7 answers
Jane
Student
Cardiff, Wales, United Kingdom
8
Questions
Asked
622 views
Data analysts, could share your experience and answer this questions? Thank You very much
What skills are most important? What skills you use every day?
What qualifications would you recommend?
What are the biggest challenges?
What advice would you give someone starting this career?
Login to comment
7 answers
Akasha Ali
Student Researcher and Peer Advisor
25
Answers
Houston, Texas
Updated
Akasha’s Answer
Hi Jane,
Data analytics is a great career if you enjoy solving problems and working with data. Here are my thoughts:
Most Important Skills: Critical thinking, problem solving, attention to detail, communication, and curiosity. Technical skills like Excel, SQL, python or R, and data visualization tools(such as Tableau or power BI) are also very valuable.
Skills used every day: cleaning and organizing data, analyzing trends, creating reports or dashboards, and explaining findings to others in a way that's easy to understand.
Qualifications: A degree in data analytics, computer science, mathematics, statistics, business, or a related field can be helpful, but many employers also value certifications, projects, and practical experience.
Biggest Challenges: Working with incomplete or messy data, meeting deadlines, and communicating technical results to non technical audiences.
Advice For Beginners: Start by mastering Excel and SQL, then learn python and a visualization tool like Tableau or power BI. Build a portfolio of projects using real datasets and keep practicing. Strong communication skills are just as important as technical skills.
Data analytics is a great career if you enjoy solving problems and working with data. Here are my thoughts:
Most Important Skills: Critical thinking, problem solving, attention to detail, communication, and curiosity. Technical skills like Excel, SQL, python or R, and data visualization tools(such as Tableau or power BI) are also very valuable.
Skills used every day: cleaning and organizing data, analyzing trends, creating reports or dashboards, and explaining findings to others in a way that's easy to understand.
Qualifications: A degree in data analytics, computer science, mathematics, statistics, business, or a related field can be helpful, but many employers also value certifications, projects, and practical experience.
Biggest Challenges: Working with incomplete or messy data, meeting deadlines, and communicating technical results to non technical audiences.
Advice For Beginners: Start by mastering Excel and SQL, then learn python and a visualization tool like Tableau or power BI. Build a portfolio of projects using real datasets and keep practicing. Strong communication skills are just as important as technical skills.
MAJ Markeith Johnson, BS, MBA
Data Scientist
3
Answers
Tampa, Florida
Updated
MAJ Markeith’s Answer
From my personal experience in industry, it’s brutally important to work with and learn the tools of the trade, which is where the rubber meets the road, rather than learning a specific language - since ai can write code for you. It’s far more advantageous to get free developer accounts in tools like palantir foundry, Qlik, power automate, power bi, etc. These are the ways real life business problems get addressed and you learn the requisite languages by proxy. Identify and research the tools. Select with ones you’d like to specialize in. Build your portfolio with projects using those tools, and you’re pretty much off to the races from there. But remember, this is a fast moving space. Learning and expanding your knowledge and capabilities never end. But start with understanding the tools in the field and the ones most interesting to you. Let the world unfurl from there.
Thank You so much for Your answer! It's easy to understand and very helpful :)
Jane
Lin Jia
Data Scientist
22
Answers
Amsterdam, North Holland, Netherlands
Updated
Lin’s Answer
Breaking into data analytics is less about knowing every tool under the sun and more about understanding how to use data to solve real business problems. Here is an inside look at what the role actually entails, the challenges you will face, and how to get started.
1. What skills are most important & used every day?
While technical tools get you through the door, business communication and problem translation are the skills you will use every single day.
Translating Business Problems into Analytical Questions: Stakeholders rarely ask for specific data scripts. They ask vague questions like, "Why are we losing customers?" Your job is to translate that into an analytical workflow: defining metrics, formulating hypotheses, and identifying the right data to pull.
2. What qualifications would you recommend?
You do not strictly need a computer science or statistics degree to become a data analyst. Employers care most about proof of work.
* Relevant Foundations + Targeted Learning: A degree in a quantitative field (business, engineering, sciences, economics) is great, but if you lack specific technical coursework, take deliberate online courses (via Coursera, edX, or Kaggle) in SQL, Python, and data visualization.
* Domain Knowledge: Understanding the industry you work in (e.g., healthcare, finance, retail, biology) is often more valuable than pure coding ability.
* A Public Portfolio: A GitHub repository or Tableau Public profile showcasing 2–3 end-to-end projects carries far more weight than passive certificates. Your projects should demonstrate how you identified a problem, cleaned the data, built a solution, and recommended a business action.
3. What are the biggest challenges?
* Handling Ambiguity: Business requests are often messy and unrefined. Learning how to ask the right clarifying questions to pin down true business requirements is one of the hardest parts of the job.
* Messy & Fragmented Data: In the real world, data lives in silos, has missing values, or contains errors. Cleaning data often takes 70% to 80% of project time.
* Managing Expectations: Helping non-technical stakeholders understand what is realistically possible with current data—and communicating margins of error without confusing them—requires constant effort.
4. What advice would you give someone starting out?
* Start with the End in Mind: Open job boards (like LinkedIn or Indeed) right now. Look at 15–20 Data Analyst job postings in your target location or industry. Map out the overlapping skills they ask for and build your learning plan around those exact requirements.
* Apply Analytics to Your Current Work or Hobbies: Don't just do generic online tutorials. Use data to solve a problem in your current job, undergraduate research, or personal interest.
* Build in Public & Network: Go to local data meetups, join open-source data projects on GitHub, and connect with working analysts. Reaching out directly to professionals or program directors to ask, "What skills am I missing to be competitive?" gives you a clear roadmap and sets you apart from the crowd.
1. What skills are most important & used every day?
While technical tools get you through the door, business communication and problem translation are the skills you will use every single day.
Translating Business Problems into Analytical Questions: Stakeholders rarely ask for specific data scripts. They ask vague questions like, "Why are we losing customers?" Your job is to translate that into an analytical workflow: defining metrics, formulating hypotheses, and identifying the right data to pull.
2. What qualifications would you recommend?
You do not strictly need a computer science or statistics degree to become a data analyst. Employers care most about proof of work.
* Relevant Foundations + Targeted Learning: A degree in a quantitative field (business, engineering, sciences, economics) is great, but if you lack specific technical coursework, take deliberate online courses (via Coursera, edX, or Kaggle) in SQL, Python, and data visualization.
* Domain Knowledge: Understanding the industry you work in (e.g., healthcare, finance, retail, biology) is often more valuable than pure coding ability.
* A Public Portfolio: A GitHub repository or Tableau Public profile showcasing 2–3 end-to-end projects carries far more weight than passive certificates. Your projects should demonstrate how you identified a problem, cleaned the data, built a solution, and recommended a business action.
3. What are the biggest challenges?
* Handling Ambiguity: Business requests are often messy and unrefined. Learning how to ask the right clarifying questions to pin down true business requirements is one of the hardest parts of the job.
* Messy & Fragmented Data: In the real world, data lives in silos, has missing values, or contains errors. Cleaning data often takes 70% to 80% of project time.
* Managing Expectations: Helping non-technical stakeholders understand what is realistically possible with current data—and communicating margins of error without confusing them—requires constant effort.
4. What advice would you give someone starting out?
* Start with the End in Mind: Open job boards (like LinkedIn or Indeed) right now. Look at 15–20 Data Analyst job postings in your target location or industry. Map out the overlapping skills they ask for and build your learning plan around those exact requirements.
* Apply Analytics to Your Current Work or Hobbies: Don't just do generic online tutorials. Use data to solve a problem in your current job, undergraduate research, or personal interest.
* Build in Public & Network: Go to local data meetups, join open-source data projects on GitHub, and connect with working analysts. Reaching out directly to professionals or program directors to ask, "What skills am I missing to be competitive?" gives you a clear roadmap and sets you apart from the crowd.
Felipe Sanchez
Data Science
3
Answers
Medellín, Antioquia, Colombia
Updated
Felipe’s Answer
What skills are most important? What skills you use every day? Apart from languages, I'd say it's important understanding the data. In the end, it's just numbers, but you must understand what they mean. You must be able to analyze and let the numbers talk to you.
What qualifications would you recommend? I'd start with excel, SQL and basic Python.
What are the biggest challenges? Lately, with the AI, seems difficult to find entry/junior level jobs.
What advice would you give someone starting this career? Start with online courses and personal projects to start a portfolio. It don't need to be complex at first, you'll learn with time and patience. Try not to feel overwhelmed with the requirements some companies have, but rather, find a learning roadmap with a lot of practice.
What qualifications would you recommend? I'd start with excel, SQL and basic Python.
What are the biggest challenges? Lately, with the AI, seems difficult to find entry/junior level jobs.
What advice would you give someone starting this career? Start with online courses and personal projects to start a portfolio. It don't need to be complex at first, you'll learn with time and patience. Try not to feel overwhelmed with the requirements some companies have, but rather, find a learning roadmap with a lot of practice.
Brandy Baker
Scrum Master
19
Answers
Winter Haven, Florida
Updated
Brandy’s Answer
I'd be happy to share my perspective!
What skills are most important?
The most important skills are:
Critical thinking – asking the right questions and understanding what the data is really telling you.
Communication – being able to explain results to people who aren't technical.
Problem-solving – turning business questions into data-driven answers.
Attention to detail – small mistakes in data can lead to big mistakes in conclusions.
What skills do you use every day?
Most data analysts regularly use:
SQL (querying data)
Excel or spreadsheets
Data visualization tools such as Power BI or Tableau
Communication and presentation skills
Data cleaning and validation
What qualifications would you recommend?
A degree in a field such as Data Analytics, Statistics, Mathematics, Computer Science, Business, Economics, or a related area can be helpful. However, employers also value practical experience and projects that demonstrate your skills. Learning SQL, Excel, and a visualization tool is a great place to start.
What are the biggest challenges?
One of the biggest challenges is working with messy or incomplete data. Another is translating technical findings into clear recommendations that decision-makers can understand and use. Sometimes finding the answer is the easy part; explaining it effectively is the harder part.
What advice would you give someone starting this career?
Learn the fundamentals of SQL and Excel.
Build projects using data that interests you.
Focus on storytelling, not just numbers.
Be curious and ask lots of questions.
Don't be afraid to make mistakes. Every project teaches you something new.
My biggest piece of advice: A great data analyst is not someone who knows the most tools. It's someone who can turn data into useful insights and communicate them clearly. 😊You're going to be great!
What skills are most important?
The most important skills are:
Critical thinking – asking the right questions and understanding what the data is really telling you.
Communication – being able to explain results to people who aren't technical.
Problem-solving – turning business questions into data-driven answers.
Attention to detail – small mistakes in data can lead to big mistakes in conclusions.
What skills do you use every day?
Most data analysts regularly use:
SQL (querying data)
Excel or spreadsheets
Data visualization tools such as Power BI or Tableau
Communication and presentation skills
Data cleaning and validation
What qualifications would you recommend?
A degree in a field such as Data Analytics, Statistics, Mathematics, Computer Science, Business, Economics, or a related area can be helpful. However, employers also value practical experience and projects that demonstrate your skills. Learning SQL, Excel, and a visualization tool is a great place to start.
What are the biggest challenges?
One of the biggest challenges is working with messy or incomplete data. Another is translating technical findings into clear recommendations that decision-makers can understand and use. Sometimes finding the answer is the easy part; explaining it effectively is the harder part.
What advice would you give someone starting this career?
Learn the fundamentals of SQL and Excel.
Build projects using data that interests you.
Focus on storytelling, not just numbers.
Be curious and ask lots of questions.
Don't be afraid to make mistakes. Every project teaches you something new.
My biggest piece of advice: A great data analyst is not someone who knows the most tools. It's someone who can turn data into useful insights and communicate them clearly. 😊You're going to be great!
Laura E. Lin
People Intelligence & Analytics Manager
16
Answers
Quincy, Massachusetts
Updated
Laura E.’s Answer
If you're working on building data analytics skills, equally important as the technical skills is the ability to talk about your work to different audiences. In a data analyst role you may have to present or summarize your work for different groups, from your own team - much more connected to the data space - to leaders, who may be more interested in the "big picture" conclusions. You will stand out as a data analytics professional if you can explain 1) not only what you did, but also 2) what it means - and tailor how much of 1 and 2 you share depending on who you're talking to.
Whether or not you're working with data yet, this translates to general presentation skills - practice really knowing what you're talking about, and consider what questions you might get asked ahead of time so you're prepared.
Whether or not you're working with data yet, this translates to general presentation skills - practice really knowing what you're talking about, and consider what questions you might get asked ahead of time so you're prepared.
Jose Munoz
Front Office at Financial Claims and Channel Data Management
2
Answers
Bucaramanga, Santander Department, Colombia
Updated
Jose’s Answer
Hi Jane,
From my experience, here are some key things to keep in mind as a data analyst:
Important Skills:
You'll need to know SQL, Excel, data visualization tools like Power BI or Tableau, and have strong analytical thinking and communication skills.
Recommended Qualifications:
Having a degree in analytics, statistics, business, or computer science is great, but certifications and hands-on projects are just as valuable.
Biggest Challenges:
You'll face issues with data quality, need to understand business needs, and explain insights to people who aren't tech-savvy.
Advice for Beginners:
Start by learning Excel and SQL, work on real projects, enhance your communication skills, and focus on solving business problems, not just handling data.
Hope this helps!
From my experience, here are some key things to keep in mind as a data analyst:
Important Skills:
You'll need to know SQL, Excel, data visualization tools like Power BI or Tableau, and have strong analytical thinking and communication skills.
Recommended Qualifications:
Having a degree in analytics, statistics, business, or computer science is great, but certifications and hands-on projects are just as valuable.
Biggest Challenges:
You'll face issues with data quality, need to understand business needs, and explain insights to people who aren't tech-savvy.
Advice for Beginners:
Start by learning Excel and SQL, work on real projects, enhance your communication skills, and focus on solving business problems, not just handling data.
Hope this helps!