Big Data Analytics: A Skillset in Demand

Abundant global career opportunities in Big Data Analytics :

According to the US Bureau of Labor Statistics, with 11.5 million jobs predicted by 2026 in big data, the demand for experienced professionals is already far outstripping the supply. People with analytics expertise are in high demand and market leaders such as Amazon, Google, Facebook (Meta), and Microsoft are offering huge salaries to talented professionals.

As a domain, big data analytics is moving fast. However, there are a core set of skills you need to kick-start a career in this field.

SQL-

You need to get SQL (Structured Query Language) under your belt before you can start your big data analytics journey. Professionals with this competency use SQL to manage data, connect multiple databases, and build or change database structures; an absolute must for working in the big data domain.

Microsoft Excel-

You may be surprised that something as ubiquitous as Microsoft Excel is a core skill for working with big data, however it is widely used to provide quicker analytics through the use of macros and VBA lookups.

R and/or Python Programming-

R and Python are powerful statistical programming languages used to analyze and produce predictive analytics from big data sets.

Data Visualization-

As a big data analyst, one of your responsibilities is to communicate your findings in a meaningful and accessible way. To achieve this, you need to know how to present a compelling story backed by data. Learning how to visualize data to effectively get your message across is critical for moving a big data career forward. Big data analysts therefore use eye-catching, high-quality charts and graphs to present their findings, and many will enjoy rewarding careers in enterprise-sized organizations.

Critical Thinking-

However, success isn’t based solely on technical knowledge. Strong soft skills are important too. To know how to use data to glean valuable insights means knowing what questions to ask in the first place. To succeed as an analyst, you must think like an analyst, and it’s the role of a data analyst to uncover and synthesize connections that are not always clear initially.

What kind of job roles can you aspire to in big data analytics?

Today, companies of all sizes rely on data to make better decisions. This has catapulted the importance of big data analysts, and companies are willing to pay high salaries even for entry-level professionals.

Did you know that the national average salary for a big data analyst is approx. ₹7,00,000+ according to Glassdoor! This means that job opportunities in the field go beyond the tech and digital spaces; they now exist across business. Great examples include:

Data Analyst-

Data analysts are in great demand, they perform a wide range of tasks, from acquiring massive amounts of data to processing and summarizing it. They use predictive analytics to analyze current and historical data and make predictions about the future.

Business Analyst-

Business analysts are responsible for identifying business needs, key gaps, challenges, and the potential impact of a solution or strategy. They use predictive and prescriptive, as well as descriptive, analyses to transform complex data into actionable insights that users can easily understand.

Data Scientist-

Data scientists work with a business to discover actionable insights from data and communicate their findings. Along with predictive analytics, they use programming languages to analyze large amounts of unstructured data to derive insights and design future strategies.

Data Engineer-

Information is designed, built, and managed by data engineers. It is their responsibility to make sure that an organization's big data ecosystem is error-free. They keep track of problems, deal with them, determine when to scale up, guarantee seamless integration, and "create human-fault-tolerant pipelines.

How do you get started in big data analytics?

Data analytics is such a broad reaching field that it’s possible to build up your skill set and gain experience as you work and learn. To achieve this, you need to:

Develop Your Foundational Knowledge-

If you are new to the world of data analytics you should start by developing foundational knowledge to gain entry-level job-ready skills. A good starting point is to become proficient in skills such as SQL, Microsoft Excel, Data Visualization, and R or Python programming languages. Plus, you should also work on your critical thinking skills to ensure you can develop your career further.

Work With Big Data Projects-

To move your skills forward, it’s worth looking for courses that include hands-on projects using real data sets. This will quickly build your appreciation of what data is about and what its value is in the real world. A great example of such a course is Predictive Modeling Fundamentals I. This course gives you advanced analytics capabilities spanning ad-hoc statistical analysis, data mining, text analytics, entity analytics, optimization, real-time scoring, machine learning and more.

Get an Entry-Level Data Analyst Job-

Once you’ve begun to develop your portfolio of practical experience and hands-on projects, it’s time to polish your resumé. Once that is ready, you can start applying for entry-level data analysts' jobs on LinkedIn and other related platforms.

Conclusion

About FutureSkills Prime: FutureSkills Prime started as a platform with a vision to upskill/reskill every Indian citizen in emerging technologies. A joint initiative of Ministry of Electronics and IT (MeitY) and National Association of Software and Services Companies (NASSCOM), it brings a synergy between the Government, Industry, Academia towards the eventual goal of making India a digital talent nation. A novel skilling program, it incentivizes the cost of the eligible course(s), providing authentic and accredited certifications acceptable in the industry.

 

Written by Simran Garg, Technical Specialist, SkillUp Online