We meet and speak to dozens of professionals every day wanting to know about analytics, career growth, opportunities in the industry, salary trends. The answers we are giving today have evolved from the answers we used to give 6 or 7 years ago. I myself have seen students come with a lot more knowledge about Analytics Careers and Prospects today than when we started ten years back. The audience is truly more knowledgeable. The internet has been instrumental in providing clarity and information in this regard. Unfortunately, the abundance of articles can get confusing and lead to an overdose of knowledge taking us back to square one.
When a professional comes looking at movement into the analytics industry, we insist that his professional background plays an important and crucial part. In our experience, we see that movement to Analytics is not an escapist plan but rather a road and journey which successful corporate professionals embark upon in order to give their careers a much-needed breakthrough.
The Data Scientist
This designation is what most of the buzz is about. Data Science Rockstar is what prefer calling them during my seminars and Lectures. With a yearly average salary of $118,70, they are amongst the top earners in the data science industry. The data scientists have the ability to handle the crude data using the latest technologies and techniques, can perform the necessary analysis, and can present the acquired knowledge to his associates in an informative way.
The Data Analyst
Languages like R, Python, and SQL are part of the data analyst’s basic knowledge. Much like the data scientist role, a broad skill set is also required for the data analyst role, which combines technical and analytical knowledge with ingenuity. This profile is often looked for by companies such as HP and IBM.
The Data Architect
Data is (being collected) everywhere and as a consequence, more and more organizations are in need of a data architect. Industries like banking and FMCG use data architects to integrate, centralize, protect and maintain their data sources. These architects often work with the latest technologies such as Spark and always need to be on top of the game to stay relevant.
The title of Statistician is regularly overlooked by or replaced by fancier sounding job titles. This is a bit of a pity, given that the statistician, with his solid foundation in statistical theories and methodologies, can be seen as the pioneer of the data science field. It is often he who reaps the information from the data and transforms it into actionable insights. To end, although the title can sound a bit dull compared to the others in this list, modern statisticians are always ready to rapidly ace new advancements and utilize these to benefit their research.
The Database Administrator
As a database administrator, you ensure that the database is accessible to every stakeholder in the organizations, is performing legitimately and that the necessary safety measures are in place to keep the stored data save. You need to master different technologies going from SQL and XML up to a more general programming language like Java.
The Business Analyst
This is probably the least technical profile mentioned on the infographic. However, the business analyst compensates for this lack of technical know-how with a profound understanding of the various business processes that are in place. A business analyst therefore often performs the role of the middle person between the business folks and the techies. Organizations searching for business analysts are companies like Uber, Dell, and Oracle.
Data and Analytics Manager
The data and analytics manager steers the direction of the data science team. This individual consolidates strong and specialized skills in a various arrangement of advancements (SQL, R, SAS, … ) with the social aptitudes required to deal with a group. It’s hard employment but if you feel up for the challenge, make sure to have a look at offerings from companies such as Coursera, Slack. Luckily, with an average salary of Rs 5.5 lakhs per annum, the financial compensation is in line with the high requirements.
How do I start my journey?
The latter is possibly the most prominent area where most of our students move to post the BIBA Program. The BIBA Program itself is a full stack profile offering 3 focus areas. The first being professionals (and students) with 0 to 3 years of work experience. This bracket generally opts for the Gold Module. The Platinum Module is ideal for professionals with over 3 years of experience in different domains other than Analytics but is looking at starting a career. Finally, the Imperia Module is ideal for those who are determined to make an impact in Analytics and move slowly slike into area Machine Learning, Artificial Intelligence, and Real-Time Data Visualisation techniques.