Today, majority of companies realize the value of data-driven business strategies. They require talented individuals who can decode and make sense of the constant feed of information. The U.S. Bureau of Labor Statistics opines that the job market for data analysts will grow 23% by 2032.
By taking a PG course in data analytics, you will be opening yourself up to an unimaginable ocean of resources and opportunities. You can look for enrollment in the IIT Bombay data science course or other reputable institutions.
Key Skills Required for a Postgraduate in Data Science
Here are the essential skills needed to be a data analyst:
1. SQL
One of the most important languages that you need to know is SQL or Structured Query Language. It is the ubiquitous industry-standard database language, which is also possibly the greatest analytical skill that data analysts can have. Business analytics courses in India can help learning on how to utilize SQL. Many experts can consider this language as the “graduate” version of Excel. It has a huge benefit: it can handle large datasets that Excel simply can’t.
Every single organization requires employees with knowledge of SQL for managing and storing data, relating multiple databases, or building/changing those database structures. Every month, companies post thousands of job opportunities that require SQL skills. If you want to work with Big Data, then the first step should be to learn SQL.
2. Critical thinking
The first step of data analysis is to figure out what to ask in the first place. In most cases, this can be quite tricky. If you want to succeed as an analyst, then you will have to think like one. It is the responsibility of a data analyst to synthesize those connections that are not always so clear.
There are several tips you can try to improve your critical thinking skills. Do not get carried away with complex explanations. Instead, ask yourself some very basic questions about the issue that you’re dealing with while searching for a solution.
3. Presentation skills
You need great presentation skills if you want to be a good data analyst. However, presenting isn’t everyone’s forte, and that is fine. Even seasoned presenters can and do get nervous sometimes. As with pretty much anything else, practice is the key to getting it correct.
4. Microsoft Excel
Something that a lot of data analytics students do not know is that advanced Excel methods, such as writing macros and making use of V-lookups, are widely used for executing smaller lifts and quicker analytics. If your job is at a startup or a lean company, then the first version of your database can be in Excel. This tool has remained a mainstay for a lot of businesses in every single industry, so it is compulsory to learn it.
5. R or Python
Anything that can be done by Excel can be done 100 times better by R or Python—and much faster. Both of them are powerful statistical programming languages that are used to perform predictive analytics on big datasets. Not to mention that they’re both industry standards. To be an effective data analyst, you will have to go way beyond SQL and master at least one of these.
After reading this, you may be questioning, Which one should I learn? Well, both these languages are open source and completely free, and employers normally don’t care about which language their employees are using, as long as their analyses are accurate. However, it must be said that some analysts prefer R over Python for exploring datasets.
6. Data visualization
Data visualization is all about being able to tell a compelling story and getting your point across. And you need to do this while keeping your audience engaged. If your findings cannot be easily and quickly identified, then you’re not going to be able to convey your idea to others. Data visualization can have a make-or-break effect.
Why Choose a Postgraduate Course in Data Science?
Here are three main reasons why you should pursue a PG course in data science:
- It’s in high demand: There is a growing demand for data scientists in all industries, especially the tech industry. According to statistics from the US Bureau of Labor Statistics, the hiring of data scientists is expected to grow by 35% from 2022 to 2032.
- Data scientists earn good money: Data scientists are paid very well across industries. Being able to decode complex data is very highly valued in today’s world. This career path not only pays a lot but also offers exciting opportunities for innovation and growth. Like, data scientists play a huge role in shaping the future of businesses and industries.
- Job opportunities in all kinds of businesses: The field of data science is blooming and blowing up, creating diverse opportunities. The flexibility of the field lets you transition flawlessly across industries such as healthcare, technology, and finance.
Conclusion
If you’ve read this far, we are guessing you’re convinced by now. Dive into the world of data analytics and make the best decision of your life. Go ahead and fill out that application form for the college or online course you have had your eyes on for a while. Once you get the hang of it, you will find that the sailing is quite smooth.
Be sure to thoroughly check the credentials of the institution you’re applying to. Before you go ahead, check whether they offer some additional courses, such as certification on cloud computing. You should also check for reviews and the qualifications of the faculty and placement records. If possible, contact some of the alumni and ask them about the institution. Best of luck for your career and life ahead.
Related Articles:
- Integrating Data Analytics into Business Administration Programs
- Top 5 AI Engineer Skills You Need to Know
- Exploring the IT Job Market: Key Roles to Watch Out For
- SAFe Training: Skills to Excel in Scaled Agile Framework
- Top 10 Must-Have Skills for IT Professionals
