A Big Data professional works with a large amount of data “ sometimes the quantity of data reaches exabytes. Professionals use sophisticated tools to work with such a large amount of data.
Working knowledge of tools comes handy and can be learned over time in this domain, but analytical and problem-solving skills are crucial to excelling in a Big Data career.
Where should you start?
Start by getting a bachelor’s degree. Technical degrees often help and are preferred by employers too. Taking economics, statistics, computer science, and engineering will improve your analytical capabilities and put you on the path to become a Big Data professional.
Moreover, you should pay attention to solving numerical problems and complex operational issues using data to improve your problem-solving skills. What’s next?
Get a Big Data Certification
Big Data industry has matured. Unlike a few years ago, the industry now has established solid processes around data collection, cleaning, and analysis, which are major tasks for Big Data Analysts. Getting a certification from a globally recognized institution will validate your skills and pave way for better job opportunities in the industry. World-renowned tech corporations “Cloudera, DASCA, Dell EMC, Amazon among others offer Big Data certifications.
Some popular certifications you can go for are —
1. Amazon Web Services (AWS) Certified Big Data
2. Associate Big Data Analyst by DASCA
3. Cloudera Certified Associate (CCA) Data Analyst
4. Dell EMC’s Certified Associate ( DCA-DS)
These are entry-level certifications which will increase your chances of getting your first Big Data job. While pursuing your degree, make sure you take these certifications or short-term courses to further increase your chances of employability.
Excel at data science skills
Further, you will need to excel at multiple skills to do better in a Big Data role. Following are the skills, you should focus on —
1. Mathematical/ statistical skills — These skills form the foundation to do well in Big Data Analysis. A major portion of the work analysts do is number crunching. Several statistical methods are used to perform exploratory data analysis can be performed well. Mathematical concepts such as probability, integration, differentiation, etc. are used.
2. Programming skills “ Programming is a major part of the work Big Data Analysts do. You are expected to know a handful of programming languages including R, Python, SAS, Java, and MATLAB. Understanding these languages is important. Understanding programming logic is way more important. Data analysis and other operations are carried out using programming. Most Big Data tools like Hadoop, Spark, Pig, Hive, etc. are based on Java. The more proficiency you have, the better chances you have at becoming a good analyst. This language holds the key to your entry into a Big Data career.
Other than these languages, working knowledge of NoSQL, Databases like Cassandra, MongoDB, etc. will make you a valuable analyst.
3. Visualization
The ability to explore data and extract insightful information is one part of an analyst’s job. Analysts are expected to visualize insights gathered by them to facilitate decision-making. This requires knowledge of visualization tools like Tableau, ggplots, among other tools.
4. Business acumen “ This is rarely stressed upon, but a Big Data Analyst must understand business. You should understand a business inside out before you can turn to provide insight for the business. How business functions, key stakeholders, sales operations, and other business operations should be at your fingertips.
Final note
Data science jobs are increasing, as companies are increasing their investment in data science projects. At the same, it is getting competitive to find a data science role. Opportunities in data science are good, but competition is fierce. Grab a laptop, start practicing.
