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Based on our record, Microsoft Power BI should be more popular than Raygun. It has been mentiond 17 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Raygun is a cloud-based platform that makes sure your web and mobile applications are free of errors, as well as your users are satisfied. It specializes in JavaScript error monitoring and offers a wide range of features to help you easily detect and fix issues. - Source: dev.to / 6 months ago
We can make the process a little easier by using our agile processes together with a continuous deployment strategy. For example, our friends at Raygun, discovered that “when a team gets locked into a sprint it can become much harder to recognize and fix bugs”. - Source: dev.to / 10 months ago
Regarding your last question, when I mention sub-processors who we don't have an SCC with I'm thinking about vendors like RayGun. It's a system we use to monitor alerts and warnings coming from our app when in the hands of our end-users. We have configured the tool so we get absolutely no personal information - no names, emails, id's or any of that sort. It's nothing more than technical data dumps from the inner... Source: over 1 year ago
Error logging and monitoring are crucial for any application, Appwrite being no exception. We wanted to make it extremely easy to collect and monitor your logs while staying true to our philosophy of being completely platform agnostic. With Appwrite 0.12, we've introduced support for some amazing open source logging providers like Sentry, Raygun and AppSignal! - Source: dev.to / over 2 years ago
We have RayGun for logging/reporting on the client-side of the apps. They are showing nothing interesting from those devices. They seem to fail silently. Source: about 3 years ago
Microsoft Fabric is currently in preview and provides data integration, engineering, data warehousing, data science, real-time analytics, applied observability, and business intelligence under a single architecture by integrating services such as Azure Data Factory, Azure Synapse Analytics, Data Activator, and Power BI. In addition, it comes with a SaaS, multi-cloud data lake called "OneLake" that is built-in and... Source: about 1 year ago
I'd suggest spending some time learning the material before you invest thousands in tuition only to find that you don't like it or aren't good at it. Download Tableau Public or Power BI and force yourself to use them for a few months. That's how I taught myself R. Source: about 1 year ago
Discover why business analytics is crucial for your business and how to utilise data analytics and PowerBI to make informed and data-backed decisions! Source: about 1 year ago
Power BI is popular... But for table reports with Excel/PDF export you can use Pebble Reports. Source: over 1 year ago
Yes, MySQL can do the job. You can use Airforms to do data entry. No need to learn MySQL syntax. You will also need a reporting tool, such as Power BI. Source: over 1 year ago
Sentry.io - From error tracking to performance monitoring, developers can see what actually matters, solve quicker, and learn continuously about their applications - from the frontend to the backend.
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
Rollbar - Rollbar collects errors that happen in your application, notifies you, and analyzes them so you can debug and fix them. Ruby, Python, PHP, Node.js, JavaScript, and Flash libraries available.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.
Sisense - The BI & Dashboard Software to handle multiple, large data sets.