Organizations in all sectors rely on data to make critical business decisions and these data are used to identify inefficiencies and other business issues which are needed to be addressed. In these organizations, the primary duty of a data analyst is to assign a numeric value to important business functions so that performance can be evaluated and compared over time. An analyst should be well educated and must know how to use data to enable an organization to make more informed. There is a higher demand for professionals with data skills and about 40% of advanced data analytics require a master’s degree or higher.
What does a data analyst do?
A data analyst interprets data and turns them into information that will help to improve the business. They gather information from various sources and interpret the pattern and trend, analyzing the results using statistical techniques. They develop and implement data analyses and other strategies that can optimize statistical efficiency and quality. A certified data analyst is responsible for performing various tasks which includes:
- Collecting, interpreting data, and analyzing results
- Reporting the results back to the member of the business
- Developing and implementing data collection systems and other strategies that can optimize statistical efficiency
- Fixing code errors and data related issues
- Reorganizing the data in a format that can be easily read by human or machine
- Using statistical tools to interpret data sets and giving attention to trends and patterns that could be used for diagnostic and predictive analytical efforts
- Demonstrating the significance of the work in the context of a local, national and global trend that impacts both organization and industry
- Preparing reports for executive leadership that effectively communicated the trend and pattern using relevant data
- Coordinate with programmers and engineers to identify opportunities for process improvement, recommend system modification and develop policies
- Create apt documentation that allows stakeholders to understand the data analysis process and replicate the analysis if necessary
Which are the various types of data analytics?
Four types of data analytics can escalate value to an organization.
- Descriptive analytics inspect what happened in the past. The study website traffic, monthly and quarterly sales, and this type of information will help an organization to spot trends.
- Diagnostic analytics – they compare descriptive data sets to identify dependencies and patterns. This would help an organization determine the cause of positive or negative outcomes.
- Predictive analytics – they detect tendencies in descriptive and diagnostic analyses allowing an organization to take proactive action.
- Prescriptive analytics – They identify what business action has to be considered and this type of analysis brings significant value in the ability to address potential problems. They often use complex algorithms and advanced technology such as machine learning.
Diagnostic and predictive analysis is increasingly important to an organization.
How to become a data analyst?
As companies are growing, the need for data analysts remains higher. If you are individuals who love numbers, problem-solving, communicating your knowledge with others then you may pursue your career as a data analyst.
Advance your education
The entry-level data analyst job requires the candidate to possess at least a bachelor’s degree. You should earn a degree in a subject like mathematic, marketing, statistics, finance, computer, and economics. However, some individuals pursue their career in this role with just a strong foundation in data analytics training. Such individuals need to have a strong understanding of maths and statistics. A higher level of data analytic job may require a master’s degree or doctoral degree. Make sure you are attaining your master’s degree in data science or business analytics. One can also choose online certified courses for this role. If you think you need some help with calculus or coding, sign up for a class that will teach you the skills.
Learn the necessary skills
There are certain skills you should master and must possess exceptional knowledge to pursue your career as a data analyst.
- Technical skills – you should be proficient with at least one programming language. You need to be familiar with languages like R, HIVE, SQL. Building queries to extract the desired data is essential. Once you have analyzed the data you need to create an accurate report. While you don’t need to be a coding expert but you should know about it. Start learning how to use programs like Python, R, Java and you may join courses online.
- Practical skill – you need to be comfortable using maths and should have a strong understanding of college algebra. You must know how to do things like interpret and graph different functions, must be able to work through real-life word problems. You need to have good knowledge of statistics and should be able to solve common business problems like calculating compound interest, depreciation, and statistical measures. Knowing linear algebra and multivariate calculus will help perform data analysis. You need to organize data and calculate numbers so you should be comfortable using excel.
- Soft skills – a data analyst should provide detailed and accurate information to the decision-maker. So they need to possess superb communication skills so that they can liaise with various clients, executives, and IT specialists.
Learn about machine learning
It is important to know about machines when dealing with data analysis. You may join a foundation course in programming and statistics.
Gain work experience
Focus your job search on industries that need data analysts. You may check the websites of companies to see if they are hiring. Financial institutions, marketing, and tech companies tend to hire data analysts. You may apply for an internship for the role. Many internships remain unpaid so check before applying. Trade organizations are a great way to join workshops and networking opportunities. You may aim for an entry-level job to gain valuable knowledge and experience that you will need for higher-level data analyst jobs.
