As recession is coming into the picture followed by the recent COVID pandemic, there are a few jobs whose demand is here to stay. Yes, I am talking about analytics. Data Science may seem a little intimidating at first, mainly for the beginners. Many questions are going around in the minds of people looking for a career in analytics. Which tool should I start with – R or python? Are there any big data certification of data analytics certification programs? How do I code? Is it all about coding? Can I be a data analyst? Well, let’s go step by step to try and understand a few basics to have a clearer vision of the path. Big Data Hadoop training and big data certification course will give you an insight into the industry.
Learning Of Blog
- Data Analyst – Definition, Roles, and Responsibilities
- Eligibility To Become a Data Analyst.
- Develop Skills To Become a Data Analyst
- Certification Courses
- Choose a Mainstream Coding Language or Tool to Learn
- Live Projects and Internships in Analytics
- Work on Your Communication Skills
- Work on Your Presentation Skills
- Teamwork and Networking
- End Notes ForTthe Budding Data Analyst
Data Analyst – Definition, Roles, and Responsibilities
First, let’s answer Who is a data analyst? What does he or she do?
A data analyst is a person who converts data into information, then analyzes this information to obtain insights, and finally turns these insights into relevant business decisions.
The following points mention the responsibilities of a data analyst –
- Acquiring Data – Data can be obtained from the internal database systems, purchasing third party data, ethically extracting online data, or any other primary and secondary sources available.
- Data Interpretation – It includes data cleaning, transformation, and manipulation in the required format to obtain relevant information.
- Data Analysis – It involves data exploration, using statistical methods, developing models, and algorithms to get expected results.
- Reporting – Creating dashboards, visualizing data, and apply business intelligence to show findings and insights for the business problem at hand.
- Enabling business decision making – Work with managers, business partners, or clients to identify, prioritize, and solve business problems by making data-driven decisions. It also involves improving the processes, ideation, as well as exploring new opportunities for the business.
Eligibility To Become a Data Analyst
Now that we understand what a data analyst is and what he or she is required to do, let’s know the eligibility criteria. The most important criterion is to possess strong analytical skills. The person should be able to collect, organize, transform, analyze, and disseminate relevant information from vast data. You cannot afford to fear numbers or probabilities. Knowing and doing math is essential. Hence, knowledge of statistics, data models, and statistical packages is required. Strong knowledge of SQL, or SAS, and Excel is a must. Knowing ETL frameworks, javascript, business objects, coding languages like R, python, HQL, etc., is a plus. Next, comes the ability to report, communicate, create presentations, and being adept at queries, and required re-iterations. A data analyst needs to code, develop logics, make relevant assumptions, understand business rules, possess strong communication skills as well as have the ability to think both in and out of the box.
As far as academic requirements are concerned, companies usually prefer candidates with at least a bachelor’s degree in engineering, computer science, information management, mathematics, statistics, economics, and sometimes even business.
Develop Skills To Become a Data Analyst
After understanding the job role and eligibility criteria, let’s move towards up-skilling oneself to become a data analyst.
Certification Courses
The first step is signing up for certification courses and sticking to it religiously until successful completion. It can be challenging to find relevant material for learning analytics. There are free as well as paid sources to learn. YouTube videos, data science blogs, and several coding tutorial websites are available for free. Then there are platforms like Global Tech Council, which provide professional certification courses on several data science subjects like statistical models, Hadoop, artificial intelligence, machine learning algorithms, optimization functions, etc. The focus should be on clearing the basics first and then reach advanced levels. Follow the course diligently, take up the assignments, and keep referring course material to attain a steeper learning curve. Certifications prove to be good CV points for beginners with no prior experience.
Choose a Mainstream Coding Language or Tool To Learn
I want to mention that it is of extreme importance for you to gain a thorough knowledge of the language or tool you select. You can hover over different languages or platforms at first to get a feel. It can be R, python, SQL, Tableau, DOMO, etc. Start with one that interests you the most. You can refer to several discussion forums as well to understand the complexity of the language that you are seeking to learn. Now, if you find coding difficult, you can start with GUI based tools or data visualization tools. Once you get an understanding and feel of them, then you can go back to some coding course. It might be easier to design algorithms after this.
Live Projects and Internships in Analytics
You can go online and start looking for some live projects on analytics to work. Seek internships, paid or unpaid doesn’t matter as long as you get the opportunity to learn. They add credibility to your profile.
Work on Your Communication Skills
People usually think that their technical capability is enough to ace any interview for the role. However, this is not true. Interviewers look for candidates who have soft skills like strong communication skills (both written and oral). Work on your professional communication language as well (the literal one!). Like if your mother tongue is different from the official language (say English in most countries), work on reading more books in English. Talking to your friends or even in front of the mirror in that language will be helpful.
Work on Your Presentation Skills
Your presentation skills are another essential criterion. Learn MS Office, particularly how to operate e-mails, word, excel, and, most importantly, Microsoft Powerpoint. Powerpoint is a powerful tool to present findings and insights from data to your business clients. They usually do not look and sometimes even understand codes or statistical models that you might have used. You should understand that your deck or ppt is where the actual consumption of your work might happen most of the time. Hence, learn to create effective slides and engage your audience while presenting.
Teamwork and Networking
Lastly, work on other aspects of soft skills, such as teamwork and networking. You are mostly going to be part of a team. An analyst can never go solo. You have to work with other analysts to collaborate; talk with other groups and departments to identify factors affecting the problem or the problem itself. You need to engage with managers and business leaders to understand business rules and constraints while you make assumptions in your logic and recommend business decisions based on your analysis.
End Notes For The Budding Data Analyst
Data Science is a vast field and encompasses many roles like Data Scientist, Decision Scientist, Data Engineer, Data Analyst, Statistician, Business Intelligence Associate, Consultants, etc. The line between them is thin. The scope in analytics huge, and jobs are secure with rising demand. The domain is among some of the highest paying industries in the world. I hope this article helps you to get started.
All the Best!