How do I start learning data analytics step by step?

Data analytics is one of the most desirable careers now, especially with companies in dire need of skilled data analysts. Businesses operate effectively with the help of data-backed decisions. Data is everything now. In order to ensure that the generated or sourced data is used as effectively as possible, data analysts are mandatory. Data analysts extract the insights required by companies from data and provide comprehensible answers to business problems. In order to acquire the necessary training to help firms make sense of data, good Data Analytics courses in Kolkata and other major cities are highly recommended.

Data analytics as a career

Data analytics has huge potential and is one of the fastest-growing occupations globally. Most companies utilize data for analyzing customer behavior, predicting anomalies, forecasting, increasing profit, cutting risk, and reporting. Without trained data analysts, firms will not be able to make the raw unstructured data cognizable. Thus, every major company and some smaller firms must depend on data analysts. This is why data analytics is a rising career and there is a bright future ahead for individuals pursuing this field. Mainly, the job roles of a data analyst involve data management and data interpretation. This is a very important role, especially inside an organization that uses data for its daily operations or for making business decisions.

Data analysts are handsomely rewarded for their services all around the world. In India, junior data analysts get paid Rs. 6,00,000 annually on average while some companies can pay as high as Rs. 12,00,000 per annum. Meanwhile, individuals with 3 to 10 years of experience can earn anywhere between Rs. 25 – 65 lakhs annually. The compensation in this field is very lucrative, however, the demand of data analysts in the modern era and the value organisations place on their data analysts are even more alluring. Even though this field offers so much in terms of materialistic value, it also is highly rewarding to have the ability to provide large corporations with insights that will help them make better operational decisions. 

However, there is still a huge lack of manpower as compared to the requirement in this sector. Working professionals who switch to data analytics from software engineering and other fields also enjoy drastic salary increments which can go as high as a 44% increase. Since 2019, 46% more data scientists are being hired, which is a huge number. India will have over 11 million job openings by 2026 and experts and we will experience more growth in this field globally.

How to learn data analytics from sratch?

Data analytics requires a good foundation of mathematics and statistics. Future data analysts should start getting familiar with linear algebra, functions, graphs and various equations. Learning the fundamentals is essential and if you wish to become a data analytics expert, you have to learn to love numbers. You must grow the habit of using numbers to predict or forecast outcomes. For example, you can try to predict an active company’s sales pattern using the available data. Data analysts should be fluent in foundational statistics and in summarising data parameters using mode, mean, median, distributions, and central tendencies.

Data analytics requires expertise in multiple areas such as data manipulation, data sourcing, data cleaning, data interpretation, visualization, forecasting, and reporting. Thus, there are quite a few tools that you must start getting comfortable with. For example, Microsoft Excel and MySQL. Data analysts must be masters of DBMS as one of their main responsibilities is to create, update and maintain databases. Due to this reason, Data analysts must also have enough experience in using SQL or the standard query language. Learning SQL will help you go a long way, as you get deeper into data management. 

More than anything, many companies require you to import data from databases into visualization tools and other business intelligence software. RDBMS or Relational Database Management Systems also can handle much larger databases as compared to Excel. However, learning how to use Power Pivot in Excel can prove to be especially helpful for building data models and conducting advanced data analytics. Power Pivot in Excel and other business intelligence tools such as Microsoft Power BI allow users to apply advanced formulas, conduct deep analysis, and work with massive datasets. 

At this point, when you are fluent in Excel and SQL, you should learn a programming language such as R or Python. Python is great for working on machine learning, artificial neural networks, and for deep learning as well. However, R is probably the best language for statisticians and even data analysts. R is best suited for statistical purposes and is developed by statisticians, thus, suiting the purposes of most data analysts very well. 

Once you are comfortable with any of the two suggested languages, you can start delving into neural networks, machine learning, or even start working on projects such as image recognition and music recognition. You can start implementing the algorithms you have learned at this point and use techniques such as Logistic Regression, Linear Regression, or K-means Clustering. This, however, is not exactly mandatory, as many data analysts get involved with business operations and core analytics. Fundamentally, this requires expertise in Excel, DBMS, business intelligence tools such as Microsoft Power BI and reporting. 

Depending on your field of choice, you can also gain industry knowledge about the sector. For instance, if you wish to join financial analytics or business analytics, you can start acquiring some business knowledge or financial knowledge. You can also choose to learn SAS as it is one of the most powerful statistical tools out there.

Conclusion

If you wish to use distributed file systems such as Hadoop or data-warehouses such as Apache Hive, you can start learning Tableau. If you feel like Excel is not enough, you can always start getting acquainted with Tableau and use modern systems. Once you are familiar with all the tools and techniques involved with data analytics, becoming a data analyst will be very easy.