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Machine Learning for Analysts: The Basics

Headshot of article author The Power BI Team

Machine learning is a hot trend in the tech and business press – you’ve probably heard about it, and you may be starting to explore it, or perhaps are already using it. OR you might have zero idea what to do with it, in which case, read on for some basics to get you started!

So first of all, what is machine learning?  Simply put, machine learning is the practice of mining your historical data with computer systems to predict future activity – trends, behaviors, patterns, etc. From a benefits perspective, this predictive knowledge is huge. If you know where things are going, you can adapt your business and stay ahead.

Historically, machine learning was an expensive endeavor requiring complex software, as well as deep expertise from data scientists. While many wanted to take advantage of machine learning, it was often too hard, time consuming, and costly to implement and operationalize.

Enter the cloud.

By putting machine learning capabilities in the cloud, we can eliminate many of these barriers and make these capabilities accessible to many more people.

So why should you care? If you’re a business analyst of any kind – financial, marketing, IT, operations, or any other department that’s using data (so, basically all of them) – you can benefit from all that machine learning has to offer.

Try it for free – no time limits, subscriptions, or credit cards needed – on www.azure.com/ml. To help you get started, there are several pre-baked sample models that can help you explore some common business scenarios for machine learning:

Check it out, and let us know what you think.

If you’re interested in stepping through more detailed machine learning tutorials, explore these videos:

If you’re already exploring machine learning and perhaps know a bit of R, there’s a free webinar happening on Friday Nov. 14 at 9:30am PDT that might be of interest to you: Operationalizing R as a Web Service. Register now!