Power BI vs Domo Everywhere

Our researchers ranked products on a whole bunch of features. They include data management, querying and visualization, advanced and embedded analytics, mobile BI, and IoT and location analytics.In our rankings, Power BI scores 87 for connectivity, leaving behind Tableau, Oracle Analytics and Dundas BI. Robust Microsoft technology is one reason, for sure. Besides, intelligent techniques like DirectQuery and easy data modeling make it popular among users.In product reviews, some users mentioned a lag when sharing reports from the desktop to the cloud. For me, the platform was a tad slow to start, but otherwise, it stayed performant for my average-sized dataset.When dealing with sales data, total sales, the top-performing products, seasonality and period trends are common queries. Creating a sales KPI report in Power BI was an excellent way for me to answer them. My CSV files included sales, calendar, products and store data.Connecting to sources is straightforward with Get Data on the home screen and toolbar. Once I had pulled in the data, I clicked on Transform Data and opened the Power Query editor. It automatically detects the data type for strings and numbers but can get confused with dates and currency, which it marks as text. It involved some manual wrangling, but I had it sorted in no time. Read my article on KPI Reports to learn how I did it.But I wouldn’t call it a deal-breaker as it’s not a tedious task. I had the same experience with Qlik Sense, but Tableau was way better as it recognizes seven data types — string, number, date, date and time, boolean, geographic and cluster values.Tracking sales over periods required a greater level of detail, so I added new columns to the calendar data — start of month and start of week. Column statistics were immensely helpful in identifying unique, distinct and null values and correcting incomplete records. Clicking on the number of products selling at a particular price allowed me to see which toys sold at that price.Creating a relational data model by defining primary keys is a manual process and seems dated once you’ve used Qlik Sense. Adding calculated measures is where DAX shows its magic. For data workers well-versed with SQL, DAX is a ready-to-go tool they’ll be glad to have in their corner.Creating visualizations wasn’t as intuitive as Tableau as it involved drag-and-drop onto the canvas, and frankly, I felt like I was flying blind. I didn’t feel that way with Tableau, and it’s slicker.Power BI offers a paintbrush tool that lets you define the layout, the card arrangement and the maximum number of cards. You can define the canvas settings, background and headers and determine the filter pane settings. It took me longer to create a dashboard from scratch than it took in Tableau.Some users found the pricing structure too complex. While using Azure data in Power BI for basic queries is free, costs can add up when you go for text and sentiment analysis. With Microsoft Fabric, the pricing complexity is set to rise. Though Power BI is available separately too, you’ll need to rely on Fabric to manage users, licenses and other administrative tasks.About 31% of the users mentioning cost complained about onboarding difficulties, possibly because DAX introduces the complexity of learning syntax. It can daunt non-technical users initially, but guided formulas can make the task easier. That said, I agree with the majority of user reviews that training will speed up onboarding and help your team maximize the investment.Overall, Power BI has many powerful features and will give you value for your money. If you’re not a Microsoft user yet, it’s worth checking out for the baked-in vendor technologies like Azure and SSAS. If you are an MS user, Power BI might be a no-brainer, though be prepared to shell out a little extra for advanced functionality and additional modules.

For users with typical embedded analytics needs, Domo Everywhere presents a mixed bag. Fans rave about its ease of use and visual storytelling tools, enabling anyone to explore data without coding - "Like having a personal data chef," gushed one reviewer. Its ability to unify data from various sources is another major pull, breaking down silos and offering "a single source of truth" for complex operations. However, Domo isn't without its detractors. Some find the learning curve for advanced features like custom visualizations "steeper than a Matterhorn climb," requiring technical expertise beyond basic analysis. Concerns also linger about its offline capabilities, with internet connectivity still crucial for most functionalities - "a deal-breaker for field teams," noted another user. While pricing starts reasonably, advanced features and high data volumes can quickly inflate costs, making some feel Domo becomes "pricey for its complexity" compared to alternatives like Looker or Tableau. Ultimately, Domo Everywhere shines for its intuitiveness and data unification, empowering non-technical users with valuable insights. However, its limitations in offline access, advanced features, and potential cost escalation leave some users yearning for a more well-rounded package. As one reviewer put it, "Domo is like a Ferrari: powerful and flashy, but not everyone needs a race car for their daily commute." So, if your embedded analytics needs prioritize accessibility and a holistic view, Domo could be your champion. But for those needing robust offline functionality, advanced customization, or a more budget-friendly option, exploring other contenders might be the wiser route.