Most of you probably know about the automated machine learning (ML) functionality in the Power BI Service. This provides a no-code mechanism for preparing, training, and applying machine learning models to your data analysis in Power BI, but is only available in Power BI Premium at this time.
We all know life can get hectic. Here at Pragmatic Works, we’re no different. But one of our goals is to learn something new about Azure every day, as things are constantly changing and being updated. Many people are still learning all the amazing things they can do within the Azure cloud and we want to help. Our posts in our Azure Every Day series are a great way to learn more about Azure each week.
If you’re like many of our customers, you’re looking to learn more about advanced analytics, machine learning and other data science type topics. In today’s post, I’d like to discuss what we do to help our customers get to where they want to be in these areas.
One of the challenges with Power BI is that there are so many ways it can be used and so many nuances that the platform may seem overwhelming to some. In this post, I’d like to share some mainstream, as well as specialized use cases.
In some past blogs I’ve discussed Azure Data Box and how the Data Box family has expanded. Today I’ll talk about Azure Data Box Edge (in preview) and elaborate on the machine learning service that it provides in your premises with the power of Azure behind it.
Welcome back to Azure Every Day! We took a break in January to regroup, refresh and get some new writers involved in our Azure Every Day series. We’re back with more great content every weekday all about Azure, with tips, up to date info, use cases and more.
This first post is about retirement planning – an interesting topic these days. At this point, the state of financial planning is a potential major crisis with current and future generations coming upon retirement age with little or no savings to account for.
Pragmatic Works is considered to be experts in the Microsoft Data Platform, both on-premises and in Azure. That being said, we often get asked many questions like, how can a certain technology benefit my company?
Your sales team is the backbone of your business. Today I’d like to talk about using analytics to build a more effective sales team. This is a big topic for many of our customers and I’ll give you some insight into how we’ve been helping customers to use analytics to make their sales teams go from good to great.
Are you in the process of or looking to implement data science projects in your organization? If you’re just starting out, today I’d like to give you the 3 key factors to make any data science project successful.