Power BI vs Oracle Business Intelligence

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.

Oracle Business Intelligence (OBI) garners mixed reviews from users. Many praise its robust functionality and ability to handle large datasets, with one user noting, "OBI can handle almost anything I throw at it." Another highlights its insightful dashboards and reporting capabilities, stating, "OBI provides the perfect blend of data visualization and analysis tools." However, some users criticize OBI's steep learning curve and complex interface. One user lamented, "It took me months to feel comfortable using OBI effectively." Others point to its integration limitations, especially with non-Oracle products, with one user stating, "OBI shines within the Oracle ecosystem but struggles with others." When compared to competitors like Microsoft Power BI and Tableau, users often cite OBI's scalability and data-handling prowess as its main differentiators. One user highlighted, "OBI is the go-to solution for large-scale enterprise data analysis, leaving Power BI and Tableau behind when dealing with massive datasets." Additionally, users appreciate OBI's tight integration with other Oracle products, creating a seamless workflow within the Oracle ecosystem. However, users also acknowledge OBI's shortcomings in terms of user-friendliness and flexibility. One user stated, "Power BI and Tableau offer a more intuitive and user-friendly experience, making them more accessible to a broader range of users." Additionally, some users find OBI's reliance on Oracle technologies limiting, preferring the broader platform compatibility offered by competitors. Ultimately, the choice between OBI and its competitors depends on specific needs. For organizations requiring in-depth analysis and scalability, OBI remains a powerful contender. However, those prioritizing user-friendliness and integration flexibility may find alternatives like Power BI and Tableau more attractive.