Learning Roadmap for Aspiring Data Analysts in 2022

In this article, we will discuss an intriguing profession within the field of data known as Data Analyst. We will explore the roadmap for aspiring Data Analysts in 2022.

Interested in becoming a Data Analyst? The global market for big data is projected to reach $300 billion by 2022. As a result, there is a significant surge in demand for data-related positions like data analyst, data scientist, data engineer, and data architect. IT companies are actively seeking individuals with the necessary skillsets to fill these roles.

The salary and growth opportunities will be prime factors attracting individuals to these positions. With immense amounts of data being collected constantly, there is a growing demand for skilled data professionals.

In this article, we will discuss the various skills required to excel as a data analyst. We will explore the tools, abilities, and top certifications that demonstrate your excellence in this field. Let’s get started!

Roadmap for acquiring knowledge as a Data Analyst

data analyst roadmap

The initial query that arises in our thoughts is, who exactly is a data analyst and what is their role?

Put simply, a data analyst’s role entails gathering, manipulating, and examining data to uncover meaningful insights that inform decision-making.

Typically, an analyst’s primary task is to manipulate raw data in order to generate practical insights. The majority of analysts do not focus on developing the central machine learning or deep learning models.

Data analysts rely on a variety of tools to handle and manipulate data in their work. It is crucial for them to possess expertise in using various tools and statistical techniques.

In the upcoming sections, we will explore each ability and its associated certifications.

1. Data analysis

Every data professional needs to possess a solid understanding of statistics and mathematics in order to effectively interpret data.

If you are completely new to the subject, you should focus on descriptive and inferential statistics. It is advisable to dedicate a few weeks to thoroughly understanding these topics and practicing through problem-solving activities. Believe me, the effort you invest in mastering these concepts will pay off immensely.

Top Certifications – Most reputable certifications or highly regarded certifications.

  • University of Michigan (Coursera) – Statistics with Python . This specialization course will enable you to apply the stats knowledge using python which is crucial.
  • Some of top books that you can read are – Practical stats for Data science and Naked Statistics.

2. Excel is a software program designed for performing mathematical calculations, organizing data, and creating spreadsheets.

Excel is highly utilized by data analysts for processing and analyzing data. Although there are various other tools available for working with data, Excel remains significant.

Excel offers a wide range of features including charts, analysis capabilities, VBA programming, macros, filters, and formulas. Analysts commonly utilize the Pivot table function and VLOOKUP function the most in Excel.

Therefore, it is recommended that you actively engage in courses that provide expertise in advanced excel topics as this will greatly impress your employer. Consequently, dedicate yourself to extensive practice in order to efficiently acquire and excel in these valuable skills.

Top Certifications –
Leading Certifications

  • 365 Data science – Introduction To excel. This is one of the underrated course but it offers more than you need to learn about Excel for data analysis.
  • Rice university (Coursera) – Intro To Data Analytics using Excel. This course is a part of Business stats and analysis specialization and teaches you all about excel from basics to advanced level.

I only need one option for paraphrasing the sentence: “SQL.”

Only a data analyst with experience can provide additional insight into the significance of utilizing SQL in analysis. As an analyst, it is crucial to have knowledge of databases and their management. You will be responsible for executing CRUD operations on the company’s database. In this regard, there is no alternative tool as versatile and adaptable as SQL.

To effectively analyze data, it is necessary to acquire proficiency in several subjects including Joins, Table operations, Unions, group by, order by, and other related topics.

Top certifications

  • Duke university (Coursera) – Excel to MySQL: Analytic Techniques for Business Specialization. . This specialization will help you to learn all the SQL concepts required for data analysis.
  • Some of the best books were – Learning SQL (Oreilly) 3rd edition.

4. Tools for Business Intelligence

The most commonly utilized tools among business analysts and data analysts are known as business intelligence or BI tools. These tools can be operated using Python, R, and SQL.

People primarily use BI for creating dashboards, generating reports, and visualizing data. The best BI tools for 2022 include Tableau, PowerBI, and Looker.

If you wish to gain expertise in the mentioned subjects, you have the option to refer to the official documentation and user tutorials provided on their respective websites. However, if you are interested in obtaining certification for mastering these subjects, you can enroll in the courses mentioned below.

Highly sought-after certifications

  • University of California (Coursera) – Data Visualization with Tableau Specialization. This course is more than enough for your tableau learning journey.
  • Udemy – Power BI, the complete introduction. . If you are beginner, this is the best course which will guide you to master power BI.
  • For looker, you can follow their tutorials on their website which are very organized.

5. Coding language.

Possessing expertise in one or more programming languages will greatly benefit you. While some companies may not prioritize programming languages for analyst positions, having a strong understanding of them will prove advantageous.

I highly advise learning both Python and R as they both provide powerful libraries like numpy, pandas, and mat plot lib in Python, and dplyr, ggplot in R.

Having a thorough understanding of these libraries can enhance the efficiency and precision of your analysis.

Top certifications –

Best certifications –

Top ranked certifications –

Most sought-after certifications –

Highest-rated certifications –

  • IBM Data analytics professional certificate and Google’s data analytics professional certificate can be the best courses to master Python and R for analytics respectively. The former will focus more on python and later focus more on R.
  • Free code camp – Data analysis using Python. This course will teach you all the libraries and methods for data analysis using python.
  • Top books for Python and R for data analysis are – Python for Data analysis 2nd edition (Oreilly) and Data Analytics with R.

6. Collection of work and curriculum vitae

Once you have mastered all the necessary skills, it is crucial to highlight the final project in your portfolio and resume. Engaging in real-world projects that demand the application of all the skills you have acquired is essential.

Furthermore, it is essential to allocate sufficient time towards crafting your resume, effectively showcasing your skills, projects, and various experiences. Ultimately, the culmination of your hard work can only be presented through an exceptional resume and a diverse portfolio.

Data storytelling is a crucial skill that shouldn’t be overlooked. Even if you excel in technical skills and tools, without a compelling narrative, your analysis will be futile. Therefore, it is imperative to effectively present your discoveries in an appropriate format and medium.

Regarding CV

  • Data camp – Tips to build your resume for data science and analytics.
  • Krish Naik – YouTube Channel dedicated for data science. You can find many videos related to resume building and portfolio building in this amazing channel.

The resources and skills provided in this data analyst roadmap are extremely important for developing your career in the field of data, especially analytics.

Roadmap for Data Analysts – The Conclusion

The data analyst roadmap provided here includes nearly all the essential skills required in the on-demand industry. It has been developed through interviews with numerous experienced data professionals. I understand your enthusiasm to enter the field of analytics, so these skills are invaluable for you. Invest some time in comprehending and practicing them, solving problems, and undertaking real-world projects. Soon, you will be prepared to be recognized as a Data analyst.

That would be everything for the moment. Enjoy your learning!

Who qualifies as a Data Analyst when reading more about them?


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