In the 21st century, data is power. It is ‘Human Nature’ encrypted in the form of numbers. However, in its raw form, data is not easily understandable. Data analysts analyse raw data to make it accessible and valuable for businesses. With the help of data analysts, a company can make vast improvements in its operations. Data science opportunities are limitless, from finding potential customers to streamlining the manufacturing process to finding the best place to put the coffee maker so all the employees can access it readily. This is why data is priceless for business organisations.
Therefore, businesses are now eager to employ data analysts. But being a relatively new field, there is a shortage of data analysts in India and the world. Therefore, it is an excellent opportunity for anyone looking to make a career in data science, as there will be no shortage of work once they complete it.
This article will discuss data analysis, why it is essential in the Indian context, Job opportunities for a data scientist and data analyst course duration and fees.
What is data analysis?
Data analysis is the discipline of deciphering and discovering meaningful insights from any given data. This is done in a structured manner.
First, data is collected from various sources. This is controversial as data privacy has become a sensitive topic for everyone. We would not want our personal data to be misused. This is why there is a distinction between ethical and unethical data.
As the name suggests, ethical data is collected with the person’s consent, and it is used so that it does not adversely affect the person or society. Whereas unethical information is collected without the permission of the public. But the data analyst can’t differentiate between ethical and unethical data because they are not the ones containing the data. Data analysts will be presented with the data, and their work will start from that point.
Since raw data is not organised, it may have several issues. For example, there can be duplicate or missing data. Therefore, the data must first be arranged and restructured by the data analyst. The term “cleaning the data” generally refers to this step. The goal is to make the data simple, easy to comprehend, and ready for the next step in the process.
After the data is structured, the next step is analysis. This step aims to find correlations, trends, and other essential aspects of the business. The study is done by running the cleaned data through various algorithms.
The final step in the process is data interpretation. In this step, the gathered knowledge from the analysis step will be observed and presented in a way that becomes useful for the business.
In its simplest form, data analysis is all about asking questions and finding their answers. There are four types of Data analysis.
- Descriptive Analysis
- Diagnostic Analysis
- Predictive Analysis
- Prescriptive Analysis
But these are not stand-alone methods. Instead, all of these are linked, and with the gathered knowledge from one kind of analysis, one can move to the following type of data analysis.
Let’s discuss these four types of data analysis in detail.
Descriptive Analysis
One of the most common forms of data analysis used in today’s market is Descriptive analysis. This form of research looks to answer a very fundamental question. “What happened?”. The answer to this question will give critical insight into the business’s performance over time. It is generally presented in the form of a dashboard.
The descriptive analysis tracks a company’s key performance indicators. For example, sales figures, number of items sold, in which months there was more volume, who was the biggest customer, etc.
This data will be used to gauge the overall health of a business. It will give the business insight into if the company is growing or performing well or not.
Diagnostic Analysis
A data analyst will move on to the second most important question with the gathered insight from the descriptive analysis. “Why did it happen?”. Having an answer to this question is very important for a business.
A data analyst’s job is to find answers to this question. The data analyst will use the insight from the descriptive analysis and find the key points that moved the critical performance indicators of a company. For example, a data analyst will look into why sales figures were high in a particular month and in other months they came down or which marketing activities generated the most sales.
Predictive Analysis
After the descriptive and diagnostic analysis is complete, the data analyst will move on to the next step in the process. Remember that predictive analysis is not as typical as descriptive and diagnostic analysis. Mostly because businesses are not yet ready or willing to invest in this form of research. Yet, predictive analysis can hugely benefit a company.
The predictive analysis looks to answer the question, “What will probably happen next?”
This question will be answered through the gathered data from descriptive and diagnostic analysis. Furthermore, this data will be run through various AI-based technologies like machine learning tools or deep learning methods. As a result, it can more accurately predict the future of a business.
Predictive analysis helps assess a business’s risks, future sales figures, and many more.
Prescriptive Analysis
The prescriptive analysis is at the forefront of the data analysis discipline. This is also a prevalent and desirable form of data analysis currently available in the market.
The prescriptive analysis looks to answer the question, “What should the company do next?”
For prescriptive analysis, insights from all the previous data analysis are gathered and run through cutting-edge AI technology.
Prescriptive analysis improves a company’s performance through intelligent and informed decision-making.
Data analytics tools
Data analysts will use various tools to gather insight from raw data. Some of the most common tools today are Python, Excel, Rapid miner, Tableau, QlikView, and many more.
Data analysis in India and opportunities
The Indian economy is snowballing, and new unicorns are coming out like clockwork. This is only going to continue. All these companies use some form of data analysis to make better-informed decisions for their business.
Still, there is a shortage in the number of data analysts available in India. Therefore, completing a course in Data Analysis in India will open up vast job opportunities. Data analyst jobs are one of the most lucrative jobs in India.
Data analyst course duration and fees
The data analyst course will take anywhere from 3 to 6 months. It will include classes on Data visualisation and analytics, Data science with python, and a machine learning course. In India, the data analyst course fees will range between 50000 to 100000 rs. For people who are already employed, online course availability is a godsend. Most courses are anyhow a mix of online and offline classes.
Conclusion
A data analytics course is a worthwhile investment for anyone looking to enhance their practical skills and job opportunities. More so in India, there is a shortage of data analysts, and every company, be it small or big, wants to have a data analyst on their team. Therefore, the demand for data analysts in India will only grow, and there is no better time than today for someone looking to enroll in a data analyst course. The short data analyst course duration and fees being so low also helps.
