As always, another month means another great update of Power BI from the Microsoft team. The new updates are full of cool features ranging from report features, visual updates, to modeling changes. Some are simpler, while others are a big change in the Power BI universe. In this blog post, I will take an in-depth look at some of the updates this month while also referencing other updates. NOTE: It may be helpful to have had some exposure to Power BI before continuing to read this.
Recently a client came to us to see if we could help them automate their RFP distribution system. Currently the client has an employee manually check several websites for RFPs and alert the appropriate business vertical when a relevant RFP is found. The current system requires manual data scraping, meaning the process is slow and results in RFPs being missed. For the proof of concept phase with the client, we decided to build a machine learning model to classify the RFPs correctly and provide a way to automate the routing of the RFPs. The client wanted to break the project into stages so once the initial Proof of Concept was successful, other parts required to automate the whole process would receive the go-ahead. If you would like a proof of concept, visit our Business Analytics page for information.
What is Common Data Service?
Common Data Service is a cloud-based data storage and management system that standardizes your data across business applications like Dynamics 365, Office 365, mobile apps, and Power BI.
Your data is stored in standard (or customized) entities, similar to how a table stores data in database. If you use Common Data Service, your suite of business applications feed data predictably to these entities, allowing simple data sharing, data mining, and business intelligence.
This dashboard probably looks very familiar to you. You might have five or six dashboards you’re watching for ebbs and flows, spikes and surges. Maybe you have a very advanced process that involves downloading data into Excel and mashing different channels together. But that doesn’t sound very advanced, does it? Manual data entry? Staring at four online dashboards, commenting on "this one is up, or this is down"? There’s nothing advanced here. It doesn’t tell you how people responded, how their interactions lead to anything. Do you let your marketing data impact future creative decisions? If it's not producing marketing intelligence, your marketing data is completely useless.
"Last night, we had a happy hour to celebrate burning Joe's Excel spreadsheet."
Those were the exact words out of the mouth of the Director of Marketing at a global med-tech company based in Minneapolis. Just a few months earlier, Beyond Impact helped deploy a Marketing Intelligence Solution leveraging Power BI to migrate an Excel spreadsheet that essentially ran the entire Retail Marketing division. This Excel spreadsheet was held together with duct-tape and elbow grease, leading the client to say, "there has to be a better way to work with our marketing reports."
Growing up in a small town near Lake Mille Lacs, a good 90-minutes north of the Twin Cities, much of my learning as a little boy happened in a sandbox. Not the giant plastic turtle you see in Walmart today. Rather, an oversized wood structure filled with sand and a collection of old metal Tonka Trucks. I would spend the summer days building roads, bridges, castles, and rivers. I engineered high-security prisons for frogs I caught. I threw sand at my older brother and occasionally we tangled with a garden hose, much to my mother's displeasure. Every night I'd come in for dinner covered head to toe in dirt. Little did I realize, I spent those long summer days learning physics and engineering in the sandbox. I've always learned by just digging in. My childhood story really has nothing to do with Power BI - it simply points out the fact we can learn so much more when we get our hands dirty.
We have all heard that sage advice since as far back as we can remember, "all that glitters is not gold." This rings true in data visualizations in Power BI. As part of our ongoing Power BI blogs, we are here to help you transform your business data into an engine that drives insights. Check out our full Resource Library for more.
The purpose of data visualization is to simplify, messy, and overwhelming data to solve a business problem. Enable decision makers to make insightful, data-driven decisions. To understand what great data visualization is, a good place to start is find out what it is not.
Up here in the North Country the chill of the fall weather is just starting to set in. Over the next few months we'll hit some bone chilling temperatures and dig out the long-underwear. Nothing warms the heart and soul like a hearty bowl of soup, especially one perfected through the years with a bit of Grandma's love. If Grandma has taught us anything, it's that when you serve her soup you don't use a teaspoon - you use the ladle.
My wife rolls her eyes every time I pull out Microsoft’s Power BI to analyze our personal bank statement data. Perhaps she doesn’t want me to know how much she spends each month on Starbucks Grande Chai Lattes… no whip. The reality is, I utilize Power BI whenever possible. In fact, these days I find it hard to engage in a business intelligence strategy discussion without Power BI being part of the conversation.
We have all heard that sage advice since as far back as we can remember, "all that glitters is not gold." And when it comes to data visualization, truer words were never spoken.
The purpose of data visualization is to simplify messy overwhelming data and solve a business problem; enabling decision makers to make insightful data driven decisions.
To understand what great data visualization is, we must consider both what it is and what it is not.