Career in analytics is one of the best choices to build your future and invest time for a bright career. Lot of people are shifting to analytics because as the industry matures it requires more skilled data professionals from various domains. If you are one among those people who are considering the shift, there are few important things you need to know about a career in analytics.
Many professionals seeking to change to analytics careers or add analytics skills to their resume browse online on how to build a career in analytics. They also search about how to gain essential skills. Majority of the people post various questions related to analytics career.
In this, article we will be addressing most important questions asked to help you get started.
1. Quantitative skills are important, but are not a prerequisite to learn analytics
Analytics is about numbers and data sets. So, understanding of math and statistics and having some level of knowledge will help. But, it is not mandatory. Just like everyone, you will also learn it. Most of the courses or trainings begin with the basics before you move on to the core concepts. In case if you do not have any idea statistics and analytics or if you aware but want to brush up your basics then that eventually happen during the course. Nothing to worry at all, at the end of the day you will be able to handle any data set easily.
2. Analytics is used in every field and it is for everyone
Data is present for everyone. Irrespective of the background you have whether it may be commerce, business, marketing, finance, engineering, or anything else, analytics can help to boost your career. Most of the companies look for people with some level of experience in organizing, handling, managing, analyzing data and hire for analytics roles in their team.
These day’s businesses are mostly data dependent, data driven. Most of the executive decisions being taken are based on the data analysis outcomes.
3. Programming background is not necessary to succeed in analytics
Data analysis is done using programming and algorithms. There are special software’s which will allow you to do data analysis. But just like with math and statistics, it is not compulsory to have coding or programming knowledge before you start learning analytics.
There are many institutes across the world providing Analytics, Data science courses. Those courses teach you the various data analysis tools, software’s from the scratch which are mostly used in the industry. So nothing to worry if you are from programming background or non-programming background. It is the passion which will drive you to success, rest all will be taken care.
4. The kind of analytics techniques used varies as per the industry sector, domain
For instance, if you come from non-HR background, it would be not easy to understand the terminology used in HR Analytics. Analytics is all about using data skills combining with domain knowledge or expertise. For a finance professional, knowing how to detect credit card fraud is more relevant whereas for a marketing professional understanding marketing mix modelling is appropriate when they are looking upskill.
It is all about having knowledge in your domain and leveraging it. As a fresher if you are aiming for a career in into data science, data analysis or as an experienced professional, want complete career change into data science, data analysis, then gain thorough knowledge on how to use different concepts, techniques to solve various real-time business scenarios.
If you want to limit yourself to your domain expertise or experience and learn to apply data science techniques, then that is also welcomed.
5. Big data is a subset of data analytics
Big Data Analytics is a section of analytics that applies to large data sets which are bigger than standard data sets. While the basic concepts remain as they are, only the techniques vary in terms of how to handle, manage, store, and analyze Big Data due to its huge volume, velocity variety, variability & veracity.
Now whether to learn Big Data techniques depends on a few things:
- Do you belong to IT sector?
- Is there a need to store and analyze huge amounts of data in the industry you are working in?
- Are you from a programming background?
Once you analyze these questions, you will be able to decide whether to go for Big Data , Machine Learning, Data Science.
Above discussed points are some of the key things you need to keep in mind before you begin your analytics career.