Blockchain: is het cybersecurity-risico de beloning waard?
De laatste tijd staan de krantenkoppen echter in het teken van oplichting en illegale activiteiten gerelateerd aan blockchain, met het ene ...
80% van de dataprofessionals
Er is een reden waarom <anchor>80% van de dataprofessionals</anchor> gelooft dat blockchain de rest van het decennium de grootste impact zal hebben op de veilige opslag en overdracht van gegevens. Blockchain kan gegevens beschermen dankzij een innovatieve coderingsfunctie die ongeoorloofde toegang tot gegevens tijdens de overdracht voorkomt, waardoor de toegang van kwaadwillende actoren wordt voorkomen. En omdat veel cybercriminelen tijdens de overdracht gegevens onderscheppen, kan dit voordeel zeer nuttig zijn om cruciale informatie te beschermen.
How to Become a Data Analyst (2024 Guide) | BrainStation®
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1. [Career Guides](/career-guides)
2. How to Become a Data Analyst

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- ## [![Data Analyst](https://wpassets.brainstation.io/app/uploads/2021/11/09154349/BrainStation-Data-Analyst.svg)\ Data Analyst](https://brainstation.io/career-guides/data-analyst)

  - The Basics

    - [Data Analyst vs Data Scientist](https://brainstation.io/career-guides/data-analyst-vs-data-scientist)
  - On The Job

    - [What Does a Data Analyst Do?](https://brainstation.io/career-guides/what-does-a-data-analyst-do)      - [What is a Data Analyst?](#what-is-a-data-analyst)
      - [Data Analyst Responsibilities](#data-analyst-responsibilities)
      - [What Tools Do Data Analysts Use?](#what-tools-do-data-analysts-use)
      - [Do Data Analysts Code?](#do-data-analysts-code)
      - [Programming Languages for Data Analytics](#programming-languages-for-data-analytics)
      - [What is Data Analytics?](#what-is-data-analytics)
      - [Types of Data Analysis](#types-of-data-analysis)
      - [Benefits of Data Analytics](#benefits-of-data-analytics)
      - [Data Analytics in Marketing](#data-analytics-in-marketing)
- ## [![How to Become a Data Analyst](https://wpassets.brainstation.io/app/uploads/2021/11/09154349/BrainStation-Data-Analyst.svg)\ How to Become a Data Analyst](https://brainstation.io/career-guides/how-to-become-a-data-analyst)

  - Skills

    - [What Skills Do You Need to Be a Data Analyst?](https://brainstation.io/career-guides/what-skills-do-you-need-to-be-a-data-analyst)      - [Data Analyst Technical Skills](#data-analyst-technical-skills)
      - [Data Analyst Soft Skills](#data-analyst-soft-skills)
    - [Is Data Analytics Hard to Learn?](https://brainstation.io/career-guides/is-data-analytics-hard-to-learn)      - [Can I Learn Data Analysis on My Own?](#can-i-learn-data-analysis-on-my-own)
      - [How Long Does It Take to Become a Data Analyst?](#how-long-become-data-analyst)
      - [How Long Does It Take to Learn Python for Data Analysis?](#how-long-does-it-take-learn-python-data-analysis)
      - [Are Data Analytics Courses Worth It?](#are-data-analytics-courses-worth-it)
    - [Do You Need a Degree to Be a Data Analyst?](https://brainstation.io/career-guides/do-you-need-a-degree-to-be-a-data-analyst)      - [Is a Data Analytics Certificate Worth It?](#is-data-analytics-certificate-worth-it)
      - [Why Learn Data Analytics?](#why-learn-data-analytics)
  - Career Path

    - [Is Data Analytics a Good Career?](https://brainstation.io/career-guides/is-data-analytics-a-good-career)      - [Data Analyst Job Outlook](#is-data-analytics-in-demand)
      - [Data Analyst Career Path](#data-analyst-career-path)
      - [Jobs in Data Analytics](#jobs-in-data-analytics)
  - Getting The Job

    - [How To Write A Data Analyst Cover Letter](https://brainstation.io/career-guides/how-to-write-a-data-analyst-cover-letter)      - [What Are Data Analyst Cover Letters?](#what-are-data-analyst-cover-letters)
      - [Data Analyst Cover Letters - a Step-by-Step Guide](#data-analyst-cover-letters-step-by-step-guide)
      - [Getting Started - What is the Purpose of the Cover Letter?](#getting-started-what-is-the-purpose)
      - [How to Create an Outline for a Data Analyst Cover Letter](#how-to-create-an-outline-for-data-analyst-cover-letter)
      - [What to Include in Your Data Analyst Cover Letter?](#what-to-include-in-your-data-analyst-cover-letter)
      - [Data Analyst Cover Letter Examples](#data-analyst-cover-letter-examples)
      - [Data Analyst Cover Letter Template](#data-analyst-cover-letter-templates)
    - [Data Analyst Resume Examples](https://brainstation.io/career-guides/data-analyst-resume-examples)      - [What Are Data Analyst Resumes?](#what-are-data-analyst-resumes)
      - [Data Analyst Resumes - a Step-by-Step Guide](#data-analyst-resumes-step-by-step-guide)
      - [Getting Started - What Is the Purpose of the Resume?](#getting-started-what-is-the-purpose)
      - [How to Create an Outline for a Data Analyst Resume](#how-to-create-an-outline-for-data-analyst-resume)
      - [What to Include in Your Data Analyst Resume?](#what-to-include-in-data-analyst-resume)
      - [What Skills Should You Put on a Data Analyst Resume?](#what-skills-should-you-put-on-a-data-analyst-resume)
      - [Data Analyst Resume Template](#data-analyst-resume-template)
    - [Data Analyst Interview Questions](https://brainstation.io/career-guides/data-analyst-interview-questions)      - [Common Skills-Based Data Analyst Interview Questions](#list-of-data-analyst-questions-data)
      - [Common Technical Data Analyst Interview Questions](#list-of-data-analyst-questions-technical)
      - [Common Personal Data Analyst Interview Questions](#list-of-data-analyst-questions-personal)
      - [Common Situational Data Analyst Interview Questions](#list-of-data-analyst-questions-leadership)
      - [Common Behavioral Data Analyst Interview Questions](#list-of-data-analyst-questions-behavioral)
      - [Data Analyst Interview Questions From Top Companies](#list-of-data-analyst-questions-top-companies)

Scroll

2024 Guide

# How to Become a Data Analyst

BrainStation’s Data Analyst career guide is intended to help you take the first steps toward a lucrative career in data analysis. The guide provides an in-depth overview of the data skills you should learn, the best data analysis training options, career paths in data analytics, how to become a Data Analyst, and more.

### Become a Data Analyst

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To become a **Data Analyst**, you must have key data analysis skills and an ability to glean insights from large data sets.

Data analytics is a field ripe with opportunity, as companies across all industries have made big commitments to big data, building out their analytics departments – especially in telecommunications, insurance, advertising, financial services, healthcare, and technology.

That growth is expected to continue well into the future as industries lagging in big data analytics adoption – including education, government, and manufacturing – have pledged to increase their big data analytics activity in the future.

**How to Become a Data Analyst in Five Steps:**

1. [Learn data analytics fundamentals](https://brainstation.io/career-guides/how-to-become-a-data-analyst#learn-data-analytics-fundamentals)
2. [Work on projects to develop your practical data analytics skills](https://brainstation.io/career-guides/how-to-become-a-data-analyst#work-on-projects-to-develop-your-practical-data-analytics-skills)
3. [Develop visualizations and practice presenting them](https://brainstation.io/career-guides/how-to-become-a-data-analyst#develop-visualizations-and-practice-presenting-them)
4. [Develop a Data Analyst portfolio to showcase your work](https://brainstation.io/career-guides/how-to-become-a-data-analyst#develop-a-data-analyst-portfolio-to-showcase-your-work)
5. [Apply to relevant data analyst jobs](https://brainstation.io/career-guides/how-to-become-a-data-analyst#apply-to-relevant-data-analyst-jobs)

## 1\. Learn Data Analytics Fundamentals

When thinking about how to become a Data Analyst, your first step should be to learn the data analysis fundamentals and data analysis tools like advanced Microsoft Excel; programming languages SQL, Python and R; Spark and Hadoop for number-crunching; and Tableau, Matplotlib, or ggplot2 for creating beautiful visualizations that bring data to life.

[Data analysis courses](https://brainstation.io/course/online/data-analytics) can be a great way to learn these **fundamental data skills**, giving you a strong footing on all these platforms, and the ability to gain hands-on experience with:

- Data management
- Statistical programming
- Programming languages
- Data cleaning
- Data visualization

## 2\. Work on Projects to Develop Your Data Analytics Skills

If you want to become a Data Analyst, you’ll need to get a firm grasp on a Data Analyst’s basic tools. Once you’ve done so, you can begin putting your knowledge to work. Successful Data Analysts will need to keep up-to-date with the latest and greatest tools associated with data analysis, including:

- Spreadsheets and querying languages depended on by Data Analysts, such as XML and SQL
- Programming languages and frameworks commonly used by Data Analysts like Python, R, and Hadoop
- Visualization tools popular with Data Analysts like Tableau, PowerBI; Plotly, Bokeh, and Matplotlib

They will also need to have experience with one or several leading data analysis platforms, including Google Analytics and Adobe Analytics.

Put together practice projects that touch on all the different stages of data analysis: researching companies and market opportunities, establishing the parameters of the data you need to collect, gathering and cleaning that data, then modeling and analyzing it using custom-built algorithms.

Finally, turn the insights you’ve drawn from your work into beautiful visualizations, or even try organizing them into a dashboard that allows others to query and interact with your dataset in a user-friendly way.

**Data Analytics Tools List**

- XML

- SQL

- Python

- R

- Hadoop

- Tableau

- PowerBI

- Plotly

- Bokeh

- Matplotlib

- Google Analytics

- Adobe Analytics


Try taking on a range of practice projects to grow – and demonstrate – your ability to work with different types of data, mining structured data, text and images, audio, or even video to perform statistical analysis, identify causality, and even make predictions.

As you go, you’ll also be practicing the **soft skills** that elevate the best Data Analysts above their peers:

- A good eye for detail
- An ability to think creatively and analytically
- Excellent communication skills
- A head for numbers

### Data Analysis Steps

1. Research companies and market opportunities
2. Establish the parameters of data you need to collect
3. Gather and clean data
4. Model and analyze data using custom-built algorithms

## 3\. Develop Visualizations and Practice Presenting Them

To become a Data Analyst, you’ll want to start using programs like Tableau, PowerBI, Bokeh, Plotly, or Infogram. Practice building your own visualizations from scratch, finding the best way to let the data speak for itself.

Microsoft Excel comes into play even during this step: although the basic premise behind spreadsheets is straightforward – making calculations or graphs by correlating the information in their cells – Excel remains incredibly useful after more than 30 years and is virtually unavoidable in the field of data science.

But creating visualizations is just the beginning. Data Analysts use these visualizations to present their findings, and that requires strong presentation skills.

_Presenting can be improved with practice. Start small with friends first before moving onto colleagues._

These communication skills may come naturally to you, but if not, you can improve with practice. Start small, if necessary, delivering presentations to a single friend for example, before moving on to colleagues.

## 4\. Develop a Data Analyst Portfolio to Showcase Your Work

One of the most important steps to take when planning how to become a Data Analyst is deciding how you will demonstrate your data skills and knowledge. A professional portfolio is a must, and to get started, you should put the code you’ve written (even as part of your coursework) up on GitHub to show what you can do and begin building your professional portfolio.

**3 Tips for Building a Data Analyst Portfolio**

- Display code you’ve written on Github or another similar portfolio platform
- Join Data Analyst communities like Kaggle to grow your expertise and find inspiration
- Research, develop and complete a personal project, making sure to carefully document and visualize its creation

When it comes to choosing your data projects, pick something that you’re really interested in, ask a question about it, and try to answer that question with data.

A well-executed data project that you pull off on your own can be a great way to demonstrate your data analysis abilities and impress potential hiring managers.

## 5\. Apply to Relevant Data Analyst Jobs

There are a wide variety of Data Analyst jobs you can get with data skills. All of the following roles draw heavily on data analytics and can be entry-level or more senior data roles.

There are many other variations out there—new applications for data analytics are being developed all the time, and even the jobs listed here will continue to evolve as data analysis becomes more prevalent.

Such a highly dynamic field, according to consulting firm Mckinsey & Co., means **demand may outpace the projected supply of data professionals by 50 or 60 percent**, making Data Analyst jobs even harder to fill. All of which is to say that if you have Data Analyst skills, you’re already in a great position when it comes to following a Data Analyst career path.

### Data Analyst Job Titles

- Data Analyst
- Database Administrator
- Data Scientist
- Business Analyst
- Business Intelligence Analyst
- Transportation Logistics
- Statistician

- Systems Analyst
- Healthcare Data Analyst
- Operations Analyst
- Data Engineer
- Quantitative Analyst
- Data Architect
- IT Business Analyst

## Data Analyst Job Descriptions

Many Data Analyst job descriptions list a Bachelor’s degree as a requirement for data-related positions. Sometimes, that’s non-negotiable, but as demand for data skills outstrip supply—and given the often specialized, highly technical nature of the work—the proof is increasingly in the pudding. **That is, data skills often outweigh mere credentialism.**

_What’s most important to hiring managers is an ability to demonstrate mastery of the subject in some way, and it’s increasingly understood that this demonstration doesn’t have to follow traditional channels._

If you’re worried your skillset or experience doesn’t lend itself to data analytics – or that you’re too far behind to start now – take comfort in the fact that there’s an abundance of career-switchers who have thrived after picking up those technical skills with data.

In fact, BrainStation’s most recent Digital Skills Survey reported that 76 percent of respondents did not begin their career in data, and nearly two-thirds have been working in the field for only five years or less. Lifelong learning is a part of the Data Analyst’s job.

#### 76%

of those working in data did not begin their career in the field.

In the end, there’s no single path toward becoming a Data Analyst, and that’s good news if you’re hoping to land a data analysis role. Because Data Analysts can work across many different industries, may be generalists or highly specialized, and often play an interdisciplinary role in a company, even job titles in data analysis can be quite varied.

For those working in marketing, communications, social media, journalism, or content management, an understanding of data is increasingly becoming not just an asset but a necessity for digital strategies.

In almost every case, data analytics skills will add to the compensation you can command, especially highly specialized skills.

## Demand for Data Analysts

Demand for Data Analysts and for data skills is surging. According to a report from McKinsey, the United States faces a shortage of 140,000-190,000 people with Data Analyst skills, as well as 1.5 million Managers and Analysts who understand how to use data analysis to drive decision-making.

> The U.S. faces a shortage of up to 190,000 people with Data Analyst skills.

McKinsey

What’s more, the World Economic Forum (WEF) found that by 2022, 85% of companies will have adopted big data and analytics technologies. WEF also found that 96% of companies were planning or likely to plan to hire new permanent staff with relevant skills to fill roles related to data analytics.

Unsurprisingly, the role has been called **one of the most in-demand jobs** by LinkedIn, Glassdoor, the US Bureau of Labor, and Robert Half, among others.

## How Do I Become a Data Analyst With No Experience?

If you’re wondering how to become a Data Analyst with no experience in the field, **your first step is to acquire the relevant data skills**. Some of these skills are relatively easy to acquire individually, others are more complex.

Even so, the data analytics field as a whole is large and diverse enough that it can be difficult to know where to even start when looking to learn data analysis. A structured learning environment that systematically covers all the basics is the best introduction to the field and will ensure that, from the outset, you’ll be clear on what you still need to learn.

Data Analytics courses and data science bootcamps, for example, are a popular option for aspiring Data Analysts looking for how to get started in data analytics. Here, you can learn key data skills and gain hands-on experience in an accelerated learning format with the confidence that the time you’re spending on learning is focused on the areas where it will benefit you most.

Once you’ve acquired key data skills, the next step to becoming a Data Analyst is to practice using these skills, ideally by building your own projects that you can share publicly.

_An effective way to display your work – and your data skills – is by posting the code you’ve written, even as part of your coursework, on GitHub. This will show off what you can do, and form the beginning of your professional portfolio._

Don’t stop at the basics. **An ambitious, well-executed data project that you pull off on your own is a great way to demonstrate your data abilities** and impress potential hiring managers hiring when applying for a Data Analyst job.

Document your journey and present your findings – beautifully visualized – with a clear explanation of your process, highlighting your technical data skills and creativity.

Finally, joining an online network of Data Scientists like Kaggle can be a great way to show that you’re engaged with the community, show off your chops as an aspiring Data Analyst, and continue to grow both your expertise and your outreach.

### How to Become a Data Analyst With No Experience

1. Acquire the relevant data skills by studying or enrolling in a data analytics course/bootcamp
2. Practice using those skills by building and developing data analytics projects
3. Gather projects into a portfolio and display it on Github
4. Practice visualizing and presenting your data analytics projects to an audience
5. Join online communities such as Kaggle to grow your expertise and network

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### RECOMMENDED DATA aNALYTICS COURSES

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The Data Science bootcamp is an intensive course designed to launch students’ careers in data.](https://brainstation.io/course/online/remote-data-science-bootcamp)

[CertificateData Science Course\
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Taught by data professionals working in the industry, the part-time Data Science course is built on a project-based learning model, which allows students to use data analysis, modeling, Python programming, and more to solve real analytical problems.](https://brainstation.io/course/online/data-science)

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