Back in Flexmonster 2.9, we often recommended using Flexmonster Data Server (FDS) when dealing with datasets that got over the 1GB mark. It was optional, but necessary for those who want better performance in certain cases.
With Flexmonster 3.0, this changes.
This release is the result of a long process of questioning our own assumptions, facing technical limitations head-on, and rewriting the core of Flexmonster from the ground up.
This blog post is the first in a series of articles in which we’ll tell you more about each of this release’s features. We’d like to share why we decided to rebuild everything, what changed under the hood, and what you can expect from the new version.
Working on Flexmonster has been our team’s passion for years. The component has proven to be a powerful tool with a wide range of data visualization and analysis features. Our team has constantly looked for customers’ feedback and used it to evolve the component further.
Over time, we accumulated numerous ideas on making a qualitative leap to take reporting to a whole new level. Powered by insights and experience, three years ago, we began rewriting everything from scratch to create Flexmonster 3.0.
The question of “Which framework is better: React, Angular, Vue?” has sparked countless debates. This trio has become the pillars of frontend development, each with its own community and use cases. You’ll see this question debated endlessly on Reddit, Quora, and tech forums, yet the answer always seems elusive.
The variety of data sources for Flexmonster makes it easier to find the perfect option for your project. At the same time, choosing the right data source is very important and can influence your experience with Flexmonster. So this article is here to help you make the right choice.
One of the big advantages of our component is its flexibility in ways you can tune it to your needs. When you first build Flexmonster into your app, it uses predefined options to look and work a certain way. But when you need more customization, create reports that truly fit your needs, you can change these options.
Raw data can often feel like a maze—difficult to navigate and even harder to analyze to get useful information. That's where interactive dashboard come in. They turn all that complicated data into simple visuals that are easy to look at and explore, making it much quicker to notice some trends and patterns.
In this tutorial, we’ll guide you through creating an interactive map dashboard using Flexmonster Pivot Table and amCharts.
Our Tech team is always looking for ways to help you get the most out of our pivot table. If you found our previous article on managing date types useful, you'll want to keep reading.
Today, we're focusing on two key features that make analyzing your data easier—grand totals and subtotals.
Flexmonster's Pivot Table is designed to empower users to analyze vast datasets with ease. One key feature is its robust filtering functionality. By understanding its configurations, you can ensure your reports focus on the most relevant information.
Let's embark on a data exploration journey using everyone's favorite fictional creatures – Pokemon!
We continue to share tips from our Tech team, and in this article, we will discuss more about managing data types in your reports. Dates are essential to any dataset. How you manage, and present date information can significantly impact the insights you derive and prevent mistakes and misunderstandings in data analysis.
Our Tech team continues to share valuable tips on how to get our component to full power and uses all means for that. On our YouTube channel, we have a separate Tips&Tricks playlist.
These videos are designed to provide practical insights and advanced techniques that empower you with the knowledge to tackle complex data challenges and make informed decisions easily.
Here is the list of ✨ 5 main videos from the Tips & Tricks series✨ we think every Flexmonster user should know about!
Our tech team is dedicated to providing you with practical tips to make your experience Flexmonster Pivot Table more efficient. If you enjoyed our previous article on creating a custom theme for your report you’re in for a treat. Today, we’ll take customization a step further by demonstrating how to change chart colors directly from the user interface (UI) and apply those changes to all chart types.
