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

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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.

Related Article:

How To Upskill Your Career In Big Data Analysis

 

What Are The Skills Required For Data Analyst?

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What makes you inclined towards Data Science? Is it the interest in data? Or the shining career in this field? Or the impressive salary package? Despite the reason, you have made a wise choice. The course, Data Science has become the talk of the town for the past many years, and it reflects through the increasing demand for a skilled data analyst.

People are signing up for the Data Science courses in India. They believe the transition to a career in Data Science means stable employment and a high-paying salary once you have a good command of the Data Analytics course.

You don’t have to be a coding expert to learn and practice data science. This article will walk you through the five important skills required to become an in-demand Data Analyst professional. So, continue reading!

Role Of A Data Analyst:

A Data Analyst typically looks at large datasets and using their skill set, transforms data into a simpler and readable form that tells the story of a business. They integrate external data sources with internal company information to see where the company’s growth opportunities are located.

The analyst’s work on data highlights the key component that leads to high efficiency and improves business.

A Data Analyst Mainly Requires To Do The Following Tasks: 

  • Designing a database that suits different modes of inquiry
  • Optimizing database performance for easier use
  • Organizing data in the form of a dashboard that provide high-level summaries
  • Looking for patterns in large sets of data using statistical techniques or other methodologies.

Do You Wish to Become a Data Analyst? Master The Following Skills: 

Critical Thinking: 

A Data Analyst has to go through every day’s challenges related to data. The answer lies in data itself. To become an Analyst expert, you have to analyze the data differently. Apply all the basic concepts that you have been imparted during your Data Analytic course. The more challenges you solve, the better Analytic you become. So, continue to work on critical thinking, and gradually you’ll enjoy working with data.

Data Visualizations & Presentation:  

The two skills are closely associated. In data visualization, you’ll practice telling a story from compelling data to engage the audience or other officials you are presenting your data report.

The data presentation skills improve over time. At first, no one comes with an impressive result. Its consistent work makes you a skilled Data Analyst who presents the data effectively.

Programming Language:  

SQL (i.e., Structured Query Language) is the top-most database programming language a Data Analyst must know and practice. It gives access to data and statistics, which makes it an essential resource for data science.

R and Python are raising their ranks after their prominent use in Data Analysis. Python supports important tasks like collection, analysis, modeling, and visualization of data.

Other important programming languages to practice for a would-be data analyst are Java, Javascript, C/C++, MATLAB, Julia, SAS.

Machine Learning: 

The Data Scientist must be well versed with machine learning for quality prediction and estimation. The skill focuses on building algorithms designed to identify data patterns that improve accuracy over time.

Microsoft Excel: 

Creating a spreadsheet in excel is the basic and most traditional approach used for data representation. Although SQL is used to retrieve and present data in Data Analytics, knowledge of traditional and widespread tools is essential. Some industries may require you to work through excel along with the Data Analytics tool. So, it’s better to be well aware of the Microsoft Excel tool.

Conclusion: 

The skills mentioned above are important and make you confident to begin your career as a Data Analyst. Over time, you’ll achieve mastery of these skills and have a shining career with an abundance of opportunities.

So, are you ready to achieve your goal to become a Data Analyst? Imarticus Learning promises you to support by providing the best suitable Analytic course that fits your career needs.

You can contact us through the Live Chat Support system or even visit one of our training centers based in Mumbai, Thane, Pune, Chennai, Banglore, Hyderabad, Delhi Gurgaon, and Ahmedabad.