Emma Jonson 
Data is the epicenter of successful businesses in the modern world. Therefore, the popular phrase in the corporate world, “Data is power,” does not come as a surprise to people hearing it for the first time.
Data drives much of the modern technological advancements like Artificial Intelligence (AI), Machine Learning (ML), and more. Data is also vital in much more rudimentary yet complex processes like accounting and finance. But data, in its raw form, is indistinguishable from randomly stacked numbers.
So, how can a person or an organization make use of the data they directly and indirectly collect? This can be done by hiring data analysts. Data analysts are highly skilled and extremely proficient at arranging, segregating, classifying, and transforming data into comprehensible chunks.
Hence, Data Analysts are indispensable assets of companies. Moreover, the skills required to become a Data Analyst is not something that everybody can master; some find it more difficult than others. Therefore, the demand for Data Analysts is on the rise.
Here are seven tips for you to become a Data Analyst in the world of cut-throat competition.
Focus on Statistics
Statistics are an important aspect of providing data-driven insights to the company that is fruitful in the long run. Making well-informed decisions using statistical data and statistical probability will keep the company from incurring losses and produce fruitful results.
It also acts as a method of risk aversion. Some decisions that the company is about to take can be looked at from a statistical perspective to determine whether the end goal would be met or not. This also lowers the number of iterations in a process and makes it faster.
Statistics also help Data Analysts understand complex computational algorithms.
Some aspects of statistics you might want to focus more on are:
- Applied Science
- Linear Algebra
- Numerical Analysis
- Graph Theory
Take Programming Courses
You might be good with numbers with a pen, paper, and a calculator. But times have changed, and everything has gone digital. You need to be faster and more efficient in what you do; hence going digital is the only way for you to land your dream job as a Data Analyst.
Knowledge in programming languages like Python that run on the backend and can handle large amounts of data is crucial if you want to be a Data Analyst.
One of the best ways to learn programming languages fast is by enrolling yourself in online or offline classes that are taught by expert programmers and coders. Take up online courses will offer a greater degree of versatility. You can learn programming from an expert in the United States of America (USA) from Canada or India.
The certificates that you get from these courses will also add value to your CV and resume. Check out the best data analytics boot camp and choose that to get the best results.
Familiarize Yourself with Data Cleaning
A Data Analyst is expected to structure random and unorganized data to help companies save valuable time and increase efficiency. One way to do so is by using data cleaning software tools.
Data cleaning software tools will rectify and ameliorate poorly formatted data and fill in the gaps when there is incomplete data. Such processes could easily take weeks if done manually, but with data cleaning tools, it becomes a matter of hours. Hence, familiarizing yourself with such software tools is a must.
Get Creative and Visualize Data
A senior data analystwould agree that the job of a Data Analyst is as much an art as it is science and mathematics. You should have a creative mind that can visualize data in different ways than what the eye of an average joe can perceive.
You can practice honing this skill by taking up data analytics courses, meditation, and indulging in creatively stimulating activities every once in a while.
Improving your creativity will also help you present your findings to executive and board members of the company in a manner that is not stale or boring. You can also make use of data visualization software like Tableau.
Get Comfortable with Handling Big Data
When you are a Data Analyst, the likelihood of you encountering a problem where the amount of data you have exceeds the amount your system can handle increases as you climb higher up the success ladder in this career. Hence, you should be good at handling large piles of data by coming up with innovative solutions.
A data analytics bootcamp can provide detailed insight into this aspect. Also, learning a programming language like Python for big data is a handy skill.
Develop Communication Skills
The importance of communication skills is truly underrated. It is of paramount importance for a Data Analyst to have impeccable communication skills.
Think about it, as a Data Analyst, you have knowledge of the thousands of digits and numbers, what they mean and what they signify. However, a person in the managerial position or in the creative team may not be able to comprehend it as it is beyond their scope of knowledge.
Therefore, you should have good communication skills to be able to relay your thoughts and ideas across divisions without room for misinterpretations.
Develop your communication skills by hiring a mentor or enrolling in courses online. Taking up courses along with peers is a wise choice in this regard as you get to practice and refine your skills even when you are not in class.
Have Relevant Qualifications
If you are not yet a graduate and are exploring paths to become a Data Analyst, then getting a bachelor’s degree in Information Technology (IT), computer science or statistics will provide you a competitive edge.
If you have a different background altogether, then enroll in courses and do some relevant internships to increase your chances of securing a job as a Data Analyst.
Conclusion
Above all, you must never stop learning. The job of a Data Analyst does not change rapidly, but the workflow can be extremely fluid. As technology changes, so does the workflow.
With the right skills, qualifications, and will, you can be one of the best in your career as a Data Analyst in a few short years.