Who's ready to talk about Power BI and Advanced DAX functions?
I know I am!
Today, we're going to learn about using the CROSSFILTER function.
For folks who have completed our Power BI Desktop and Power BI Service courses and have been looking to go deeper, this video from our new Advanced DAX course should be right up your alley. If you're brand new to Power BI, this might be a little over your head.
Before you jump into this Advanced DAX video, let me tell you how I use CROSSFILTER...
Personally, I love CROSSFILTER because it is a great way to get around having to define bi-directional relationships in your data model. Instead, when we use CROSSFILTER, we can define the nature of the relationships directly within a given measure. This makes things a lot more flexible.
I could keep talking about CROSSFILTER all day, but I think the best way to teach you about this is to point you to the video below. Check it out!
This video is from our new Advanced DAX course, which we're aiming to get live by Thursday or Friday this week.
We've put a lot of work into this course, and I'm so happy with how it turned out.
If you want to be among the first to hear about the new course launch, make sure to follow Maven on LinkedIn, where we'll be announcing the release later this week.
Learn on!
-Aaron
Up to 50% Off Maven Pro Plans!
FLASH SALE
Take advantage of this limited-time offer and save up to 50% off unlimited Maven access!
Aaron Parry
Partner & CCO
Aaron is a professional analytics consultant and Microsoft Power BI expert, with 10+ years working in business intelligence and marketing analytics. He's an instructor, coach and mentor for aspiring analysts, and has deep experience helping companies develop and implement full-stack BI solutions.
Frequently Asked Questions
What is Maven Analytics?
Maven Analytics is an online learning platform that helps professionals and organizations build practical data and AI skills in analytics, business intelligence, and data science. Our hands-on courses are designed to help learners stay competitive and future-proof their careers in the age of AI.
Are data analysis and data science still good career paths?
Absolutely. As long as companies collect and use data, they need people who know how to turn that data into results. Roles are changing, and so are the skills needed to succeed, but the career paths remain strong. Focus on data literacy fundamentals, business thinking, communication skills, and learning how to use modern data and AI tools, and you can build a strong career.
Will AI replace data jobs?
AI is changing how data professionals work, but it is not replacing the need for skilled analysts and data scientists. Instead, AI is becoming another tool in the data workflow. Organizations still need people who can ask the right questions, interpret results, communicate insights, and apply data to real business decisions. The most successful professionals will be those who learn how to combine core data skills with modern AI tools.
How can I future-proof my career in analytics?
Future-proofing your analytics career means building strong core data skills, understanding business context, and learning how to work effectively with AI rather than compete with it. The goal is to become a better analyst, problem solver, and decision-maker.
How long does it take to build job-ready data skills?
That depends on your starting point and goals, but many learners can build meaningful skills over a few months with consistent practice, even when studying part-time. The most important factor is applying what you learn through hands-on projects and real business problems.
