The increase in online usage for everything has resulted in the accumulation of data all over. The term is known as Big Data. Big Data is everywhere and there is an urgent need to collect and preserve this huge amount of data.
There is another term known as Big Data Analytics which is used to improve business, decision making and offers a bigger edge over competitors.
Now you all will be wondering what does this Big Data mean?
Large volumes of data which is both structured and unstructured, that bombard a business on day to day basis is known as Big Data. Data is everywhere but how to capitalize this data is the next big question for the organizations.
Do you want to learn the technique of capitalizing this data? Do you feel you can manage the heaps of data? Think about it. If yes then a bright career awaits you. Because organizations want candidates like you to manage the pile of data. So be ready to become the future data scientist.
Is the term Big Data New? Haven’t heard about it earlier.
Yes, the term Big Data is comparatively new for all of us. But the act of collecting as well as storing a big amount of data is an old practice.
The amount of data created and stored on a global level is huge and it keeps growing. As a result, it means business organizations are in need of people who know the technique of managing data. They need to know how to successfully utilize the raw information that flows into their organization.
The above description makes it clear that Big Data holds significance in today’s world. You probably won’t be able to manage your business without managing the Big Data. The significance is not related to how much on data you have but what to do with the data.
You can get data from any source and analyze it to find answers:
- It enables both cost and time reductions
- Smart decisions
- New product development and optimized offerings.
You can also combine big data with high powered analytics and accomplish the business-related task such as:
- You can recalculate the entire risk portfolios
- Monitor customer buying habits and generate coupons at the point of sale
- Determine the root cause of defects, failures in real time
- Detect fallacious behavior before it affects your organization.
Top colleges for Data Scientist:
- Indian School of Business (ISB), Hyderabad
- Great Lakes Institute of Management, Gurgaon/Chennai/Pune/Bangalore
- Indian Institute of Management (IIM), Bangalore
- MISB Bocconi, Mumbai
This is just a list of few colleges. Find for yourself the best college and get admission into it.
Education Qualification needed for Data Scientist:
If you want to become a data scientist then you require a degree in Maters’s, MBA or Ph.D. Some companies also accept data scientist with undergraduate degrees in analytical concentrations. For instance, Computer Science, Statics Management, Engineering, Hard Sciences, etc.
Certificate courses in database management, predictive analytics, business management are preferable. The only necessary education condition for a candidate to become a data scientist is Mathematics. Hence, you need to be a student of math.
How to become a Data Scientist
- It is advisable to complete your higher studies in science subject with math as the core subject from a recognized board like CBSE.
- After completing your higher studies, take an undergraduate degree, master degree or even the certification as mentioned above. Ensure you do it from a reputed university.
- Gain technical skills in Python, Java, etc. and also business skills.
- Build your portfolio by taking up internships first, build a well-written resume.
- Apply for jobs in an organization that requires data scientist like you.
These skills can land you Big Data jobs:
- Apache Hadoop: You need to be aware of Hadoop components such as Flume, Oozie, MapReduce, NoSQL: Pig, Hive, Yarn are high in demand.
- Apache Spark: Technical expertise is required in order to run the program
- NoSQL: NoSQL databases are the source of data crunched in Hadoop and location for application changes put in place after insight is gleaned from Hadoop
- Machine Learning and Data Mining: Machine learning technology can be used to build as well as train predictive analytic apps such as classification, personalization system.
- Data Visualization: One skill that is a must as big data can be tough to comprehend and all eyeballs must be on data.
- Creative and Problem Solving: You may learn as many analytics and tools but you need to have a creative mind that is able to think through a situation.
Responsibilities of a Data Scientist:
- Extract a huge amount of data from multiple internal and external sources
- Conduct research and frame open-ended industry questions
- Explore and examine the data from different angles to determine hidden weaknesses, trends or opportunities
- Devise data-driven solutions for problems
- Invent new algorithms to solve problems and build new tools for work
- Recommend cost-effective strategies to change the existing strategies.
- Employ high and sophisticated analytics programs, machine learning for use in predictive and prescriptive modeling
Every company has different takes on job tasks and different takes on how to manage big data. Your job description and handling of the task may vary accordingly. Some organizations need data analyst while some need persons skilled in machine learning and data visualization.
Job Titles offered when you become a data scientist:
- Big Data Engineer
2. Big Data Analyst
3. Big Data Analyst Architect
4.Big Data Business Consultant
5. Analytics Associate
A few more can be added to the list depending on the organization.
Sectors you are expected to land a job in:
The salary of a data scientist varies according to the job title, organization. Since the industry is in demand you can expect handsome salaries at the start. However, the salaries you can get may start from a minimum of Rs20,000 or more.
This is the end of the journey of a data scientist. Edu4Sure is a career counseling platform where you can read articles related to education. Stay connected.