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Data Analytics vs Statistics – A Comprehensive Analysis

Data Analytics vs Statistics – Which Field should I Choose? Data Analytics and Statistics both are trending topics among students who aspire to enter one of the fields. Many assume that data analytics has more scope than statistics as a few think statistics offers better career prospects.  But which is true? This is why a brief introduction to both streams and their applications in the sectors is provided. We will conclude the relation between the two at the end of this article. 

Data Analytics vs Statistics (2)

Data Analytics

A branch of data that employs various tools and techniques for the conversion of unfiltered data into actionable information to let decision-makers assist an organization in improving its performance is called data analytics. An individual who takes charge of performing data analysis and providing management with actionable insights is called a data analyst. Predictive analysis, prescriptive analysis, Prescriptive data analytics. diagnostic data analytics, descriptive data analytics, and predictive data analytics are the different types of data analytics. 

Statistics

Statistics is a science that converts raw data into meaningful data like data analytics. It is more focused on identifying, collecting, organizing, and presenting data. The selected data could be quantitative or qualitative in nature. It promotes easier decision-making for the management. However, it differs from data analytics by employing tools such as median, mean, standard deviation, mode, sample tests, and coefficient of variance. If you are a statistician, you will use mathematical formulas to interpret raw financial data.  Inferential Statistics and Descriptive Statistics are the two kinds of statistics.

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Applications of Data Analytics and Statistics

One of the simplest ways to understand the difference between data analytics and statistics. I.e., Data Analytics vs Statistics by learning about their applications. The two streams have applications in many fields. However, we will go through four main sectors where they are used. 

Data Analytics

  • E-commerce
  • Healthcare
  • Cybersecurity’
  • Banking

E-commerce:

All the e-commerce mediums implement data analytics to know their customer behavior to customize the shopping experience for them. It is basically done to optimize the marketing campaigns and increase sales. As a data analyst, you will have the opportunity to analyze customer preferences, browsing patterns, and purchase history to suggest to the marketing team to target specific niche segments, show customized product recommendations to the customers, and thereby improve buyer retention & satisfaction. 

Healthcare:

The healthcare industry uses data analytics to advance in the field and adapt to the changing needs of human welfare. The application of data analytics to healthcare will promote better patient care, prevent diseases, and optimize resources. Let us say you are a data analyst at a hospital and you were asked to identify requirements of certain drugs and combinations of remedies to treat a set of patients. Your first step will be to collect data from all the relevant patients, assess their health condition, and then suggest customized treatment plans for each. The use of data analytics is also known to detect disease outbreaks, track the effectiveness of remedies, and thereby improve healthcare operations. 

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Cybersecurity:

The cybersecurity department employs data analytics to detect and prevent cyber attacks and threats. The application of data analytics to security systems enables data professionals to analyze system logs, user behavior, and network traffic to detect potential security breaches and anomalies. An organization that uses data analytics can strengthen its security measures, identify, and respond to threats to safeguard its sensitive information. 

Banking:

Banks choose data analytics over other forms of data analysis to find out customer behavior, handle risks, and customize financial services. Banks can tailor their offers, assess creditworthiness, and identify potential by performing an analysis of transaction data, credit histories, and customer demographics. Many banks utilize data analytics to expose money laundering tasks and thereby adhere to regulatory compliance. 

Statistics

  • Government sectors
  • Clinical Trial and Design
  • Sports
  • Political Campaigns

Government Sectors:

Government entities make decisions based on the results of well-researched figures and statistics.  The decisions may be related to any field starting from health to development in the country. The government sector uses statistics to conduct research/survey on education to track the progress of college students. 

Clinical Trial and Design:

This is one sector that makes data analytics and statistics appear connected. However, there is a difference in the use of both fields. .i.e., Data Analytics vs Statistics. Statistical data is one main element that helps medical fields to run their operations. Discovery of a new treatment or a drug will be first tested on a group of humans to find out its safety and efficacy. In simple words, the drug is experimented on human bodies to note down their reactions. Health practitioners also conduct studies as per the age, race, nationality, or other aspects of the chosen humans to assess the effect and outcomes of the drug. 

Sports:

Believe it or not most of the sports like cricket, basketball, football, chess, badminton, tennis, and volleyball use statistics for a variety of purposes. The usage of statistics promotes the improvement of the effectiveness of the sport. Statistics also help a sportsperson to track their performance and become better at it. As we know the world is advancing every day and statistics is being used for the same; advancing sports. This is why a variety of equipment and tools are used to gather data that is related to numerous factors.

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Political Campaigns:

The application of statistics to political campaigns is crucial and critical. It is almost impossible to run a political campaign without statistics. Certain entities that research politics and gather numbers related to politics help leaders curate campaigns to please the public and win their votes. There are also software which are used to predict winners in the next elections. Many news channels use the software to grab the attention of their viewers by using their predictions. Political parties use statistical tools to know the number of candidates in a chosen voting zone. 

Ways to Become a Data Analyst

One of the obvious aspects that displays the difference between data analytics and statistics (Data Analytics vs Statistics) is the eligibility criteria to enter the fields. Let us look at the educational requirements to become a data analyst and a statistician. 

  • Complete 10+2 Education
  • Obtain a Bachelor’s degree
  • Complete Masters
  • Avail of Certifications
  • Programming languages
  • Learn Programming languages

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Complete 10+2 Education:

Having a certificate with 10+2 education is mandatory. You must have a basic understanding of mathematics, computer science, statistics, and economics. Knowledge about these subjects will make your life as a data analyst easier. The next step after 10+2 completion is entering a college to complete graduation.

Obtain a Bachelor’s degree:

You must obtain a bachelor’s degree to become a data analyst. Many degrees are available at your reach to kickstart your career in data analytics. If you are in India, consider obtaining degrees in the subjects below. 

  • Mathematics
  • Economics
  • Computer Science
  • Statistics

Complete Masters:

You do not want to remain in the entry-level position forever, Do you? Learners who are interested in targeting management and senior-level roles must do a master’s. Not only that, a master’s degree will increase the number of career opportunities for you. 

Avail of Certifications:

Be open to learning new concepts and deep dive into data analytics through certification programs. If you currently are a data analyst, enquire about the certification programs at your workplace. The courses developed by your employer will give you an in-depth understanding of your process and open doors for new opportunities. Joining an online course will help you stay updated with the latest changes in data analytics techniques and tools. If you are a fresher looking for experience, consider applying to a data analytics master course from IIM SKILLS for a better future. 

Learn Programming languages:

Data analytics makes use of programming languages like SQL, Python, and R. When you master any one of the languages, you can easily finish the assigned tasks. You can achieve this by taking admission to a crash course or a full-time program from some of the leading ed-tech companies. If you want to brush up or improve your coding skills, enter an advanced course. 

Tip to Get Shortlisted for an Interview:

Ensure to include all the essential data analytics skills in your resume. Maintain a consistent format and avoid multi-colored fonts to create a good impression on your future employer. Go through the job description and accordingly customize your CV. You can also take ideas from ChatGPt and create an appealing and impressive resume. This point is applicable to individuals aiming to master statistics and become a statistician in the future. The only difference (Data Analytics vs Statistics) is that you have to replace data analytical skills with the skills of a statistician. 

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Ways to Become a Statistician

  • Obtain a bachelor’s degree
  • Gain experience
  • Pursue an advanced degree
  • Get professionally certified

Obtain a Bachelor’s Degree:

Just like you need a bachelor’s degree to join the data analytics field, you must graduate to become a statistician. Take admission to a graduate college and ensure to choose statistics as a major subject. You can also obtain a bachelor’s degree in mathematics or subjects related to statistics and become eligible for the post of a statistician. Most relevant degree programs have computer science, applied mathematics, economics, and statistics as part of the curriculum. 

Gain Experience:

When I say get exposed to a workplace, I mean serve a company to apply the methods of statistics to the process. This tip will help you get shortlisted for better opportunities in the future compared to the workforce who have irrelevant experience. You can serve a company as an intern or work on a college project in a reputed organization to get exposure to real-world scenarios. Another approach to gaining relevant experience is to participate in competitions. This is being said because individuals from relevant career fields will participate in the competitions and you will get an opportunity to network with them and increase your chances of getting hired. In simple words, you can find a mentor at competitions who can guide you to start your career as a statistician.

Pursue an Advanced Degree:

You should aim to delegate work from a management role. And for that, you need an advanced degree. You can apply for a doctorate or master’s in applied statistics or mathematics. If you are interested in teaching at a university, get a doctorate degree. While a master’s degree will get you placed in a private sector or a government body. It is always best to learn about the requirements of your dream roles to take the necessary actions to get hired. 

Get Professionally Certified:

If you are keen on gaining a competitive edge over others, enroll in a trending course. Make sure the institute you choose is accredited by regulatory and well-known bodies. List the skills you want to acquire and then search for a program with a suitable curriculum.  There are many online and offline certification courses and workshops available for you. The only thing you need to do is research the best training providers and join one of them.

Must Have Skills in a Data Analyst

Though strong communication eliminates the difference between the two(Data Analytics vs Statistics) to a certain extent, there are other faculties you should have to work as a data analyst and they are 

  • SQL skills
  • critical thinking
  • Broader business knowledge
  • Communication tools and skills

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SQL Skills:

The majority of the data is stored in an online database using programming languages. SQL is the most popular programming language used in the companies. This is why every data analyst must have knowledge about SQL. It is considered one of the most reliable, applicable, and mature programming languages that can be used to address data queries. The presence of SQL in the essential skills list shows the difference between data analytics and statistics (Data Analytics vs Statistics).

Critical Thinking:

Critical thinking is the ability to connect the dots and make something useful out of it. You should be in a position to assess the level of risk a company has if a problem is not fixed. Data analysts play with numbers so make sure you are good at interpreting the figures and understanding facts to eliminate the problem. The ability to analyze a problem and the requirements to fix it for the improvement of a company also comes under critical thinking ability. This point also sheds light on your ability to detect growth opportunities and make necessary recommendations.

Programming languages: Data analysis involves the usage of programming languages. There are other important programming languages apart from SQL. Python, R, Scala, JavaScript, and Julia, are some of them. 

Python is used for agile and fast data manipulation by the data analyst. 

R is used for statistical computing and has many libraries that can be used for analysis. R is easier to learn compared to Python due to the smaller number of iterations. 

Scala is a new entrant into the industry which is used to fix issues with Java. That being said, it is employed by data analysts like you for machine learning, web programming, and many other activities. 

JavaScript is one of the data analysts’ favorite tools as it assists them in creating dashboards and promotes data visualization. 

Julia was developed to help data analysts perform high and fast performance numerical analysis. It is used to deal with matrices through the implementation of mathematical concepts. This point shows us statistics and data analytics are connected and not completely different from each other(Data Analytics vs Statistics). 

Broader Business Knowledge:

How can a data analyst create solutions to business problems when they do not have enough knowledge about the affected areas? They have to learn about the essential aspects of the business problems which includes understanding how some of the business areas work and how they can be fixed using the data. This is why you should know about other parts of the business as well to become a successful data analyst.

Communication Tools and Skills:

You may be great at performing data analysis but if you do not have the ability to communicate your findings, all your efforts go in vain. This is why you should ensure you get better at expressing your thoughts and insights. You can improve your communication skills by attending soft skill classes and reading books to eliminate grammatical mistakes. Having good communication skills will allow you to explain the findings in a better way. Storytelling skills will grab the attention of your audience and encourage productive discussions. 

Must-have Skills in a Statistician

There are a set of skills that are mandatory to perform the statistical operations. Every statistician should possess the below list of skills

  • Communication
  • Problem-solving
  • Analytical ability
  • Mathematics

Communication:

The job of a statistician involves regular interaction with other professionals like engineers and chemists. It means having strong communication skills is a must. You can clearly share your thoughts and conclusions with others only when you are able to express them well. This is also important because you may come across individuals who do not have knowledge about statistics and you have to explain in a way they understand.

Problem-solving:

Why does an organization require statisticians? Companies need statisticians to fix real-world problems. This means a statistics professional must be good at solving problems. You should know what to consider when to format, and how to analyze the data. You should also have the mental faculty to interpret data. All these come under one basket and it is called the problem-solving skill. 

Analytical Ability:

You as a statistician have to implement mathematical models and for that, you should have good analytical skills. You can evaluate large sets of data only when you have analytical skills. You can use the relevant models to produce accurate results if you have analytical ability. 

Mathematics:

Statisticians must be proficient in applying mathematical methods and theories to the processes. When you are good at mathematics you can find effective and new ways to resolve problems in engineering, business, science, and other linked fields. The main reason for suggesting having mathematical expertise is the requirement of implementing mathematical concepts at work.

 Conclusion on Data Analytics vs Statistics

We started the article with the topic of Data Analytics vs Statistics. We learned the meaning of statistics and data analytics along with their applications in various industries. Data analytics is applied in many sectors including E-commerce, Healthcare, Cybersecurity, and Banking. Statistics is used in many industries including Government sectors, Clinical Trial & Design, Sports, and Political Campaigns. 

Statisticians consider data to report facts and figures to the concerned teams to assist them in making decisions to achieve the desired results. Even data analysts apply some aspects of statistics to data analysis to draw insights from the data. However, the skills and knowledge required for each role differ; data professionals must have crucial skills like SQL skills, critical thinking, Broader business knowledge, and Communication tools and skills. Whereas statistics should possess mandatory faculties such as Communication, Problem-solving, Analytical ability, and Mathematics. The difference between the two fields (Data Analytics vs Statistics) is obvious in connection with the skills as only a few are common in both. 

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FAQs

Q. Which career path is good between the two(Data Analytics vs Statistics)?

Both data analytics and statistics have great career opportunities for students like you. You need to understand and find out which subject interests you more. If you love playing with math, choose statistics. On the other hand, if you are passionate about applying various data-related tools and techniques, prefer data analytics. But make you enter relevant educational programs to have a smooth journey. 

Q. Will joining an online course help me become a data analyst?

Yes. Applying to a data analytics course will help you gain the necessary skills and knowledge to enter a company and perform data analysis. That being said, having a relevant educational background will catalyze your career growth. 

Q. What skills should I have to work as a statistician?

There are a set of skills to become a statistician. However, the most important ones that will get your resume noticed by your potential employer are Communication, Problem-solving, Analytical ability, and Mathematics. 

Anuja Maniyala is a intern at IIM SKILLS. She worked as a creative content writer for AADOX and Quoteslyfe in the past. She has identified her passion for writing after working as a banker in some well-known companies like Wipro and HSBC. Her current target is to become an author of a unique and creative self-help book. Her enthusiasm and curiosity to learn about the human mind and behavior makes her different from the rest of the world.

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