Entry Level Careers

Hi mariagonzalez14 ,

Thanks for reaching out in Microsoft Fabric Community and congratulations on completing your degree.

For entry level roles in Data Analyst or Data Scientist tracks, focusing on hands on experience will help you stand out. If you are exploring the Microsoft ecosystem, getting familiar with Microsoft Fabric and Power BI is a good starting point. Try building a few end to end projects covering data ingestion, transformation, and reporting.

You can refer to the official Microsoft learning paths here:
Training for Power BI | Microsoft Learn
Microsoft Fabric documentation - Microsoft Fabric | Microsoft Learn

For Data Science specifically, you can also look into Azure Machine Learning and related learning paths:
Quickstart: Get started with Azure Machine Learning - Azure Machine Learning | Microsoft Learn

Relevant certifications:
Microsoft Certified: Azure Data Scientist Associate - Certifications | Microsoft LearnMicrosoft Certified: Power BI Data Analyst Associate - Certifications | Microsoft Learn

Building a small portfolio with real world datasets, including basic machine learning use cases, will also strengthen your profile.

Since this forum is focused on queries related to Microsoft Fabric and Power BI, if you have anything specific within these areas, feel free to reach out here.

Regards,
Community Support Team

hey mariagonzalez14  congratulations on your graduation!
There are a lot of advices / suggestions I can give you, but as someone in the industry for 10+ years I would only recommend one thing:

=> Build a portfolio of projects.

I mean you just build 2–5 real projects and publish them (GitHub or else), you can get help from ChatGPT or Gemini to ideate any business use cases, generate synthetic data and getting started.
For Examples:

1. Data cleaning + visualization (sales, finance, healthcare, etc.)
2. Predictive model (classification, regression)
3. Dashboard (Power BI Free)

This way when you are interviewing for a role in the company, you have something "real" to show and (most likely) impress the interviewers.

Companies don’t expect you to know everything, but they want to see that your willingness to learn, think logically, and build a solution to real problems.

Appreciate if you can 'Kudos' and/or 'Accept as Solution' if this answered your query.

Congratulations on your graduation!

For aspiring Data Scientists or Data Analysts, I would recommend focusing on three key areas:

1. Technical Skills – Strengthen your Python, SQL, statistics, machine learning, data visualization (Power BI/Tableau), and data analysis skills.

2. Projects & Portfolio – Build real-world projects and showcase them on GitHub. A strong portfolio often helps recruiters assess your practical skills.

3. Networking & Certifications – Engage with data communities, attend webinars, connect with professionals on LinkedIn, and pursue relevant certifications from Microsoft, Google, or other recognized providers.

For job opportunities, consider applying for entry-level Data Analyst, Business Analyst, Junior Data Scientist, or Data Science Intern roles. Tailoring your resume to each job description and highlighting measurable project outcomes can significantly improve your chances.

Best of luck with your job search!