How to impress your boss: Infographics, dashboard, visualization tools

An image worth more than thousand of data, sorry words. Yes, sometimes you have a lot of data to present in a very small period of data. What is better than a good dashboard where to see in a glance your KPI’s or a nice infographics to show tons of info in few seconds?

People don’t have time, so having all in one page is very useful to present but also to make a good storytelling to help your audience to digest complex info and memorize important messages.

63% of your audience could remember stories, but only 5% could remember a single statistic (Source: Stanford professor Chip Heath)

Create an infographics

You can simply create an infographics with Picktochart

Infographics Photo by rawpixel on Unsplash
Infographics Photo by rawpixel on Unsplash

Here how it works:

  • Sign in to piktochart
  • Define a template 
  • Select from the left menu with icon, graphics that you want to change or adjust (graphics, background, text, color, tools) 
  • On the top side you can save, share or download

Below you can find some examples 

A simple but powerful infographics could be found here:

How quitting smoking affect your body

Infographics on Pinterest

What now you have to do is just think about which are the data that you would like to present and how to create a good storytelling that your audience will remind.

If you need to analyze quickly your data, consider to read: How to analyze your data in 5 minutes with Panda.

Build your dashboard in 5 minutes

Dashboard helps you to understand immediately what is going well (maybe showing green numbers, up arrows) and where to investigate more maybe with other self-service reports.  

An example of interactive dashboard
An example of interactive dashboard -Photo by rawpixel on Unsplash

To create powerful visualization you need to fulfill the following requirements:

What I want to explain with this dashboard? Maybe I want to show if we have reach our sales target, or which are the most contributors for growth or products that are in delay

Test how simple and easy to read is your dashboard: go to one of your colleague with less familiarity with technology and ask to explain the content of our report. If he/she report the right message you have created a good one. Otherwise interview other people on what is difficult to read or unclear and simplify.

Create your dashboard: you have several tools to create it:

  • Excel: Best info At where you will discover how to create and manage your dashboard.
  • Python: More complicated but you can define every aspect of your dashboard. 
    • Plotly and Bokeh are the modules that you can use to excel on this topic. 
    • An interesting example is this Bokeh dashboard or Kickstarter project by category and status (successfull, cancelled…) including also name of the project if you pass through 
An example of kickstarter dashboard done in Bokeh
An example of kickstarter dashboard done in Bokeh
  • R: Best choice: Here you can customize everything, using Shiny and Rmarkdown using less code than Python. 
    • An interesting example is R Cran download monitor, where in one page you can see evolution of package download, name 
CRAN download - R dashboard example
CRAN download – R dashboard example









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5 thing you can do better with data mining

Today we will discover more about data mining. If you are not familiar with this concept, it is better that you start to understand more what is behind. We are talking about powerful tools and techique that will help you to get insight from your big data. 

A simple definition is: 

Data mining is the sum of technique and methodologies  to collect information from different sources and manage in automatic way through algorithms and logical patterns

How data mining could help you to collect data ?

Data are growing fastly not only on social and open database, but everywhere. 

With data mining tecnique like data scraping (taking data from internet, like ecommerce price , weather data, stock exchange…),  you can increase number of datasources that you can use for your analysis.

Did you know that you can get data also from images. Discover more here:

In few minutes with very small line of code you can learn how to web scraping data using Python and R

How to group your data: clustering analysis

Image a big databases with many customers. It often happen that you have a lot of different groups of customer . Clustering analysis could easily identify which are customer with affinity that you can address in a similar group target,  maybe because they are similar to size order, purchase need, purchase attitude.

Clustering income vs education
                                 Example of cluster from

This will help you or your firm to set different pricing, product and general marketing strategies more focused for that particular target.

Using Python or R will help you to identify clusters (see below an example of 3 clusters)

Other examples could be find here:

Cluster Analysis by JMP


Regression analysis: identify future output based on historical data

Consider a dataset with icecream sales of last three years and one with temperature information. With regression you can create an algorithm to estimate how much icecream you can sales based on expected temperature

Interesting article that clarify more regression, expecially on marketing 

Anomaly detection

Yes, how many times you have seen dataset with errors like typo distraction or duplicated info. Through specific tools and Machine learning you can easily identify and prevent this kind of error analyzing historical data and suggesting correct value.

How much time you can save from more robust and clear data set? Data scientist usually pass from 70% to 90% cleaning data 

Classification analysis: a powerful data mining technique

In this field are growing machine learning algorithm and chatbot that in future could try to solve most of our questions, maybe about a product features, classifying our question base on common patterns. 

Could be also interesting to identify common words in books, text, maybe through Wordcloud.

Signup to our newsletter to know soon how to analyze through wordcloud any text with Python and discover more info on datamining tools and techniques