Want to Become a Big Data Analyst? Know the Skills and Education Required

Data analytics is a multidisciplinary field that requires an understanding of IT, business analysis, and project management. And to make a career in this field, aspirants must possess certain specific skills and knowledge. Read further to learn more about what it means to be a big data analyst. Additionally, learn all about the essential skills required and how to get ahead in the world of data analytics.

What Does a Big Data Analyst Do?

A data analyst is responsible for gathering, cleansing, and analyzing data sets to address specific questions or solve problems. Given that today, nearly every industry deals with big data, such professionals are employed in various sectors, such as business, finance, science, medicine, and government.

What are the Most Important Skills for a Big Data Analyst?

Here are a few prominent skills that every big data analyst must possess.

1. Analytical Skills

Strong analytical skills are crucial for becoming an expert in big data. Therefore, to dive deep into complex data, one must be proficient in mathematics and possess relevant scientific skills. Additionally, familiarity with analytics tools in big data can enable one to address challenges in this field effectively.

2. Data Visualization Skills

For aspiring big data professionals, enhancing their data visualization skills are crucial. It’s important because it equips them to present data effectively and convey the intended message clearly. Therefore, proficiency in visualization skills is highly valued in this field.

3. Programming Skills

Expertise in programming languages such as Scala, C, Python, Java, and others can benefit aspiring big data professionals. Moreover, to excel as a big data professional, one should understand fundamental concepts such as algorithms, data structures, and Object-Oriented Languages (OOL). Also, quantitative and statistical analysis skills, including coding abilities, are crucial in the big data industry.

4. Problem-Solving Skills

The ability to solve problems effectively is a valuable trait in the field of big data. This is because the unstructured nature of big data presents unique challenges that require creative problem-solving skills. Therefore, a big data professional should be able to think critically, analyze complex data, and arrive at creative solutions.

5. SQL Skills

Structured Query Language (SQL) serves as a fundamental base in this current era of big data. SQL is, therefore, beneficial for programmers working with big data technologies. Additionally, familiarity with SQL can enhance their ability to derive meaningful insights from large and complex data sets.

6. Data Mining Skills

Focus on gaining skills and experience in data mining technologies and tools. By learning from top data mining tools such as KNIME, Apache Mahout, Rapid Miner, and others, professionals can develop the most sought-after data mining skills.

Also Read: Data Analyst: Jobs and Salary in India on 2023

What Education or Training is Required to Become a Big Data Analyst?

To become a big data analyst, one must have the relevant academic qualifications and skills. While that is certainly important, it is also essential to continually upskill to stay up-to-date with the latest industry trends and excel as a big data analyst.

1. Bachelor’s Degree

One needs a Bachelor’s Degree in Computer Science, Finance, Economics, Statistics, Math, or any related field. As with any degree program, this, too, typically takes three to four years to complete. However, the duration may vary depending on the learning institution and the curriculum.

2. Master’s Degree

As with any field, an advanced degree offers more job opportunities and helps with career advancement. Moreover, it exposes the latest knowledge, trends, and analytical tools from the industry. A Master’s Degree in Data Analytics or Data Science, or a related field can further help in career advancement.

3. Certificate Programs

One can also enroll in certificate programs as an alternative to a degree. Furthermore, a certificate program offers an inclusive overview of the subject in a shorter period of around 12 months.

What Kinds of Industries Employ Big Data Analysts in India?

In India, big data analysts are employed across various industries due to the growing demand for data-driven decisions and insights.

1. IT and Software Services

IT and software companies are at the forefront of leveraging big data for activities such as business intelligence, customer analytics, and product development.

2. E-commerce and Retail

E-commerce and retail companies rely on big data analytics for several reasons. This includes analyzing customer behavior, optimizing pricing and inventory, and improving supply chain management.

3. Banking, Financial Services, and Insurance (BFSI)

In this industry, data analysts work with big data for risk management, customer segmentation, investment analysis, and fraud detection as well.

4. Healthcare

The health sector uses big data analytics to analyze patient data, optimize treatment plans, and improve healthcare outcomes.

5. Telecom and Communication

Telecom and communication companies utilize big data analytics for various reasons, including customer analytics and network optimization.

6. Manufacturing and Automotive

Big data analysts are required by these industries for activities such as process technology, supply chain optimization, and product quality improvement.

7. Government and Public Sector

Government and public sector organizations use big data analytics for policy-making, public health monitoring, and fraud detection.

8. Media and Entertainment

Finally, there is also the world of entertainment and media that leverages big data. Analysts in this field work with big data for audience segmentation, content recommendation, and personalized marketing.

What are the Best Tools and Technologies for Big Data Analysis?

1. Apache Hadoop

Apache Hadoop is a popular Java-based open-source platform that processes and stores large-scale data.

2. Cassandra

Cassandra is a highly scalable and distributed NoSQL database designed to handle large amounts of data across multiple nodes and clusters. It provides high availability, fault tolerance, and horizontal scalability, which makes it suitable for big data analysis in real-time applications,

3. Qubole

This cloud-based big data platform provides a managed environment for processing and analyzing large data sets. It supports popular big data processing engines such as Apache Spark, Apache Hadoop, and Presto.

4. Xplenty

Also a cloud-based data integration platform, Xplenty allows users to Extract, Transform, and Load (ETL) data from various sources.

5. Apache Spark

This open-source data processing engine provides fast and distributed data processing for analysis.

6. MongoDB

MongoDB is a widely used NoSQL database that is known for its flexibility and scalability. It provides a document-based data model, thus allowing the storage of unstructured and semi-structured data,

7. Apache Storm

This distributed stream processing framework is designed for processing data streams in real-time.

8. SAS

Then there is SAS, a popular commercial software suite for advanced analytics and data management. It provides a wide range of tools and capabilities for big data analysis.

9. RapidMiner

RapidMiner is an open-source data science platform that provides a visual interface for designing and executing big data analytics workflows.

What is the Average Salary Based on Different Roles and Levels?

The salary of a big data analyst starts at ₹2,65,000 annually for aspirants with a year of experience. However, it can increase up to ₹16,60,000 per annum for those with experience of nine years.

Join Emeritus to Accelerate Your Big Data Analytics Career

Big data analysis is a growing field with ample opportunities for career advancement. Taking data science courses can help expand your skill set, knowledge, and expertise. Emeritus’ data science courses provide the necessary qualifications and skills to pursue higher-level roles and responsibilities in your career.