The year 2023 has been a pivotal chapter, shaping the landscape of data analysis and insight generation. As we step into the promising horizon of 2024, data analytics beckons with fresh opportunities and evolving challenges. Charting a course through this dynamic terrain requires expertise and a strategic roadmap, a blueprint that navigates the intricacies of data exploration and interpretation. Enter the Learning Path to Become a Data Analyst and Skills Required in 2024. This comprehensive guide equips aspiring analysts with the indispensable skills and knowledge to thrive in this ever-evolving field. Join us as we unravel the layers of this transformative journey, unveiling the key milestones and insights that will shape your voyage toward becoming a proficient data analyst in the year ahead.
In this article you will get to now how to become a data analyst, its a complete data analytics roadmap in 2024 that will help you to become a data analyst and show the path to become analyst. In this roadmap for data analyst here it will tell should you start a career as a data analyst what skills you should required.
In recent years, there has been a surge in the number of people looking for information on becoming data analysts. The role has grown in popularity, which is unsurprising given the vast data we generate today.
Companies in all industries want professionals who can collect data, evaluate it, derive valuable data-driven insights from it, and use those insights to help them address critical business challenges. As a result, there are several reasons why you would choose to work as a data analyst:
Companies in all industries want professionals who can collect data, evaluate it, derive valuable data-driven insights from it, and use those insights to help them address critical business challenges.
A data analyst is a professional who has the technical skills to work with data and the analytical abilities to extract meaningful information and actionable insights from data sets. Their role is to bridge the gap between raw data and informed business decisions by applying statistical methods, programming, data visualization, and problem-solving techniques.
There has never been a better moment to start a career in data analysis. In this essay, I’ll walk you through the entire process of becoming a Data Analyst in 2024. You must master the following skills:
Are you feeling overwhelmed? Don’t worry. We’ve put together a 6-month plan to help you learn these abilities. To make things easier, we’ve separated the roadmap into two quarters. This Skills Required For Data Analytics path assumes that you will study for at least 4 hours per day, 5 days per week. If you stick to this strategy, you should be able to:
In the first quarter, we aim to prepare you for a Data Analytics Internship or even an entry-level Data Analyst job! So here, you must focus on learning three primary data analytics skills: Microsoft Excel and SQL Programming, Storytelling with Data, and EDA using ChatGPT. Now. Let’s check out what you need to learn.
In the first month, focus on the tools that every Data Analyst must know: Microsoft Excel and SQL. These tools will help you with data exploration, the first step in data analysis.
Under Excel, you should focus on
Within SQL, learn things like Querying Databases and managing and manipulating data stored in relational databases. For practice, you may do SQL projects like these. This will make you fluent in SQL.
You will learn to tell stories with your data in the second month. For this, focus on learning one of these data visualization tools: Tableau, PowerBI, or Qlik Sense. After that, use these tools to analyze and present a given data visually appealing and interactively. You should also learn how to build an interactive Dashboard on topics like:
Apart from that, you will also learn EDA or Exploratory Data Analysis. This is the process of investigating the data to discover hidden patterns. It includes techniques like Univariate / Bivariate Analysis.
With the advent of ChatGPT, tasks like EDA can be done much faster with tools like Code Interpreter. To do this, you only need to provide your dataset to ChatGPT and ask questions like Check for missing values. How do we attribute these missing values with mean or median? What visualization is most suitable for representing a given dataset?” or “Checking for outliers in a dataset?”.
You can enhance your EDA questioning skills by learning Prompt Engineering. This will help you write effective prompts to elicit desired information from LLMs like ChatGPT.
As I said at the beginning, soft skills are equally important as technical skills and Data Analyst Learning Path for a Data Analyst role. So, in this entire first quarter, you must also sharpen your Communication and Analytical Skills. Specific to communication skills, you may start writing blogs or making YouTube videos to share your learnings. This improves your writing as well as spoken skills. Additionally, for Analytical skills, you must solve various Logical Reasoning and Data Interpretation problems.
At the end of this first quarter, you will have a solid understanding of drawing inferences from data and building stories around them. You know what, at this point, you may start applying for Internships and even entry-level Data Analyst roles.
You will need to create a Resume, Cover Letter, and LinkedIn account by now. And given you know ChatGPT and the art of Prompt Engineering, you may do all that in minutes.
We have created a series of videos on how to do this. You may refer to them as well.
Moving on to the Second Quarter.
Also Read: Top 10 SQL Projects for Data Analysis
We aim to prepare you for full-fledged data analyst roles in the second quarter. So our focus should be on strengthening our subject knowledge. For a good Data Analyst, in depth knowledge of mathematics, statistics, or programming for that matter, is a must. These skills give a solid technical foundation to perform Exploratory Data Analysis, and Basic Statistics.
The first thing we will learn in month 4 is a general-purpose programming language like Python/R. Now, Python is a popular choice among Data Analysts. This is because:
Basic Statistics follows this. Under statistics, focus on:
This is the second last month of our journey. This month is all about practice. You have learned all the skills you need to know. So what’s next? Next is end-to-end projects, where you solve a real-world problem like a real Data Analyst Learning Path does.
Projects also give you the much-needed platform to practice whatever you have learned, revise your skills, and become a better data analyst. This month, these are the projects you may do. Apart from this, you will also practice Data Analytics Interview Questions. Here’s a video we have done on this.
Finally, you should also have basic knowledge of a few simple Machine Learning Algorithms. Namely, Linear Regression, Logistic Regression, Decision Tree, K-Nearest Neighbour, etc.
Believe it or not, these beginner-level ML algorithms can be applied to almost any data problem.
The soft skill we will focus on in this second quarter is: structured thinking. A great way to do so is by practicing Guesstimation and going through various Case Studies. With structured thinking, you can learn how Data Analysts work and think.
Another skill to learn is Mind Mapping, which will help you chalk out your thinking structure.
Guys, within this quarter, you may begin applying for full-fledged Data Analyst roles in the industry. Earlier, we told you how to create a LinkedIn profile, resume, and cover letter. Update them as per the job experience you have.
Now, the next step is getting a job! We have made videos on landing a job in the Data Tech domain. These may help you get a callback and crack interviews with the help of Generative AI.
Becoming a proficient data analyst in 2024 is an intricate yet rewarding path, promising opportunities amidst evolving challenges. As we conclude this comprehensive guide, it’s evident that the demand for skilled data analysts continues to surge, creating a landscape ripe with prospects for those equipped with the right expertise. As you navigate this transformative journey, embracing the complexities and challenges while staying committed to learning and growth will pave the way for a fulfilling career as a data analyst in the year ahead.
Hope you like the article and get your doubts clear about roadmap for data analyst, in this article their is a complete guide for data analytics roadmap 2024. We have also a complete guide to become a data scientist roadmap check this!
A. The five types of data analytics are Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, Prescriptive Analytics, and Exploratory Analytics.
A. Data analytics is useful for extracting insights, making informed decisions, improving efficiency, and identifying trends/patterns within large datasets.
A. Yes, data analytics is considered a promising career with high demand and growth opportunities due to the increasing reliance on data-driven decision-making across industries.
A. The job of a data analyst involves collecting, cleaning, and analyzing data to uncover trends, patterns, and insights. They also develop reports, dashboards, and visualizations to communicate findings and aid decision-making processes within organizations.
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Hello, although I don't have much knowledge about data science, but the article you wrote was very motivating and encouraged me to take a step in this direction. Thank you for sharing your knowledge and experience with us.
This was the best I have seen today .. thanks so very much
Hats off to Sanjana Rajpan and Analytics Vidya team for such a detailed and well-structured article.
This road map for data analyst is the best of all.
I'm interested, how can i go ahead