New Gartner Magic Quadrant: Alteryx Weak in Reporting, Dashboards, and Mobile

Alteryx Definitely. SPSS is an old product et very outdated as compared to the new tools such as Alteryx or Knime.

Alteryx is much easier to install, learn, build with R and Python capabilities... Plus can handle big data... SPSS is legacy.

I have found that it is often difficult to make business decisions that accurately consider the various streams of data that my business produces. It can be hard for me to sift through the data and interpret it meaningfully. Furthermore, even if I can interpret the data, manipulating it effectively can prove to be a challenge. These challenges are the reason why Alteryx is the predictive analysis and data preparation tool that I recommend for business owners. One of the things that I initially noticed about Alteryx was just how much flexibility it offers. It gives us the ability to accomplish a myriad of different tasks with a single solution. Among the different types of tasks that Alteryx enables us to complete are the following: Creating and updating spreadsheets. Alteryx removes our need to rely on products like Microsoft Excel. We are able to transform our data into a spreadsheet within Alteryx’s confines. Vast quantities of data are now easily manipulated and transformed into a format that we can easily use and maintain. Database integration and SQL replacement. In the past, we often needed to rely on a multitude of different solutions if we wanted to draw data from multiple databases and then perform operations using that data. When we switched to Alteryx, all of that changed. Alteryx gave us the ability to integrate our systems with a multitude of different databases. We were then able to take data from multiple databases at the same time or even focus our attention on a particular portion of a given database. Additionally, we have the ability to perform many of the operations that are possible with SQL without having to employ it. Read and write data in various locations. We are not limited by the location where we have to work. Alteryx makes it easy for us to handle data that is housed or meant to be housed in a variety of environments. Data stored in the cloud or a hybrid environment are equally easy for us to read or write. We are also able to handle a variety of formatting types. Report and dashboard creation. Alteryx gives us access to built-in tools that make it easy for us to create reports. These reports allow us to lay out our data in a clear way. Instead of worrying about finding a way to transform our data into actionable reports, we only need to focus on generating the report that we need at the time. Furthermore, we can build custom dashboards that ensure that we are always equipped to address the tasks that confront us at any given time. A major benefit that Alteryx offers us is the ability to leverage machine learning to analyze, profile, and gain insights from our data. Alteryx learns from the data that we feed into our system. This makes it possible for us to mine the data for patterns and other significant insights that we might otherwise miss. Our ability to gain insights is infinitely improved by Alteryx. Ultimately, Alteryx is a solution that provides its users with the ability to seize control of their system’s data and use it to consistently make the best business decisions possible.

Choosing Alteryx is not an easy decision. I have been using it for the last 3 years and the answer, as usual - it depends :) By your situation: 1. As a quick and flexible analysis tool capable of grabbing source data from various different sources and money is not an issue, the answer is Yes. 2. If money is tight - choose KNIME instead (free), but be prepared to tinker at the start with setting up drivers for some tricky data connections, like SAP Hana etc.  3. For any production/repeatable applications, the answer is No. Alteryx may be quite buggy in some functionality like containers, macros and complex workflows in general. Main Alteryx advantages from my experience: 1. Various source formats & connection protocols are built-in 2. Graphical "almost no coding" interface 3. Fast logic development and debugging (from seeing all scenarios of how your source data flows through, e.g. what rows do not join, etc.) and Disadvantages: 1. High cost, while some features like predictive modelling not being included in base license 2. Unstable buggy app, e.g. when working with containers or opening complex workflows. Some tools are also very sensitive to loosing their configuration from just checking them out 3. The whole architecture around Macros is not very intuitive 4. Very dubious implementation of certain functions like waiting for something or forcing a particular order of processing