Want to build a mobile application that runs on multiple platforms and package it with analytical features, interactive reports, and dashboards? Then this tutorial is for you.

In this blog post, you will learn how to build such an app with Ionic 5 and Flexmonster.

But before jumping straight to practice, let’s figure out which approaches we can follow when it comes to mobile development. We will also take a sneak-peek into their pros and cons.

Native vs. cross-platform development

When developing a mobile app, one way is to go with native development. You can create an app for Android or/and iOS. …


Why is enterprise reporting important?

Enterprise reporting in the business intelligence context is a process of arranging data into a format that is easy to understand by a target audience. As a rule, reports are comprised of tables, pivot tables, graphs, and text.

There are different types of reports produced with reporting software, but the most common is an analytical report.

Analytical reports assist in deriving insights from business data and transforming the insights into actions and strategies.

A general goal of enterprise reporting is to help departments or a business make decisions data-driven. …


Diving into exploratory data analysis with Python, a JavaScript library for data visualization, and Jupyter

Any data science or data analytics project can be generally described with the following steps:

  1. Acquiring a business understanding & defining the goal of a project
  2. Getting data
  3. Preprocessing and exploring data
  4. Improving data, e.g., by feature engineering
  5. Visualizing data
  6. Building a model
  7. Deploying the model
  8. Scoring its performance

This time, I would like to bring your attention to the data cleaning and exploration phase since it’s a step which value is hard to measure, but the impact it brings is difficult to overestimate. Insights gained during this stage can affect all further work.

There are multiple ways you can…


With the advent of Electron.js, it became possible to develop a cross-platform desktop application using JavaScript, HTML, and CSS — web technologies.

This tutorial aims to cover the basics of building a cross-platform app with Electron and enabling it with data visualization and reporting functionality.

The philosophy of the framework is “Write once and distribute everywhere”. Hence, your reporting app will run on all popular platforms and fit a wide audience of end-users.

If you already have an Electron.js application, jump straight to the Getting the pivot table library section.

What you will get

Upon the tutorial completion, you’ll get a desktop app running…


Visualize data in Jupyter Notebook with JS libraries

Rich interactive computing experience is what I love most about Jupyter Notebook. Besides, it’s a perfect web-based environment for performing exploratory analysis.

In this tutorial, I’d like to show how to empower the exploratory phase of your project with two interactive data visualization tools that are available as JavaScript libraries. The guide will take minimum time and steps to complete.

I believe data reporting should be comprehensible and take less time than the analysis itself. That’s why, without any extensions added, we will establish a working environment for reporting within Jupyter Notebook in the minimum time.

Hopefully, the resulting notebook…


We can speak at length about the importance of presenting data not only in a dry, text format but also in visuals. However, this article has a more pragmatic purpose. I decided to gather and consolidate in one place the brief yet useful information for developers who want to solve the task of data visualization in a mobile application. More specifically, to present a list of data visualization libraries for React Native developers. I’ve tested each library and checked them for compliance with the following criteria:

  • responsiveness
  • easiness of integration
  • interactivity
  • modern design

I do hope this guide won’t leave…


Today I’d like to show you how to create a full-stack application and empower it with a reporting functionality. As a back-end technology, we’re going to use ASP.NET Core. For the front-end part, I’ve decided to pick Vue.js — fast, easy to learn, and powerful framework. If you have previous experience with React, it won’t be a problem for you to address this framework, too.

As a result, you’ll get a lightweight app with reporting functionality. To make things beautiful, we’ll try following material design guidelines to give our app native look & feel.

We’ll implement the web API on…


Seeing reporting in Jupyter from a new angle

Jupyter Notebook is an important arrow in the data scientist’s quiver. This open-source application is flexible and, most importantly, interactive. This is a tool you need for basic data science tasks, such as data cleaning, building visualizations, creating machine learning models and a lot more. You can write here Python or R code (depending on the kernel you use), save results of code execution in the cells and share them with other people.

I can’t imagine my work without Jupyter Notebooks. They are shareable, fast to set up, and simple to use…


What is Vue

Vue.js is a front-end framework that goes side by side with such major frameworks as React and Angular when it comes to choosing the framework for building the client side for modern applications.

It’s best described as approachable and progressive since it offers incrementally adaptable pieces like a routing solution, a state management solution, a build toolchain, and the CLI.

The term ‘progressive framework’ was coined by its creator, and now it’s widely used when mentioning Vue.

Popularity of Vue

After being released and posted on Hacker News in 2014, its popularity literally skyrocketed.

On the graph in the State of JavaScript 2019…


Data visualization is both a science and an art. If you work with data, one of the greatest challenges you may encounter is picking the right way to shape and present your data in a readable form. A proper visualization flawlessly delivers the meaning of the conducted data analysis.

Since there’s a countless diversity of data visualization tools in the market, no wonder that it may take a lot of time before you find a perfect one.

To save your time for accomplishing more sophisticated tasks, I’m going to present to you my top of JavaScript libraries that greatly simplify…

Veronika Rovnik

Passionate about mathematics, machine learning, and technologies. Studying approaches in the field of data analysis and visualization. Open for new ideas :)

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