Much has been written about ‘data is the new oil’ and ‘data science’ is one of the hottest emerging technology areas. Yet many of the aspirants who would like to get into this sector have many questions about the skill requirements, opportunities in the industry, job openings etc. In this article, we shall try to answer a few of the commonly asked questions and clear the ambiguity around the required skills and job roles.

● Almost 48% of analytics job openings are looking for a B.E./B.Tech graduate degree in the incumbent.
● 18% analytics job openings are looking for a postgraduate degree which is not MBA or M.Tech. This is a decrease from 26% a year ago.
● 8% of analytics jobs specifically require an MBA/PGDM degree.
● Just 13% of recruiters are looking specifically for graduates with no/ non-B. Tech degrees, up from 10% last year.
So here’s the question in everyone’s mind that then how do a fresher crack this industry?
I am interested in getting into data science as a career. What do I need to learn?

In the area of data science, broadly understanding of three areas are required:
1. Statistical /machine learning techniques & algorithms
2. Computing tools/languages
3. Business understanding

For the first two areas, skills need to be built through learning and training.
Business understanding is a function of exposure in the business and industry.
One can prepare by learning through examples, case studies, projects etc.

It will lead you to become an expert in data science. A data science expert is someone who can analyze huge amount of unstructured and structured data using advanced tools and machine learning algorithms to solve a real-world business problem.

Skills that are needed to get an entry-level job in this field.
1. Basic of statistics.
2. SQL
3. Knowledge of basic problem-solving.
4. Having a portfolio of projects.

In statistics, you need some basic knowledge like
1. Sampling.
2. P-value.
3. Hypothesis testing.
4. Experimental design.

Try to implement these concepts using python on small data sets, so that you can tell anyone that you are you have some practical knowledge. By doing this you will have an edge over other candidates who may just have a theoretical understanding of these concepts.

SQL will help you
1. To retrieve data from relational database
2. It stores data in your databases.
Many data analytics professional spend their time on writing SQL scripts.
You may get various job descriptions like data scientist, business analyst or big data this might be confusing for you you but do not get confused by different job titles by companies providing.
In reality, they go in the path of data analytics after B.Tech graduation in this

Python, R, MySQL or Excel are mandatory skills for this job. They are also looking for candidates who have a good knowledge of the algorithm and if you know the basic concepts in machine learning, then it would be like “icing on the cake”.

What are the job roles in data science?
Data Science Aspirants wonder about the kind of roles that are there in the industry for them. There are many roles and opportunities in organizations. It is pertinent to remember that data science or big data analytics can not be done with one person. It is a team that works on such projects and there are various functions
and roles that are needed. Let us decipher a few of such job roles and designations that you may come up with.

1. Data Scientist
A data scientist is like the master chef! He is expected to work with big sized and complex data to derive meaningful patterns/visualization for the business to benefit. He should know statistical and machine learning
algorithms, how to manage complex data sources as well as have a strong understanding of business. A tall order of requirements from a single person but a data scientist adds tremendous value to an organization’s data science and analytics journey.
2. Data Analyst
Data Analysts are curious people who have an analytical mind. They sift through tons of data to find out if there is a relationship by running statistical analyses or find out the root causes of an event happening, like, why the sales of a division in a geography is going down for a product line or developing a model for predicting fraudulent claims for a health insurance company.

3. Data Engineer
Data Engineers are the people who love to play with large scale databases and systems and typically come with a software engineering background. ln, a data science context they operationalize the analytics model developed by data scientist and data analyst team and, automate, deploy and make it run for clients/business.

4. Data Architect
In the context of a large organization with disparate sources of data, the role of data architect is very important. He creates the blueprint and map for data sources and data mart which is crucial for any data science or analytics
5. Business Analyst
A business analyst, on the other hand, is more business savvy and looks at problems from the angle of business rather than the technicalities of data, algorithm, architecture, management etc. He is the one who will have a
better business/domain knowledge and uses data to support business processes. He may use different visualization and analytics tools/products for his findings and recommendations. Needless to say, all the above may start at entry-level and grow to senior levels and, also there could be other roles and nomenclatures that you
may come up with like data integrators, database administrators, data warehouse specialists, big data consultants etc. and there are always some overlaps in functions among these roles. NASSCOM has identified six areas of
specialization in the Big Data Analytics domain that is expected to drive growth in the sector: business analysts, solution architects, data integrators, data architects, data analysts and data scientists.

Where are the job opportunities?
The scenario for data science jobs for freshers and experienced professionals in India is constantly evolving.. Companies are looking to hire professionals who are looking to hire professionals who are well-trained with new tech concepts such as analytics, big data, data science, artificial intelligence, and machine learning among others.

● Around 62% of analytics requirements are looking for candidates with less than 5 years of experience.
● 17% of analytics jobs are for freshers.

Opportunities in data science are no more limited in only the technology or consulting companies.
It is finding greater acceptance in traditional businesses as the interest increases in leveraging data for decisions. The number of opportunities of data scientists and data engineers can be found in companies like Uber, Amazon, Ola, Google etc. as their business models are heavily data-dependent as well as in consulting companies like PWC, KPMG, Deloitte etc.

10 leading organizations with the most number of analytics openings this year are – JPMorgan, Accenture, Microsoft, Adobe, Flipkart, AIG, Ernst & Young, Wipro, Vodafone & Deloitte.
Then there are user companies in healthcare (hospitals, pharma etc.), retail, telecom, utility, BFSI (banking, financial services and insurance) etc. where there is a large number of opportunities as data analysts, business analysts, reporting specialists etc. The startup companies are also coming up with new product and services using analytics and artificial intelligence which are creating new job opportunities.

Top designations advertised are Analytics Manager, Business Analyst, Research Analyst, Data Analyst, SAS Analyst, Analytics Consultant & Statistical Analyst, Data Scientist.

l am a fresher. Where do I start?

Innomatics Technology Hub offers quality-driven Data Science courses in
Hyderabad, India. We at Innomatics provide very comprehensive courses at
Hyderabad. People from different part of cities come across here to get knowledge
in specific domain i.e Data Science. We Innomatics provide hands-on an experiment

with 100% of placement once you are done with your course.

Nowadays every fresher graduate is interested in analytics as an industry. Why is
everyone moving towards data analytics jobs? Why there are more interested in
this field?
Because analytics is one of the fastest-growing industries in the world today. The
demand so vastly surpasses the supply of data analysts that companies find it
difficult to hire trained professionals in analytics. Innomatics Technology helps
freshers as well as experienced candidate with highly qualified trainers to help you
land on a data science job with full placement support. Innomatics will also explain
analytics concepts in a simple way to you, while also demonstrate how these
concepts are implemented in a series of projects, which will make your learning
process effective, easier and hassle-free.

Can IT professionals be reskilled for these new-age job opportunities?
With the rising demand for data-driven technologies across the globe, IT companies
are reskilling their large pool of IT professionals in these new-age technologies like
predictive analytics, machine learning, data mining, deep learning, cognitive
analytics, artificial intelligence (A), IOT based analytics etc. Best SAS, SPSS, Cognos,
R, Python, IBM Watson, Hadoop, Spark etc., – proprietary or open
Apart from training aspirants and practitioners incorporates in business
analytics, big data, data science etc., Innomatics also offers new courses like
cognitive analytics using IBM Watson, machine learning with Python etc. Many of
our students have successfully moved on from being an aspirant to successful
practitioners in the industry.
Startups and young organizations are also using these new technologies to come up
with disruptive solutions and business models. This is also adding to the
opportunities for existing professionals for lateral shifts.