In the last 2 years, a lot of people(beginners, transitioners) asked us how do I start my career in data analytics and similar questions. We, then started writing articles on these topics and got overwhelming response from the readers.
We bring you the curated list of all the articles based on career related suggestions and knowledge. These articles will help you to get acquainted with the steps that you must take if you are planning to enter data analytics industry.
If you are still facing any issue in your career, feel free to get in touch with us at [email protected] and we commit to respond you back within 24 hours.
Below are the list of articles which can help you to know more about career in analytics:
1. How to start a career in Business Analytics?
This article will guide you through a stepwise approach to learn about how to begin your career in business analytics. Lately, a lot of folks have developed affinity for business analytics mainly because of two reasons: 1) It is a lucrative industry 2) passion for numbers/quantitative skill set. We have revealed the sets of tips which can help to choose this path.
2. All you need to know to start a career in Business Analytics
There are a lot of things one should consider before making a mark in business analytics domain. Such as, he/she should learn about what part of business analytics suits the best, what sets of skills, tools, techniques would be the best suited for his caliber. In this article, we have listed all the possibilities which should be considered for a business analytics career.
3. How to become an analytics rockstar?
Lately, we received a lot of queries on how to become an awesome analyst. An awesome analyst is defined by the sets of work he can perform with great ease. It generally involves having a good grip on the concept you know of. Here is the knowledge of how you can become an analytics rockstar.
4. Tips to prepare outstanding CV for Data Science roles
Curriculum Vitae marks the first impression of your candidature on the hiring team, even before you personally meet them. More than 50% of every interview success is driven by how flawlessly your resume has been built. In this article, we have discussed the tips to help you make an awesome CV for job interviews.
5. How freshers can ace interviews for Business Analytics roles?
The biggest roadblock for a fresher to enter in a industry is ‘clearing job interviews’. Freshers usually struggle in this stage due to lack of guidance and smartness. Here we have revealed the list of  smart tactics which can help you to ace in your job interviews.
6. How can I become a data scientist(business analyst)?
This has been one of the hottest topic on our website in the past 2 years. Data Scientist is known to be sexiest job of 21st century, reckoned by Harvard Business Review. In this article, we have stated the road map which we recommend to all our readers to follow for becoming a data scientist.
7. Should I become a data scientist(or business analyst)?
If you are inclined towards business analytics but still you are in dilemma if you can succeed or not, this article is a must read for you. This will make you aware, considering your current set of skill sets, if you are a fit to become a data scientist.
8. Starting a big data analytics practice? Answer these 5 questions first.
Ever tried to learn about big data analytics? Here are 5 questions to challenge your status quo, which will then help you evaluate the set of knowledge you possess.
9. Taking a new job in analytics? Ask these 5 questions first!
Are you looking for a new job in analytics? Â Here are the 5 questions that you should ask yourself before making the next move. These questions will help you reflect on your decision and its consequences.
10. Planning a late career shift to analytics/big data? Better be prepared!
Lately, people have started embracing data analytics for being one of the lucrative industry today. A lot of IT professionals, marketing, finance professionals ask us how to begin the career in analytics. Here is a list of some essential points that should be kept in mind before making this shift.
