This month, Panoply is running an Instagram Data Challenge! The gist is, you can pull your own Instagram data into a Panoply database with a few clicks, make a visualization or tell a data story with the data about your own posts, and enter to win one of several $1000 awards.

To kick off the challenge, I did a bit of exploration…

For most businesses, machine learning seems close to rocket science, appearing expensive and talent demanding. And, if you’re aiming at building another Netflix recommendation system, it really is. But the trend of making everything-as-a-service has affected this sophisticated sphere, too. You can jump-start an ML initiative without much investment, which would be the right move if you are new to data science and just want to grab the low hanging fruit.

One of ML's…

The insurance industry – one of the least digitalized – is not surprisingly one of the most ineffective segments of the financial services industry. Internal business processes are often duplicated, bureaucratized, and time-consuming. As the ubiquity of machine learning and artificial intelligence systems increases, they have the potential to automate operations in insurance companies thereby cutting costs and increasing productivity. However, organizations have plenty of reasons to resist…

The best trained soldiers can’t fulfill their mission empty-handed. Data scientists have their own weapons — machine learning (ML) software. There is already a cornucopia of articles listing reliable machine learning tools with in-depth descriptions of their functionality. Our goal, however, was to get the feedback of industry experts.

And that’s why we interviewed data science practitioners — gurus, really —regarding the useful tools they…

Appropriate data, audience understanding & building a good story for meaningful & powerful visual dashboards that influence & engage the audience for actionable insights; is the key. Here is an infographic is about storytelling with visualization:

Data Analytics remains incomplete without data visualization.

In a Data Analytics course, I understood how Tableau was a useful tool so as to create and explain a visual story that heavily relied on big data. As a student, I was given x-cases which required data retrieval, cleaning, manipulation, and analysis so as to make appropriate recommendations.

To start with, I have a double major in finance and international…

Introduction to OEMs

The increasing complexity of smart products, more demanding users, and stiff competition are driving the focus of electronics OEMs (original equipment manufacturers) on product quality and productivity. These companies are struggling to improve their operations to increase their production yield, operational efficiency, and product quality. This has been driving demand for  Data Visualization & Analytics solutions over the past few years and as part of their…

Dashboards for data visualization, such as Tableau or R Shiny, enable an interactive exploration of data in the form of plots or tables, through a programming-free interface with drop-down lists and checkboxes. The apps can be useful for both the data analyst and the public.

Visualization apps may be privately consulted as well as published online. There are two main platforms: R Shiny and Tableau. Shiny has a free starter license…

This is a tutorial to show how to implement dashboards in R, using the new "flexdashboard" library package.

this new library leverages these libraries and allows us to create some stunning dashboards, using interactive graphs and text. What I loved the most, was the “storyboard” feature that allows me to present content in Tableau-style frames. Please note that for this you need to create RMarkdown (.Rmd) files and insert the code using the…

Can data bring the best in humanity? Can it evoke emotions? Can it speak to us?

Every time I walk by a memorial wall, I am filled with visuals. Some folks run their fingers on the wall and when they spot a dear one’s name, a feeling of acknowledgement envelops their face. Many others stand in front of the wall to capture their own memories with their camera.

 As I watch the wall, I stand in awe. The combination of symbolism of the wall in totality and a tribute…

In this post I want to talk about all of us finding our place and building our careers in data. And when I say “data”, I mean analytics, data science, business intelligence, and so on. In the previous post, I talked…

Beer is delicious but it is not one thing. If you disagree with the former part of the previous sentence please keep the latter in mind[1]. Think of sports, for instance. Many would agree with the blanket statement "sports are fun" but depending on what you have in mind two people can easily have opposite reactions to being presented the opportunity to play ping-pong. Sports are not one thing, music is not one thing, and neither is beer.

Presented with a finely crafted brew in…

In today's blogpost, we take a look at the crime statistics in Philadelphia, investigation from a "data scientist" perspective, so as to speak. This is my attempt at presenting crime in Philadelphia area from a data visualization perspective. Please feel free to add your thoughts and feedback in the comments section.

The…

Project of DeDaL was born in 2014 (or long before) in a context of cancer research in the lab of Computational Systems Biology of Cancer in Institut Curie in Paris in the mind of my research advisor Andrei Zinovyev.

The idea was to develop a tool that would combine multidimensional meta data associated with network and network itself in a form of an intelligent layout. We achieved…

Original post is published at DataScience+

Recently, I become interested to grasp the data from webpages, such as Wikipedia, and to visualize it with R. As I did in my previous post, I use rvest package to get the data from webpage and…

This is a guest repost by Jacob Joseph from CleverTap.

The most widely used coordinate system to represent data is the…

If you want quickly to get started with data analysis, here is my advise on free software programs that I use every day for data analysis, statistics and data mining.

R-package - a software for statistical computing written in C. Script oriented.

• Pros: widely used, simple, extensive documentation.
• Cons: less options for graphics compared to competitors, no…

Learning any new skill is hard. There are too many possibilities, and the goal seems massive and intimidating.

Enter the Pareto Principle.

The Pareto Principle, also known as the 80/20 rule, suggests that 80 percent of results come from 20 percent of efforts. It can be applied to everything from business to language, even learning how to use R.

With just a…

An open-source exploration of the city's neighborhoods, nightlife, airport traffic, and more, through the lens of publicly available taxi and Uber data.

Images are clickable to open hi-res versions.

Pick-ups:

Drop-offs:…

Big Data is, as the adjective suggests, is quite large. Businesses are asked to leverage all sorts of data and data types to make decisions and insights on where to move forward. In years past, making sense of Big Data was the purview of engineers and statisticians who spent the better part of a decade studying these patterns and numbers. But, in recent years, software developers have attempted to cut the middle man out. Data analytics is now becoming more accessible to those even if they…