Learn analytics and become a data analyst.
Data Analyst is one of the high paying, in-demand jobs right now. Every company despite its field is becoming data-driven. They are trying to find value with their data. They can outsource the job to other companies or hire their own analyst team. Whatever the decision may be, a data analyst is the one who finds the value in data. Naturally, the demand for data analysts is booming. IBM predicts the demand for analysts will soar 28% by 2020.
If you want to know how to become a data analyst, then you have come to the right place. First, let me quickly give out the definition for the data analysis. As an analyst, you’ll be working with a huge volume of data to derive valuable insights for the organization using some analytic technique. This process is data analysis. The analyst role is not only exclusive to the data. There are a few types of analyst role present,
Data Analyst – As I said, the role of the data analyst is to retrieve valuable information from the data.
Business Analyst – It is closely related to the data analyst, but business analyst retrieves useful information that drives the performance of the business. They find insights on how to refine the day to day operations, mitigate risk, etc. They are more related to the business side than the analytics side.
Quantitative Analyst – They work in the financial industry to predict the stock or bond price, find any potential risk in investment, etc.
As you can see, there is a variety of data analyst role. Whatever you decide to become, you should have the following capabilities.
Have strong knowledge in Mathematics
Though there are tools and software that executes the mathematical algorithms, it is vital for a data analyst to have strong mathematical skills. Whatever analysis you may do with the data, it all has math at its core.
Data Cleaning uses basic statistics like mean, mode, median, etc. Linear algebra like matric manipulation is used in the development of neural networks. Gradient descent in the regression algorithm uses calculus techniques. Graphs and tree structures in discrete mathematics are used in the optimization algorithms.
The analysis process literally touches every area of mathematics. It is easy to get disappointed to see the hurdle in the form of maths. But as I said, there are many tools and software that mask the difficulties in implementing the algorithms. Scikit-learn, TensorFlow are free popular machine learning frameworks that don’t require any mathematical skills to work. But if you want to become a top person in the analytical field, you should take the difficult path and have the knowledge of mathematics.
Know your technologies
You should not only have mathematical skills but know how to deploy the maths using technology. You will work with any one of the popular technologies like excel, python, SQL, Tableau, Hadoop, etc in your company environment. These technologies help you in executing the analytical process like cleaning, visualizing, analyzing, etc seamlessly. So, have working knowledge in all the process of analytics from cleaning to visualization using a popular technology to land a role as a data analyst.
Data Analysts should also have knowledge of programming. All the popular tools like TensorFlow, Hadoop, spark are based on coding. So learning a programming language is a must. For analyzing and visualizing data, Python, and R is a popular programming language to learn.
Learning by doing
Learning by doing is the best way to learn anything. So after you master your skills in mathematics and analytics technology, practice your skills by solving real-world problems. You can check my previous post on a “data analytics project to advance your career” to have an idea about it, or there are a number of projects hosted on the Kaggle website that you can work on. Having a working knowledge will go a long way in grabbing the role of the data analyst.
Learning about analytics may seem difficult as it involves mathematics and programming. But once you start learning about it, you’ll be amazed by the potential of it. It is the most popular domain right now, and analysts are in high demand. There are numerous sources available on the internet to start your learning. It is never too late. Start now and become a part of this wonderful domain.