How to Become a Data Analyst In 2023?

In 2023, Data Analysis has become one of the core functions in any organization. This is a highly sought-after role that has evolved immensely in the past few years. But what is Data Analysis?  What do Data Analysts do? How to become a Data Analyst in 2023? What are the skills one needs to have to be a Data Analyst? There are many such questions which strike our mind when we talk about this profession. To know more, check out top Data Science courses.   

Let's walk through the answers to all the questions to ensure we have a clear picture in our mind.

What is Data analytics?

Information collected from different sources is used to make informed decisions for the organization, and is analyzed for some specific goals through Data Analysis. Data Analysis is not only used for research and analysis; but it helps organizations learn more about their customers, develop marketing strategies and optimize product development, just to name a few areas where it makes an impact.

To be precise, there are four types of Data Analytics:

1. Descriptive Analytics: - In this type of analytics, analysts examine the past data like monthly sales, monthly revenue, website traffic and more to find out the trend. They then draft a description or a summary of the performance of the firm or website. This type of analytics uses arithmetic operations, mean, median, max, percentage and other statistical summaries.
2. Diagnostic Analytics:- As the name suggests, here we diagnose the data and find out the reasons behind any particular trend, issue or scenario.  If a company is faced with any negative data then this type of analysis will help them to find out the main reasons/causes for the decline in the performance, against which decisions and actions can be taken.
3. Predictive Analytics:-  This type of analytics helps in predicting the future outcome by analyzing the past data and trends. It will help companies to take proactive actions for the better outcomes. Not just this, but predictive analysis also helps us forecast the sales, demand, fraud, failures and set our budgets and other resources accordingly.  
4. Prescriptive Analytics:- This type of analytics helps in determining what action the company should take next in response to the situation, to keep the business going and growing.

Why do we need Data Analysts?

Organizations across different fields or sectors rely on data analysis to take important decisions for the development of a new product, to forecast sales for the near future, or find out about entry into new markets or new customers to target. Data analysis is also used to analyze the business performance based on the present data and find out various inefficiencies in the organizations. Not only industries or businesses use data analysis, but it is also used by different political parties and other groups to find out about opportunities as well as challenges.

What does a data analyst do?

There are several functions which an analyst performs, but some of the functions may also depends on the type of business and organization. Generally, a data analyst performs the following responsibilities:

1. Data collection from various sources like primary sources and secondary sources and arranging the data in a proper sequence.
2. Cleaning and processing the data as per requirement. A data analyst may be required to treat missing values, clean invalid or wrong data and remove unwanted information.
3. Using different kind of statistical tools like R, Python, SPSS or SAS, to interpret the data collected.
4. Adjusting the data according to the upcoming trends or changes like seasonal trends and then making interpretations.
5. Preparing a data analysis report.
6. Identifying opportunities and threats from the analyzed data and apprising the same to the organization.

Wondering where to begin your career as a data scientist? Enroll in KnowledgeHut top Data Science courses. Now that you know what areas a Data Analyst works on, let us move to the skills and knowledge you would require to get started in this field.  

What are the skills necessary to be a Data Analyst?

Broadly, a data analyst needs to have two type of skills at a broader level:

1. Technical skills - Knowledge of different technical languages and tools like R, SQL, Microsoft Excel, Tableau, Mathematical skills, statistical skills and data visualization skills. These technical skills would help an analyst actually use the data and visualize the final outcome in a form that could be beneficial for the firm. This may include tables, graphs, charts, and more.  
2.  Decision making – This is extremely necessary to present the outcome and take the executives through the various changes, trends, demand, and downfall. Deep analysis is required to be able to take logical, factual and beneficial decisions for the firm. Data analysts must have the ability to think strategically and get a 360 degree view of the situation, before suggesting the way forward.
   

After acquiring the above mentioned skills, it is very much required to keep yourself updated with the latest trends in the industry, so a mindset of continuous learning is a must.

How to Become a Data Analyst in 2023?

The year 2023 changed all the definitions of a business and its processes. COVID-19 put companies across the world in a tailspin, forcing them to rethink their business strategies in order to cope with the evolving challenges thrown up by the pandemic. Some companies that were market leaders in their domain were unable to cope, and many had to even close down. 

The question therefore arises, in such an uncertain scenario, with challenges around every corner, is it even prudent to consider stepping into the role of a Data Analyst at this juncture?  

The answer to this is, “YES”. This is the best time to be a data analyst because organizations everywhere are looking for expert Analysts who can guide them in making the right decisions, helping the organization to survive through the pandemic and beyond. Data analysts can perform detailed sales forecasting, or carry out a complete market analysis to make the right predictions for future growth. Companies need to prepare smart strategies for sales and marketing, to survive and thrive in the long run.

If you want to shape your career in data analytics then

1.  You must have a degree in Mathematics, Economics, Engineering, Statistics or in a field which emphasizes on statistical and analytical skills.
2.  You must know some data analytics tools or skills which are mentioned above like R, SQL, Tableau, Data Warehousing, Data visualization, Data mining and advanced Microsoft Excel.
3.  You must consider some good certifications in the above-mentioned skills.  
4.  You may also consider a master’s degree in the field of data analytics.
   

Let us now take you through the scope of Data Analysis in 2023.

What is the Scope of Data Analytics in 2023?

The world is witnessing a surge in demand for data analytics services. According to a report, it is expected that there will be 250,000 new openings in the Data Analytics field in 2023, which is almost 60% higher than the demand in 2019-20. To stay ahead of the competition, organizations are employing Data Analysts and the demand for experts in the field is only set to rise. 

According to another report published in 2019, there were 150000 jobs which were vacant in the Data Analytics sector because of lack of available talent. This is a lucrative field, and those professionals who have expertise and experience can easily climb to the top in a short time. A report by IBM predicts that by 2023, Data Science and Analytics jobs would grow to nearly 350,000.

What are the sectors in which Data Science jobs are expected to grow in India in 2023?

Though the need for data analytics is growing across every sector, there are a few sectors that are more in-demand than others. These include:

1. Aviation sector: uses data analysis for pricing and route optimization.
2. Agriculture sector: analyses data to forecast the output and pricing.
3. Cyber security: Global companies are adopting data engineering and data analysis for anomaly and intrusion detection.
4. Genomics: Data analytics is used to study the sequence of genomes. It is heavily used to diagnose abnormalities and identify diseases.

Conclusion

If you would like to enter the field of Data Analytics, there’s no time like now! Data is useless without the right professional to analyze it. Leading companies leverage the power of analytics to improve their decision making and fuel business growth, and are always looking to employ bright and talented professionals with the capabilities they need.  Opportunities are plentiful and the rewards are immense, so take the first step and start honing all the skills that can make you fulfil your dream!