Roadmap for Becoming a Data Analyst In 2023
Roadmap for Becoming a Data Analyst In 2023
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As an AI developer, we first play with data and we want to understand the data a lot. For that Data Analyst is the best role. So, today am going to give you a roadmap for becoming a Professional Data Analyst which am following right now!
𝗪𝗵𝗼 𝗶𝘀 𝗮 𝗱𝗮𝘁𝗮 𝗮𝗻𝗮𝗹𝘆𝘀𝘁? 𝗪𝗵𝗮𝘁 𝗮𝗿𝗲 𝘁𝗵𝗲𝗶𝗿 𝗱𝗮𝗶𝗹𝘆 𝗱𝘂𝘁𝗶𝗲𝘀, 𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝘀𝗸𝗶𝗹𝗹𝘀 𝗱𝗼 𝘁𝗵𝗲𝘆 𝗻𝗲𝗲𝗱? 𝗜𝗻 𝘁𝗵𝗶𝘀 𝗮𝗿𝘁𝗶𝗰𝗹𝗲, 𝗜 𝗱𝗶𝘀𝗰𝘂𝘀𝘀 𝘁𝗵𝗲 𝗿𝗼𝗹𝗲 𝗼𝗳 𝗱𝗮𝘁𝗮 𝗮𝗻𝗮𝗹𝘆𝘀𝘁𝘀 𝗮𝗻𝗱 𝘀𝗵𝗮𝗿𝗲 𝗮 𝘀𝘁𝗲𝗽-𝗯𝘆-𝘀𝘁𝗲𝗽 𝗴𝘂𝗶𝗱𝗲 𝗼𝗻 𝗵𝗼𝘄 𝘁𝗼 𝗯𝗲𝗰𝗼𝗺𝗲 𝗼𝗻𝗲.
Data Analyst and Data Scientist are the buzzwords of the present day. We have seen a sudden inclination towards this career path in recent times. A Data Analyst job role has countless benefits, most notably its compensation and that’s one of the many reasons why everyone is so excited about it. But data analysis is not a piece of cake and has its own struggles. So, before you get swayed away by its better side, do a fact check and make sure this role is a right fit for you.
Since its an emerging role, there is no fixed curriculum to follow about. At present, there are heaps of online paid courses and bootcamps out there assuring to make you a job-ready data analyst. But honestly, I think you can become a data analyst without spending a dime. All you need is to devote 3–4hrs daily and a stable internet connection. To help you on your journey, here I am penning down a brief blog on who exactly is a data analyst and more importantly how to become one on your own without much expense.
Data Analytics Market will increase from $23 billion to $133 billion between 2019 and 2026. Here is the Fastest way You can Become a Professional Data Analyst. You may have spent too many hours watching YouTube Videos, and Udemy Courses, but it may not help.
In this article, I remove all the fluff and give you the fastest path to go from ZERO to FULL-TIME DATA ANALYST. Also, I will share the major mistakes almost every data analyst makes. So, you will try to not repeat those.
Let’s get into it.
Who Is a Data Analyst?
Data analysts collect, analyze, and report valuable insights found in data. The daily duties of data analysts include:
- Collecting data from a variety of sources.
- Preparing the data for analysis (i.e. cleaning the data).
- Performing an exploratory data survey.
- Modeling and analyzing data.
- Creating data visualizations and reports.
There is a lot of hype around this profession, but it’s hard to overestimate the role of data analysts in today’s data-driven organizations. With proper data analysis in place, a company can understand its customers better, improve the targeting of marketing campaigns, organize better logistics, improve HR management, prevent fraud, and much more
To put it in another words, Data Analyst is the one who turns this raw data into information in order to draw out meaningful, actionable insights. These insights are then used to help businesses make smart decisions. And these insights are then used by the companies in many ways ranging from forming marketing strategies to making improvements in the production process.
7 Steps for Becoming a Data Analyst
To succeed in this career path, I’ve mentioned that you’ll need a specific set of skills. Here are seven steps that will help you acquire them.
1. Learn Statistics
To spot real trends, patterns, and causal relationships, you need to be familiar with basic statistical concepts such as significance, predictors, response variables, leading indicators, lagging indicators, hypothesis testing, etc. Just building a correlation graph is not enough to understand the true relationships between variables and all the underlying processes and interactions. Learning statistics is one of the key first steps to becoming a data analyst.
Resources:
- Khan academy YouTube
2. Statistics by Marin
3. Statquest YouTube channel
2. Good at Excel
Even though Excel might not be the most effective tool for data analysis — especially when working with large amounts of data — you are still likely to find lots of company data stored in Excel spreadsheets. So, as a data analyst, you should be very familiar with Excel. You should be able to collect data from spreadsheets and know when it can be more effective to do data analysis in Excel. Excel is a very powerful analytical tool, but as you’ll learn with experience, SQL often works better for data analysis.
Features such as data filters, functions, formulas, Charts and plots, Pivot table, vlookup and VBA macros should be covered in one week to do data analysis. Beginner to Advanced level expertise of Excel is required for a good data analyst.
Resources:
1. Analysing Data with Excel | IBM
2. Freecodecamp’s MS Excel Tutorial for Beginners :
3. Data Analytics In Excel Full Course | Intellipat
4. Excel Tutorial | Intellipat
5.Advanced Excel Full Course 2022 | Simplilearn
6. Data Analytics Using Excel | Simplilearn
7. Beginners to Pro Fre/e Excel | Chandoo
3. Learn SQL
Companies of all sizes usually store most of their data in relational databases, and SQL is a language used to interact with relational databases. So, if you want to be able to extract data from these databases and then work with it, you should learn SQL.
In big organizations, you can probably rely on database administrators and other “IT guys” to extract data from relational databases. However, knowing SQL lets you retrieve data on your own, giving you additional speed and independence. Data analysts with SQL knowledge can respond more quickly to requests, and thus add more value to their companies.
Resources:
Here’s 8 free Courses that’ll teach you better than the paid ones.
- SQL Full-course by Simplilearn
2. Learn Basic SQL In 15 Mins | Learn BI Online
3. SQL Basic Tutorial | TechTFQ
4. MySQL Tutorials for beginners | Edureka
5. NOSQL databases tutorial | freeCodeCamp
4. BI Tools
Data visualization helps in conveying your story in simple words so that everybody can understand. Week 3 and 4 can be spent in learning BI Tools for data visualization. Data visualization enables you to find patterns in the data by which you can create a good story to present to your clients.
Power BI, Tableau and Qlik sense are three most popular tools for this in the industry. However, you can just learn one or two tools and that should be enough to make you a good data analyst. I personally recommend Tableau since I find it more easier and convenient comparatively. Beginner to Intermediate level expertise is required.
Resources:
1. Abhishek Agarwal
2. Bharti consultancy
5. Python
Python is another essential tool for modern data analysts. Of course, data analysts don’t need the same programming skills as software engineers or developers. But they are expected to know how to clean data, explore and visualize it, and build simple machine learning models with Python. If you want to do data analysis, you should be familiar with Python’s popular data analysis and visualization packages.
Resources:
1. Learn Python Full Course for Beginners by: freeCodeCamp
2. Learn Python basics for Data Analysis: Google
3. Introduction to Python Programming: Udacity
4. Python for Data Science by: IBM
5. CS50P from Harvard University
6. Numpy, Pandas, Matplotlib
These are the libraries provided by Python for data visualization and other purposes. Numpy and pandas are essential for analyzing data whereas matplotlib and seaborn lets you visualize your data. You can learn either Matplotlib or Seaborn as both of them serve the same purpose.
Resources:
1. Codebasics Numpy playlist
2. Codebasics pandas playlist
3. Codebasics matplotlib playlist
4. Codebasics seaborn tutorials
7. Get Industry experience
Companies rarely require industry experience from data analysts, but it can definitely be a key advantage. If you have gained some experience in a specific industry, it might be easier for you to find a job in this domain — even if your previous role was not directly related to data analysis. Understanding a domain will help you differentiate between patterns that are really important for business and those that are irrelevant or insignificant.
Grab Communication skills
To make others understand your data and findings, you need to present your data in a storytelling format with concrete results and values so that other people can understand what you are saying. Hence, good communication skill is a must for a data analyst.
That’s about it for this article.
I am always interested and eager to connect with like-minded people and explore new opportunities. Feel free to follow, connect, and interact with me on LinkedIn, Twitter, and YouTube. My social media — — click here You can also reach out to me on my social media handles. I am here to help you. Ask me any doubts regarding AI and your career.
Wishing you good health and a prosperous journey into the world of AI!
Best regards,