How To Become Data Analyst After 12th?

Data science, especially data analytics, is becoming the most desired job in the world with time. With multiple job positions and abundant opportunities, it is only wise to opt for data science courses after 12th or graduation. Students aspiring to be data analysts need to have a clear picture of how to become a data analyst and what data scientists do.

The first thing that an aspirant needs to know is that data analytics is a subset of data science, and hence knowing what is data science is paramount to learning what data analytics is.

Why a career in data analytics?

 

As data is becoming the most essential commodity to organizations worldwide, it is only wise to opt for a data science course in India. There are many benefits of data science courses and the most important one is that you can start a career in data analytics.

Business analytics courses will also boost the knowledge of a candidate in data analytics as it will help in understanding the domain better. Before understanding the requirements let us list the benefits of a job in analytics:

  • There are many job opportunities in the domain. Thousands of vacant positions are only waiting to be filled by qualified candidates
  • The salary of a data analyst is even higher than that of an IT professional
  • There are different domains within data analytics that can be a great option for career and salary growth
  • A challenging and stimulating work environment with a great work-life balance
  • An elite lifestyle

What are the requirements to become a data analyst?

You can opt for data science courses after 12th for UG. But, there are further options to start a data science course in India even after UG at PG or doctorate levels. You can also opt for certifications and diploma courses after the 12th.

At the postgraduate level, you can opt for a specialization in computer management and computer science to start your analytics career.

For pursuing a postgraduate program, a bachelor’s degree with a minimum of 50% marks is required, preferably in computer science or data science and from a recognized university.

Apart from educational qualifications, several soft skills like analytical and numerical skills are important for pursuing a career in data analytics. Further, a deep and thorough understanding of computer software and programming languages including querying languages (like Hive, SQL, and Pig), scripting languages (including Python and Matlab), statistical languages (such as R, SPSS, and SAS), and Excel is a must.

Besides, data analysts must possess problem-solving and interpretive skills to explain and present the process of data analysis and its results to decision-makers.

A data analytics course can help a student after 12th to bag high-paying jobs like data scientist, data engineer, database administrator, data analyst, and data architect. If you want to expand your job horizon, then you can even choose to do business analytics courses to end up in even higher positions with better commissions.

How Big Data Analytics Course Help to Achieve Better Data Management In Banking?

What is Big Data Analytics Course?

Banks create a huge amount of data regularly. The speed of data creation is slower than the speed of processing this information. The Big Data Analytics course can help the banks to diversify the data into Big Data that can be stored in a divided manner for better understanding and longevity.

Big Data Analytics Course focuses on the Collection and organization of the data and its conversion into such information that is worth analyzing and studying to draw meaningful conclusions. It educates about the ways to handle Big Data that cannot be used making use of the traditional methods.

Companies require specialized personnel of Big Data Analysts specifically for this job. Jobs in this particular field are shooting because of the usage of the internet and technology at large. This amalgamation of Finance and Technology can give rise to Fintech (Financial Technology)

What are the sources of Big Data?

Analysts can find Big Data whenever they want to make use of it. Some of the most important sources of Big Data are mention below:

  • Sensors- Used in Cars, Industrial machinery, Space, Technology and CCTV Footages, etc.
  • Social Networking Site- Facebook, Twitter, Instagram, Google, etc.
  • Transportation Services- Data from Aviation, Railways, Shipping, etc.
  • Online Shopping Portals- Data from Amazon, Flipkart, Snapdeal, eBay, etc.
  • Institutions- Data from Hospitals, Banks, Software Companies, Educational Institutions, etc.

Characteristics of Big Data

Big Data has been characterized by 3Vs. All the Vs stand for the following:

  • Volume- Data in Tera Bytes, Zeta Bytes, Giga Bytes, etc.
  • Velocity- The speed at which the data grows fast.
  • Variety- Includes the unstructured and Semi-structured data.

Advantages of Big Data Analytics Course in Banking

Big Data Analytics Course has been proved advantageous in numerous fields and industries but the Banking Sector has been able to make the best use out of it so far. The following points show how Big Data Analytics Course can help Banking Sector to achieve Better Data Management:

  • Boosting the Overall Performance

data analytics courses in IndiaAs far as the performance is concerned, both the employees’ and the bank’s performance can be analyzed through Performance Analytics. The Big Data Analytics Course helps to ascertain the loopholes in the performances that can be corrected in the future course of action.

  • Providing Personalized Banking Services to the Customers

The deposit or withdrawal of money in a bank account or the usage of bank cards at shopping sites, all are activities or information of the customers that a bank has. By using this information and the tools from the Big Data Analytics Course, banks can design some personalized services for their specific customers. This can benefit the banks by the way of increased customer loyalty.

  • Managing the risks to the Data

With a discreet vision of the market, banks can regulate their policies or can bring changes in their framework. If the return from the market keeps running low, after analyzing, banks can raise the loan interests for the customers in that respect.

To avoid frauds, banks can turn down or withdraw payments from questionable Investments in the market.

  • Sentiment Analytics

Under this, the banks analyze the data through social media and understand the patterns and behaviors of the customers on social media platforms. This helps to know the sentiments of people about a brand, firm, Company, or product.

Conclusion

Anyone aspiring to be a Big Data Analyst must take up a  Big Data Analytics Course. Considering the current scenario where every company deals with its data through Information Technology, the use of Big Data Career is on the rise.

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