How to Become a Data Analyst
With the large amount of big data produced everyday, companies around the globe have thought it wise to employ the services of professionals to analyze data. One of which is the data analyst. A data analyst is responsible for studying big data sets. He understands the trends in these data sets and is able to analyze them too. Hence, helping companies make informed decisions and improve business practices.
Simply put, a data analyst turns data into information, this information is then transformed into insights and these insights are used by companies to improve business practices. These business practices may include; better customer services, improvement on production processes or market strategies.
You may have heard about the increase in big data demand worldwide and want a piece of the pie or maybe you are somebody who loves numbers and enjoys solving problems and sharing knowledge with others and have now decided to take on a career as a data analyst.
Good choice I must say…
Data scientists and analysts are about the most sought after jobs in existence today.
Worrying if a career path as a data analyst will fetch you money? Worry no more. These jobs are lucrative due to the high demand and low supply of professionals in the field. A 2019 study showed that there are 97,000 analytics and data science positions vacant in India due to an unavailability of qualified candidates to fill the positions. However, to master the data analytics skills required to understand big data, you might need to get proper training from a renowned college.
Skills Required to Be a Data Analyst
Microsoft Excel goes beyond just spreadsheet, so if you think you already know how to operate Microsoft excel, think twice. There are advanced options on the software that are required for data analysis. Although Microsoft Excel is not very useful for analyzing big data like R or Python, it has proven to be “god” in analyzing smaller data sets using tools like VBA methods. If you do not know how to use Microsoft excel, many online classes are available to help you learn how to use it.
It is essentially a combination of multivariable calculus and linear algebra, along with statistics. Every data analyst needs to understand machine learning. As a data scientist, you should be able to solve common business problems like; calculating compound interest, depreciation and statistical measures (mean, median, mode). It is important to have understanding of simple algebra and how to use tables, charts and graphs.
This skill provides you the ability to analyze and interpret large data sets and produce information that will enable you give necessary insights and make informed decisions. It is necessary that you should get familiar with some form of data analysis; at least, the basics of Statistical Analysis. You should gather knowledge on the type of statistical techniques that exist and know when to use them to solve a given data problem. You should also get familiar with analytical tools; as they help in statistical analysis. The most popular analytical tools are; Pig, SAS, Hive, Hadoop and Spark.
These skills are important in performing predictive analytics on big data sets in order to draw useful conclusions. Python and R are the most commonly used languages in data analysis. Python is used for statistical analysis.
To become a data analyst, you should have knowledge in SQL (Structured Query Language). It is one of the primary tools used in Data Management. SQL (Structured Query Language) involves processes of Data Extraction, Transformation, and Loading. Data extracted from different sources are first transformed into a more convenient format for analysis before finally loading it into a data warehouse. Knowledge in SQL (Structured Query Language) is also needed by a data analyst to enable him to run queries in order to find relevant information in the data set.
Advanced knowledge of matrices, framing data, linear and relational algebra, CAP theorem and series are important to succeed as a data analyst.
This skill is very important to acquire as a data analyst. This is so because a data analyst must be able to translate data findings into insights that have useful conclusions. Data should be presented in a simple and understandable way such as using a storytelling format. This ensures that others who are not data professionals are able to understand your findings.
The Steps Involved in Becoming a Data Analyst
Gain a bachelor’s degree in information technology, statistics or computer science
Research and apply to gain entry into colleges that have programs in information technology, statistics, economics, marketing or computer science. When you get accepted, ensure that you register courses that emphasize project management and database management.
Although a lot of companies seek the services of data analysts, it is difficult to get a job as a data analyst without any working experience. Look for industries that need data analysts and apply for internships while you are in college. It is a good way to gain experience and will help you develop skill sets that are currently been taught in school. Positions such as a statistical assistant or technician is not a bad way to start. Jobs that teach about analytical software programs and big data management are also advisable.
Get a Postgraduate Degree
Getting an advanced degree is a good way to advance your career and leave you open to more job opportunities. Companies want to employ people that are well grounded in the latest technologies and have professional experience in data analysis. Getting a master’s degree in data science, data analytics or big data management is a good way to stand out in the employment market.
Prepare your Resume
You should prepare your resume and cover letter. It is important that your resume is professionally drafted because it is the first thing that tells a potential employer about your skills. Once you are done, ensure to proofread your resume and cover letter properly to avoid embarrassing mistakes.
To become a successful data analyst, you should be ready to put in all the hard work required. You should obtain a college degree. Next, learn important analytical skills and gain valuable work experiences in the field. It is also important to note that new technologies for data analysis are discovered everyday. Do not stop researching; continually get acquainted with new technologies.
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