The Best Way a Beginner Can Learn Data Analysis

Every day businesses produce and store tons of data, but what happens with that? Today, this pool of information requires the ability to understand and refine data with efficiency, which has boomed the use of analytics and the number of people investing in learning data analysis. How then, can you learn data analysis?

To become a data analyst, you will have to aim for a bachelor’s degree that is required for many entry-level data analyst posts. Or if you are planning to switch your position from being in any other data-related field to data analytics, you can start with an online course. 

Data production is increasing every second and will never end. But before stepping into the field, you must have the right understanding of where you are going and what can you expect once you get in there.

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What is data analysis?

Data analysis is a process to sort through the massive amount of unorganized or unstructured information and driving key insights from it. The insights are extremely valuable for the companies to make decisions, no matter what size a company is.

But, to warn you beforehand, data science and data analysis are two different things. There is no doubt that they belong to the same species but data science is typically more advanced than data analysis.

What is the role of a Data Analyst?

Mainly, a data analyst is a technology expert who retrieves and gathers large volumes of data, organizes it, and turns it into the insights that are used by businesses to make better decisions. To put forward his insights, a data analyst uses graphs, charts, or any other visual representations, giving meaning to the unorganized data.

These professionals use a variety of methods including machine learning, programming, statistics, and data collection.

The best way for a Beginner to Learn Data Analysis

If you are new to data analytics and you do not know where to start from, do not panic. After you have done your degree in stats and computers-related fields, there is a great pick of online courses and resources available online to help you master the fundamentals of data analysis and take advantage of tremendous opportunities that data analysis can offer. 

You can easily access those courses online, after all, the key perk of learning online is easy access to information. 

Here are the five steps to become a data analyst, even if you are a beginner:

  1. Get yourself a bachelor’s degree in such a field where statistical and analytical skills are emphasized
  2. Manage to learn important data analytical skills
  3. Consider getting a certification
  4. Get a first entry-level data analyst job
  5. Get a master’s degree in the field of data analytics. 

How long will it take to become a Data Analyst?

Considering the different paths to a career that result in becoming a successful data analyst, it can take anywhere between 10 weeks to 4 years. That is assuming that you either take quick online courses and start gaining experience with projects, or you go straight for a 4-year university degree.

Is becoming a Data Analyst a good career?

Lately, data analysts have become one of the highest in-demand jobs throughout the world. With very few professionals being able to effectively do justice to the title. However, for experienced data analysts in some countries their salaries are higher than most other technology-related professions. 

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This is How much Data Analysts Make (By country, industry and Experience Level)

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Skillset of a Data Analyst

Learn Data Analysis

These are the skills required to become an efficient data analyst:

  • Ability to interpret, analyze, and model data
  • High understanding of the mathematical ability
  • Understanding of programming languages, such as Python, SQL, and Oracle
  • A logical and methodical approach
  • Ability to meet deadlines and plan work
  • Attention to detail
  • Verbal and written communication
  • Interpersonal skills
  • Teamwork

Data Analyst Qualifications

Along with a good skill set, a data analyst must know these:

Programming languages

A data analyst must be proficient in at least one programming language and have the know-how of the other languages. Especially, the field requires R and SAS for data cleaning and data gathering.

Creative and analytical thinking

The key attributes to become a good data analyst are curiosity and creativity. It is necessary to have a strong ground in statistics with an ability to think critically about the problems of a company with a creative and analytical lens.

Effective communication

A data analyst must know how to convey his findings. Whether he is addressing a small audience or the executive decision-maker. He must possess strong communication skills.

Data visualization

A data analyst should know the types of graphs to use along with scaling the visualizations and knowing the right charts to use.

Data warehousing

Some of the data analysts are working at the back-end of the company. They are responsible for connecting databases from multiple sources to make a data warehouse and use query languages to manage and find data.

Data mining and data cleaning

A good data analyst knows how to use tools to gather unstructured data. Once the data is collected, he knows how to clean and process it.

Advanced MS excel

A data analyst should know how to handle excel and understand the advanced analytical and modeling techniques.

SQL Databases

If you are new to the term, SQL databases are relational databases with structured data. Such as the data is stored in form of tables and the data analyst pulls information from tables to run analysis. 

Machine learning

The data analysts who know machine learning are highly valued. Though it is not an expected skill, but if you know it, boom!

Simple Roadmap to Develop Your Data Analytics Skills

Now, once you are done with the degrees and courses, to become a successful data analyst you need to keep yourself updated with the latest tools, that include:

  • Structured querying languages and spreadsheets such as SQL and XML.
  • Frameworks and programming languages used by Data Analysts such as Python, R, and Hadoop
  • Popular visualization tools used by Data Analysts such as Tableau, and Power BI
  • Data Wrangling and Data Mining
  • Experience leading data analysis platforms such as Adobe Analytics and Google Analytics.

Mathematics

  • Data summarizing parameters and basic statistics e.g. mode, mean, distributions, central tendencies, median.
  • Data comparison, integrity, and tendency tests like t-test, z-test.
  • Linear, GLM, Logistic – Regression
  • Predictive modeling and advanced techniques and prescriptive methods

Technology

  • Microsoft Excel is the core of mathematics. You should learn everything, from simple formulas to a data analysis tool and dashboard. 
  • Tableau is almost the standard right now for data visualization and dash boarding
  • VBA is not widely used but still, it can help to perform many tasks easily.
  • SQL is a logical development from Excel for handling larger data volumes and also standardizing processes and creating code modules for repeated use
  • R is the next step as these are some of the tools as they can help you do more complex processing like modeling and regression.

Business

  • Functioning of different verticals for example Pharmacy, Healthcare, Retail, Technology, Banking, etc.
  • Applying analytics in each of the above-mentioned verticals, hope this helps.

9 of the Most popular Data Analysis Courses for Beginners

  1. Coursera Project Network: A Beginners Guide to Python for Financial AnalysisPython Geospatial Data Analysis
  2. University of Michigan  : Python for Everybody
  3. Alberta Institute : Data for Machine Learning
  4. IBM: Python for Data Science, AI & Development 
  5. Coursera Project Network : Spreadsheets for Beginners using Google Sheets 
  6. Coursera Project Network : Pandas Python Library for Beginners in Data Science
  7. Coursera Project Network : Analysing Unstructured Data using MongoDB and PySpark
  8. University of Maryland, College Park : Framework for Data Collection and Analysis 
  9. University of Colorado System : Introduction to Clinical Data Science 

Here are some Free useful Resources to Learn Data Analysis:

Job outlook of a Data Analyst

Nowadays the role of an analyst is becoming more complex increasingly. The data analysts should be prepared to use modeling and predictive analytical techniques to generate useful insights and actions. After which they have to communicate their insights with people.

In short, getting out of your comfort zone and reflecting both a data analyst and a data scientist in yourself is expected from you.

The positions of an analyst are growing by 11% to 18%, which is faster than an average job growth rate. The main reason is that an analyst is perfect for the majority of industries such as healthcare, information, manufacturing, finance, and retailing.

Job Responsibilities

The job responsibilities of a data analyst are to understand the goal, querying, data cleansing, data mining, data examining, interpreting data trends, preparing summary reports, and collaborating with other teams mainly.

Salary of a Data Analyst

Depending on the job responsibilities, a data analyst can earn a good deal of salary numbers.

  • If you are an entry-level data analyst, you can earn approximately $84,000.
  • An average data analyst can earn up to $100,000 approximately.
  • Whereas, a senior data analyst can earn between the range of $118,000 – $143,000

Check out: This is How much Data Analysts Make (By country, industry and Experience Level)

What are some tools used by data analysts?

In this efficiently moving world, some tools used by data analysts to speed up the process are:

Google Analytics

It helps to gain an understanding of customer’s data along with the trends and customer experience that can be improved on landing pages.

Tableau

A Tableau is used by analysts to aggregate and analyze data. They create and share dashboards with other team members to create visualizations.

GitHub

GitHub is used for sharing and building technical projects. It is a must for all data analysts to use object-oriented programming.

Jupyter Notebook system

It makes the test coding easier for data analysts. The markdown feature of Jupyter notebook is well-liked.

Conclusion

Data analysis has become quite popular in the enterprise as a means to analyze and shape business processes and to improve decision-making and business results. Advanced analytics helps businesses to make the conversations more customer-centric.

Hence to manage the big data of organizations, if you think of becoming a data analyst, there are plenty of opportunities for you.

REFERENCES & FURTHER READING

https://www.mastersindatascience.org/careers/data-analyst/

https://brainstation.io/career-guides/how-to-become-a-data-analyst

Free Data Analytics Basic Tutorials for Beginners in Data Science

How To Become a Data Analyst?: A Step-by-Step Guide

 8 Beginner Online Classes to Learn Data Science on Your Own Time

How to Learn Data science from scratch

Emidio Amadebai

As an IT Engineer, who is passionate about learning and sharing. I have worked and learned quite a bit from Data Engineers, Data Analysts, Business Analysts, and Key Decision Makers almost for the past 5 years. Interested in learning more about Data Science and How to leverage it for better decision-making in my business and hopefully help you do the same in yours.

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