… You got this…

Hmmm…. Now that we have understood what Data is, the question is why do we need to spend time to collect it? It makes no sense…

Data makes little or no sense if seen alone. When combined with other facts, data gives us a clear picture of a particular problem or you can say, it gives us a solution.

2. What is Data Analysis?

In its simplest form, Data Analysis can be defined as the task of interpreting the data based on past collected facts. Or, we can say, to explain our data to make more sense. The task of Data Analysis can be achieved if we have relevant data related to the area we want to study.

Any individual or any organization who wants to take effective decisions, so that risks in future decision-making can be minimized, can perform a Data Analysis. It is not always true that if we take our decisions based on past data, it won’t fail. But the risks of taking unsatisfactory decisions can be minimized.

A student, who is ready for college next year, can perform a data analysis as to which courses to opt for to be a successful employee/ Entrepreneur in future. A food shop owner can perform data analysis to minimize food wastage. And the examples can be many…

Let’s brainstorm on it for a moment. Think about problems in our daily life and then read on…

Data Analysis can be very helpful in taking significant decisions, depending on the goals of analysis.

Personally, I would love to solve many problems with the help of data analysis, not only related to big organizations but also at individual or household level. I will write another blog posts on the problems which I would like to find a solution to…through Data Analysis.

Data Analysis is the art of making your data speak what it wants to speak. It is a technique to make your data your best friend. It should say every relevant fact and you should listen to it fact by fact, everything that you need to know, and it wants to tell.

After all, you have spent so much of your time, energy and probably money as well, collecting those facts. Your data should be as clean as possible so you can be a describer/ storyteller of that data. By clean data, I mean removing repeated, wrong, or irrelevant data, so that the analysis will be based on real facts only. They call the ‘repetition of Data’ as ‘Data Redundancy’. The whole process of removing the irrelevant or redundant data is called ‘Data Cleaning’.

Cleaning of Data is done to prepare the data for analysis.

Nowadays, Data is sometimes so big that it cannot be analyzed by human brain. To make this task easier, companies have provided various software to help us in the process of what is called ‘Data Analysis’.

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3. Why to analyze the data?

You might already got the answer to this question. In real world, we analyze the data to study past trends, as they say…

What? Past is all gone… Why are we putting so much effort into studying the past? How can it help us in taking a decision.

Well! We learn from our past mistakes which actions are not to be repeated and which areas to focus more on, if we want to be better. Similar is the case with big organizations. They want to study the past trends with data analysis to take decisions related to their finances, which product to launch and when, how to retain employees in the company, how to satisfy their customers in the best possible way and much more.

In big Organizations, we analyze the data to help higher management take important business decisions, which helps them thrive.

4. How to analyze the data: The steps

Data is analyzed in various steps, as listed below:

Define a problem:

There is no sense of data analysis unless there is a problem to solve . So, the first step in analyzing the data is to define a problem statement. Why do we need to collect the data (Defining a goal)?

Identify the population to collect Data from:

The next step in Data Analysis is to identify where to obtain that data. Do we need to take the whole population into consideration, or a sample of the population will work? Where do we need to send the team to collect specific data related to that field?

Prepare a questionnaire:

Questionnaire is a worksheet to collect the data. We need to frame mostly open-ended questions for our target sample/population, to fill up. This is done to collect views of the people/organizations, so that collected data can be used to approach our best solution to the problem we defined.

Creating a Database out of that data:

Now, Data cannot be interpreted if just written on a sheet of paper. There must be a medium which can be understood by a computer so it can help us in our analysis. The collected data is fed in different tables which together is known as a Database. By this, I can say Database is an assembly of related tables.

For example, if I collect data about a particular store and its customers, I can create one table related to various products in that store and another table which has data about how many customers purchased a particular product in that store. Because we are talking about the same store here, the tables which we have created will belong to the same database.

Analyze the data:

It is not possible for human beings to just look at the raw data and take decisions based on that data. There must be something which can analyze faster and give trends to decision makers in the form of visualizations. In today’s world, data is changing all the time and a huge amount of data is being generated every second. People are using different websites, YouTube channels, Facebook, twitter, etc. every second and huge amounts of data is being generated. We need to act fast in our analysis process.

To make our analysis process fast and efficient, companies have developed some software in which we can feed our tables from the database and these software helps us to make graphical representation of collected data.

Finally, our data has its own meaning. It speaks up and tells us a story.

Let us look at some of the tools which can help us in the process of analysis.

5. Tools for Analyzing the Data in today’s world.

Here is a list of some of the tools which can help us in Data Analysis.

Tableau

Microsoft Power BI

Microsoft Excel

QlikView

Splunk

And many more!

6. Conclusion:

Huge Data is being generated every second of our lives. Analyzing and taking important decisions can be overwhelming and sometimes impossible for humans without the use of different tools.

Are you ready to dive into the world of data?

In my another post, I will give you a sneak peak of the options if you decide to make your career in the IT industry.

Thanks for your time!