What do you do? I’m a data analyst.
How much do you make? Somewhere around 1 lakh
Oh per year, ah!? No! Per month
Did you feel a thug life BGM while imagining this conversation with that one uncle who said you are of no good!
In this digital era, we are surrounded by data. We generate information every time we use devices ranging from a fitness band to online transactions we make. Thus the term ‘data analyst’ isn’t new to this generation. In simple terms, the word analyze means scrutinizing something to obtain actionable information. Adding the word 'data' can be defined as the art of drawing meaningful information from raw data.
Data analytics jobs are expected to be growing at about 31% by the end of this decade. This high market growth is backed by an increase in the launch of AI initiatives, implementation of big data technologies, and prioritization of data-driven decision-making. While the prominent companies have attractive packages for this post, there are a set of skills required to achieve heights. The internet is full of various online power bi courses which claim to aid you to land a fancy job with a handsome package. Sounds vague right? Are you still confused about how to groom yourself to match the job requirements for a data analyst? Don’t worry. Here’s a list of the top 8 skills you need to brush up to level up your data analyst career. Exercising these skills will take you a step closer to your dream of becoming a data analyst.
In no particular order, here are the top 8 must-have skills to start or improvise your data analyst job:
Microsoft Excel: This isn’t anything new. Being around in use for more than three decades now, excel is widely used in the data analytics field. Excel works best for small data sets. Even though there are many newer manual software programs, spreadsheets are still relevant. It’s not only the most fitting solution for all data projects but also a reliable & affordable one. The use of excel also deepens the understanding of the analytics process. Many actionable insights like revenue patterns, operations trends, marketing trends, etc can be analyzed through Excel spreadsheets.
SQL: Structured Query Language or SQL is an easy-to-understand language that allows the data analyst to interact with the data stored in relational databases. It is easy to understand and learn and thus is a user-friendly language. With the help of SQL, many companies have built their information fetching tools with ease. SQL can be done in Microsoft SQL Server, MySQL, Oracle, etc. SQL supports exceptional handling as it provides standard documentation to the users and also helps in the effective retrieval of big data from multiple databases.
Data Visualization Tools: For people who don’t work closely with data regularly, understanding the insights on paper or a spreadsheet will be difficult. One of the major tasks of a Data Analyst is to interpret, visualize & explain the insights in an understandable way to others. This is why it is very important to have the right data visualization tool at their disposal. These tools allow the analyst to communicate the findings effectively even to the ones who are not familiar with data science concepts. With PowerBI & Tableau being the two most popular data visualization tools, we would recommend a mastery of at least one of them. Learning one of these would make it easy for you to gain a grip over the other tools also.
Communication & Presentation Skills: The knowledge of digging in through the raw data to fetch valuable insights is incomplete if the data analyst lacks communication skills. The need for efficient communication & presentation skills becomes mandatory as the data analysts are responsible for reporting the insights and their conclusion to the team. One must be proficient with speaking, listening & writing communication skills. Without these, the collaboration with different stakeholders might be inefficient. This is one of the most underestimated soft skills, which holds the power to ease your career advancement. Strong communication & presentation skills are all that you need to explain complex data to non-technical colleagues.
Domain Knowledge: This is a certain skill whose importance goes without saying. A thorough understanding of a particular industry can be said to be domain knowledge. Having a clear understanding of the specific industry makes your application stand out. Many times, the position of data analyst states a specific domain like financial data analyst or retail data analyst. In such cases, the person qualifying for the relevant domain carries an extra benefit. One of the major myths about becoming a data analyst is that you need to hold a degree in computer science. In fact, you can start a career as a data analyst irrespective of the qualification you hold.
Python or R programming: Python or R programming languages can do anything excel does but in a 10 times faster way. However, not many companies ask for this skill. Knowing a programming language is not a must, but definitely a plus. These powerful statistical programming languages are used to perform predictive or advanced analysis on big data sets. When planning to learn a programming language, opt for python. Learn python with the help of the videos available on the Codebasics youtube channel. Also, we have launched our own ed-tech portal where even an absolute beginner can learn Python through a project-based learning approach. These videos explain the programming language in such a simplistic way that even a fifth-grader will understand it with ease.
Math & Statistics: A data analyst requires a strong grounding in mathematics & statistics to achieve heights. Statistics underpins all aspects of data analysis. Basics of inferential statistics and descriptive statistics can come in handy in the data analyst role. An understanding of math & statistics means the ability to parse extensive data sets for high-level insight. One need not have expertise in this skillset, but the clarity of fundamentals is a must.
Problem Solving: It’s never enough to just simply look at the data. You have to look past it and understand them thoroughly. This is not possible with problem-solving skills. A typical day of a data analyst needs data analysis and the ability to identify the patterns and conclude information. The role of a data analyst is to uncover and synthesize the connections which are not necessarily clear. Even though there are tools available for running different problems, understanding the crusts of the problem is manual. When you have limited resources, you have to initiate innovation in problem dealing. There is no one-fit-all solution to mastering this skill. You have to enhance your skills with every problem you solve.
Knowing the skill gap is as important as the desire to become a data analyst. With the blooming of industries and the increasing use of big data, many companies are short in supply. Improving your data analytics knowledge will fetch more opportunities and money in the near future. The ultimate decision to hone these abilities depends on your current capabilities, resources, and willingness to commit.
It can be helpful to take advantage of the books and other resources available for free. It allows you to become more familiar with the terminologies and build a stronger foundation. Visit the Codebasic YouTube channel for getting hands-on experience with practical real-life examples. We also offer courses at a very affordable price focused on this area, which includes a completion certificate and lifetime access to the materials. We have designed this program strategically to prepare anyone for the analytics field by building a strong theoretical foundation and applying it to real-world industry issues. Check our site to learn more about data analyst projects for beginners!
Are you looking for how to learn data analysis? In this blog, we explained the roadmap which will help you lay a strong foundation of data analyst skills.