Power BI vs i2 Analyst's Notebook

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.

User reviews suggest that i2 Analyst's Notebook is a powerful tool for analyzing complex data, but it's not without its flaws. Users praise its ability to visualize data and identify patterns, which is crucial for understanding complex investigations. For example, one user highlighted how the software helped them uncover connections between seemingly unrelated events, leading to a successful prosecution. However, some users complain about the software's steep learning curve and clunky interface, which can be frustrating for new users. One user likened the experience to trying to navigate a maze with a blindfold on. Despite these drawbacks, i2 Analyst's Notebook remains a popular choice for law enforcement and intelligence agencies due to its robust features and ability to handle large datasets. The software's strength lies in its ability to connect the dots, making it ideal for investigations involving complex networks of individuals and organizations. For example, it can be used to track the movement of money, identify potential threats, and analyze social media data. However, the software's complexity can be a barrier for users who are not familiar with data analysis techniques. It's not a tool for casual users; it requires a dedicated team of analysts with the skills and training to use it effectively. Overall, i2 Analyst's Notebook is a powerful tool for organizations that need to analyze large amounts of data and identify patterns. However, it's not for everyone. If you're looking for a user-friendly tool with a gentle learning curve, this might not be the right choice. But if you're serious about uncovering hidden connections and gaining actionable insights, i2 Analyst's Notebook is worth considering.