Analytics is the field where experience matters most. Yes, I mean it. No doubt there are many other criteria and important too. Say, getting yourself certified in the technology you feel you should be moving forward in your career with, get some projects done, write blogs or help to resolve issues on online forums. However, leaving behind the experience, the next lion share goes to the certificate. So let us concentrate on the first part where your experience matters more not only on the field but during the interview.
A certificate can get you to the interview room, but your confidence and experience or we can see the know-how of interview can achieve you a job. It is also impossible to prepare for each potential question, as Analytics is a huge subject. However, the same questions can be bucketed into different categories and one can concentrate on specific categories depending on the work profile or career he or she looking into. Each company tests these categories subsequently and you must do well to have the job in your pocket.
There are many fancy designations being awarded now a day to the professionals across the globe, however, there are some standard designations which can be listed as below.
- Data Architect
- Data Engineer
- Data Analyst
- Business Analyst
- BI Expert
- BI Engineer
- Data Scientist
Above is the information on the just to kick start, there are many fancy as well as traditional designations you may be attempting. So let us move towards attempting an interview.
All though there may be different rounds based on the level candidate getting interviewed, Say
- Aptitude or skill test – (Entry Level)
- Group discussions – (Entry Level)
- Reasoning or Logic test
- Coding ability test
- One to one discussion
Above all are important, however, the most important one is “one to one discussion round”.
There could be the main category as below,
- asic domain knowledge in the field of analytics
- Soft skills say spoken or written skill
- Thinking abilities
- Mathematics and statistics abilities
- Database, types, and concepts
- Machine Learning
- Data visualization
- Different data analysis tools and relating questions
Freshers or the experienced candidates wanting to shift their career into analytics should concentrate more on nontechnical skills and the experience candidate would be tested on both.
Currently, there is a huge demand for people with the right skills in the analytics industry and therefore the chances are bright for the candidates acquiring right skills and demonstrating the skills. In order to perform well in an interview, please have the following things in place,
Decide on the Objectives:
It is impossible to do sound analysis without knowing what you wish to achieve. Too often an analysis is started without a clear idea of where it is going. The result is usually a lot of wasted time and an inadequate analysis. In case during the interview, if you have been given with the problem to solve, ask question as many as required building clarity before you access the problem/puzzle
Understand the Data:
Understand the data given to you, and start with collecting information and analyzing the sets give and decide on how you going to use the give data to achieve the objective given. Basically, collecting data meaning putting a design for collecting information into operation. You’ve decided how you’re going to get information – whether by direct observation, interviews, surveys, experiments, and testing, or other methods – and now you want to implement your plan.
In real life, or in professional life it may or may not required to clean the datasets before start building analysis out of it however, there are 98 % chances that the data given to you in the interview need cleaning. Improving data quality is an essential step in data analysis. Analyzing bad quality data will result in erroneous conclusions unless steps are taken to validate and clean it.
The analysis involves examining information in ways that reveal the relationships, patterns, and trends in it. That may mean subjecting it to statistical operations that can tell you not only what kinds of relationships seem to exist among variables, but also to what level you can trust the answers you’re getting. The point, in terms of your evaluation, is to get an accurate assessment in order to better understand your work and its effects on those you’re concerned with, or in order to better understand the overall situation.