Big Data Analytics

Big Data is the need of the hour today for companies in the race to overcome their peers. No organization can survive without analyzing current and future trends. We are currently in a data-driven economy with a need for data analysis on product information, services, buyers, suppliers and consumer preferences. This involves complex applications with elements such as predictive models, statistical algorithms and what-if analysis for scenarios comparison.

Comprehensively, data-analytics technologies and techniques provide a means to analyze data to get more information to help organizations make informed business decisions. Business intelligence (BI) queries and Business Intelligence Reporting Tools (BIRT) pull data from many different sources and answer basic questions about business operations and performance.

Big data analytics through specialized systems and software can lead to positive business-related outcomes:

Big Data Analytics applications allow data analysts, data scientists, predictive analytics, statisticians and other professionals to correctly analyze volumes of structured transaction data, plus other data that is often left untapped by conventional BI and analytics programs, like Internet Clickstream data, web server logs, social media content, text from customer emails and survey responses, mobile phone records, and machine data captured from IoT.

Big data gathers data from different sources, making it of crucial for the insurance industry. That is how you get random calls from an insurance provider enquiring if you want to get insured. It happens because various consumers are tracked feeding this data in the cloud, which helps the providers to create target customers.

Big data applications in healthcare provides preemptive and wearable trackers which transmits the data of patients to physicians, helping them analyze the patients and create a database that can be used in the future.

Big data helps banks in getting information about their customers, their credibility and credit scores as well.

It also helps in:

Big data analytics is extensively used for higher education. The University of Tasmania in Australia, with over 26000 students, uses a Learning and Management System for many things, one of them being tracking a student’s log hours on the system, the time is spent on different pages, as well as the overall progress of a student.

It helps in the efficiency of a smarter transportation supply chain, improving customer experiences and in lowering costs. US Express, an American Logistics company has already installed 1000 sensors in each truck to monitor its movement, which helps receive feedback of every kind.

Big data technologies in the retail industry reveal patterns and trends of consumer preference on the basis of a greater understanding of consumer shopping habits and creates recommendations based on their history of purchase, resulting in a customized shopping experience.

Big Data can be used for public management and governments can have easy access to relevant information essential to decision making and allow them to monitor their decisions and make timely changes if required. It can ascertain the country’s population, the trends in GDP, mortality, fertility and birth rates. Big Data models can also help farmers with recommendations on agriculture and cultivation. Trade flow can also be monitored from and in the country.

AAROGYA SETU- The recent example of big data management is of this app, which is a is a government initiative to ensure safety for its citizens from COVID-19 infection. This application connects Indian health services to all the app users across India. It can notify a user through contact tracing, of any high-risk areas in proximity to him or her.

What skills do I need to become a Data Analyst?

Programming Language

First and foremost, to become an expert in data analysis, you must have a solid understanding of at least one programming language. However, having command over more than one language makes you more versatile and increases your chances of getting a good salary. Some of the languages used by data analysts are python, R, Excel, and SQL. The trend keeps changing with technology, but the logic remains the same. It would be best if you focused on algorithms and fundamentals behind them to stay up to date.

Communication Skills

Insights that are gathered from data analysis are consumed by several departments within the company to aid decision-making. Hence, it is of utmost importance for a data analyst to convey their findings in a manner that is easy to understand for a vast audience. Strong presentation and communication skills are the keys to success.

Database Knowledge

Being a data analyst, you may have to work at the backend wherein you design a data warehouse to store a huge chunk of data from multiple sources in one place. You must possess a strong database and database query language knowledge to query the database to pull information from different tables to perform further analysis.

Data cleaning and interpreting

One should possess a strong knowledge of data mining and advanced statistical techniques to clean and extract unstructured data.

Analytical thinking and problem-solving approach

Thinking out of the box, keeping a creative mind, and having a problem-solving approach are key attributes of a good analyst. It helps you ask relevant and interesting research questions and build good repo among key stakeholders of the company.

Understanding the concepts of big data analytics and getting hands-on practice on tools can help become a Data Analyst, Data Integrator, Business Analyst, Data Scientist, Solution Architect, or a Data Architect.

With a big data course, available at no cost on FutureSkills Prime, learners can get an introduction to the foundational concepts of big data. Access high quality, industry-aligned courses that are validated by SSC nasscom and recognized by the government of India.