Alteryx vs Microsoft BI (MSBI)

• Alteryx does a great job of allowing more beginner Analysts to automate many of their routine process but also allowing advanced Analysts to ability to leverage deep statistical modelling for predictive analytics.
• Given the visual workflow nature of Alteyrx, the learning curve is not steep.
• The Alteryx Gallery allows non-technical consumers to execute complex workflows by leveraging an intuitive web interface.
• Alteryx allows data scientists to bring their own programming language to Altyerx, such as R or Python.

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• The layout of Power BI is very intuitive. Someone that is familiar with Excel and working with Charts and Graphs in that environment will find the learning curve a rather short one to start using Power BI.
• I like the way Power BI fits an assortment of users and how the functionality that you engage is replicated in Excel, that being Power Query and Power Pivot. So what you learn in one tool can be readily applied towards the other which allows you to more effectively apply your training.
• I appreciate how Microsoft is working to develop tools that go a long ways to empowering the end user. Prior to Power BI I would have had to consult with a "BI" professional to develop a dashboard. With Power BI I don't have to consult with anyone, I can work to put together the dash board I want and using a tool set that is really robust and allows me to engage an enormous amount of data. It's provides a great deal of flexibility and the types of data I can connect to.
• Updates...Microsoft is working diligently to keep Power BI current with monthly updates. They do a really good job of listening to the end user, if there is functionality not currently present just give them a month or so.
• Just to be clear, even though it's easy to get going right out of the gate with Power BI it provides plenty of opportunities to create some really sophisticated reporting solutions. With DAX in Power Pivot and M language in Power Query, you are provided with plenty of head room to do some really amazing things in Power BI.
• Training...there are resources across the web for learning and growing your skills and Power BI. And what's even better is the majority of those resources are free.
• Data engagement, when presenting the data to the end user Power BI goes a long way to allowing that end user to engage the data and begin to identify root cause by simply interacting with the graph/chart/data set. It allows for really fluid engagement. Prior to Power BI so many times during the presentation of data we often times ended the engagement with that data with more questions than what were answered. With Power BI, more often than not, the end user is able to get answers to the questions by simply clicking on the data in the graph/chart/dataset to see the details. This tool really does have the capacity to make you look like a rock star.

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• Sometimes the desktop version of authoring tool crashes! It's been unstable in the previous versions but gets better. Even if it doesn't crash, it used to be slow or not responding.
• When running several version of database drivers in local machine or server, it is tricky to set up database connections. Often you have to figure out it by googling the problem and solution. There are not many knowledge bases from Alteryx.
• Alteryx project file creates .bak file automatically. It is useful to prevent for the purpose of back up, sometimes it's not necessary. But it is not changeable for some reason. By default, it always creates backups.

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• The race to perfect gathering of Non-Traditional datasets is on-going; with Microsoft arguably not the leader of the pack in this category.
• Licensing options for PowerBI visualizations may be a factor. I.e. if you need to implement B2C PowerBI visualizations, the cost is considerably high especially for startups.
• Some clients are still resistant putting their data on the cloud, which restricts lots of functionality to Power BI.

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• Alteryx does an excellent job of integrating consumer and spatial data to calculate and visualize things like locations within a certain drive-time radius.
• For visualization purposes I had to move the data to excel for some decent graphs.
• It can become very expensive.

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• As a SaaS provider we see being able to provide self-service BI to our client users as a competitive advantage. In fact the MSSQL enabled BI is a contributing factor to many winning RFPs we have done for prospective client organisations.
• However MSSQL BI requires extensive knowledge and skills to design and develop data warehouses & data models as a foundation to support business analysts and users to interrogate data effectively and efficiently. Often times we find having strong in-house MSSQL expertise is a bless.

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