How to install Lotus Notes 8.x on Mountain Lion and Mavericks


Have you tried installing the Lotus Notes 8.x client on your Mac with Mountain Lion or Mavericks, and failed?

Claudio has an easy-to-follow solution for you.


A short and sweet introduction to Pentaho Data Integration

6906OT_Instant Pentaho Data Integration Kitchen
Whenever I have to create or maintain a Pentaho Data Integration scheduled job I have to go back to the Pentaho wiki or google for use cases. Although I should, I never remember the specifics and going through 2007 forum posts and outdated documentation is always a pain.

Recently, I stumbled upon Instant Pentaho Data Integration Kitchen, a quick and inexpensive reference guide for using the PDI command line tools.

Sergio Ramazzina guides you through the process of designing a simple Data Integration job –along with best practices that will ease your life come maintenance day–, using the proper command line tool and scheduling the transformation for periodic execution.

If you’re looking for a short, inexpensive and authoritative guide on creating Pentaho Data Integration jobs and scheduling them using the command line tools, this is it.

Instant Pentaho Data Integration Kitchen


How to improve your Business Objects charts

disaster, disguised as a "dashboard"

disaster, disguised as a “dashboard”

Business Objects, SAP’s BI platform, is notoriously bad for data visualization. Somehow, it empowers the developers to make all the wrong decisions at the same time and create really ugly and unusable “dashboards”.

Lately, I’ve seen my share of ugly bobip visualizations, like the one above. Which would seem ok but it commits the greatest of sins: unnecessary embellishment.

To create better Business Objects visualizations you should try to avoid “non data ink”, like:

  • Unnecessary big numbers (100,000,000 could be abbreviated to 100M)
  • Axis borders.
  • Colored or gradient backgrounds.

Also, you could re-work your charts to remove:

  • Data point markers.
  • Double vertical axis.

Also, surprisingly –or not– Business Objects lets you mix bars and lines to confuse the reader:


Lines in a chart are supposed to express continuity, cause and effect.

In this case, the use of lines confuses the reader. There’s no logic in stating that a measurement in the leftmost products influences the ones at the right.

Unless you have a time measurement in the horizontal axis, you should avoid using lines mixed with bars.

All this omissions and mistakes defies the purpose of the chart, which is to give a quick assessment of the situation. A professional product like Business Objects shouldn’t let you make those mistakes. But unfortunately it does and that’s why your charts suck.

Noah Iliinsky addresses some of this charting “sins” in his famous talk “Data Viz: You’re Doin’ it Wrong”

I don’t doubt for a second that SAP’s BI Platform must be great for building data warehouses, but it’s notoriously poor as a tool for visualizing data. You would be better served by using bobip in the back-end and disguising it with Processing, D3js or some other library to better show of the fruits of your hard work. In every Business Intelligence endeavor, charts are the visible face of the project. If your charts suck, your project sucks. Is as easy as that.

As a developer, it also helps to learn some design elements and even do some reading on the subject. Remember: your charts and dashboard should be compelling enough to inspire and motivate the users to dive into the data.


How to present statistics without boring your audience


A few days ago I found a very valuable, yet free resource for improving the way we report statistics.

Making Data Meaningful is a series of short, sweet and free ebooks created by the United Nations Economic Commission for Europe as a practical tool to improve the way charts, tables and statistical data are presented to the general public.

Don’t be deterred by the official designed-by-committee air that a UN publication may have, this are books inspired by the latest trends on mass communications and data visualization. In it you will find several references to some of my favorite books: Few’s “Show Me The Numbers” and Tufte’s “The Visual Display of Quantitative Information”.

I particularly like Part 1, “A guide to writing stories about numbers“, because in a very concise manner, it proposes a way of changing your approach to presenting statistics. Starting from the language. Look at this wonderful summary:


  • Language that people understand;
  • Short sentences, short paragraphs;
  • One main idea per paragraph;
  • Subheadings to guide the reader’s eye;
  • Simple language: “Get,” not “acquire.” “About,” not “approximately.” “Same,” not “identical”;
  • Bulleted lists for easy scanning;
  • A good editor. Go beyond Spell-Check; ask a colleague to read your article;
  • Active voice. “We found that…” Not: “It was found that….”;
  • Numbers in a consistent fashion: For example, choose 20 or twenty, and stick with your choice;
  • Rounded numbers (both long decimals and big numbers);
  • Embedded quotes (these are sentences that generally explain “how” or “why”,
  • and which journalists like to use verbatim in their news stories in quotes);
  • URLs, or electronic links, to provide your reader with a full report containing further information.


  • “Elevator statistics”: This went up, this went down, this went up;
  • argon and technical terms;
  • Acronyms;
  • All capital letters and all italics: Mixed upper and lower case is easier to read;
  • “Table reading”, that is, describing every cell of a complex table in your text.


And then, they present several ways on how you could improve your writing skills:

Not Good:
From January to August, the total square metres of utility floor space building starts rose by 20.5% from the January to August period last year.

In the first eight months of 2004, the amount of utility floor space started was about 20% higher than in the same period of 2003.


Also, another wonderful summary about creating better charts:

  • Achieve clarity in your graphics by:
  • Using solids rather than patterns for line styles and fills;
  • Avoiding data point markers on line graphs;
  • Using data values on a graph only if they don’t interfere with the reader’s ability to see the big picture;
  • Starting the Y axis scale at zero;
  • Using only one unit of measurement per graphic;
  • Using two-dimensional designs for two-dimensional data;
  • Making all text on the graph easy to understand;
    • Not using abbreviations;
    • Avoiding acronyms;
    • Writing labels from left to right;
    • Using proper grammar;
    • Avoiding legends except on maps.


Few people stop to think about how others will interpret or read their findings. Others are delusional enough that they deliberately stay away from this “journalistic style” and think that numbers speak for themselves. That’s rarely the case.

Even if you have a chart that tries to explain the numbers, you still have to put up some work to make those statistics interesting enough so that they stand out and you don’t bore or confuse your audience. You have to tell a compelling story, you have to incite curiosity, questioning and further exploration. Even if you’re doing a private report, you have to be a journalist and a storyteller.

So if you want a quick crash course on the subject, go on the UNECE website, download Making Data Meaningful and give it a read.


Drawing the world by hand

At Lucerne’s Gletschergarten, among old maps, models and reliefs of the Swiss Alps, we’ll find an expo from Ueli Läuppi, a local cartographer that makes hand drawings and colorings of maps using a particular projection that highlights a thorough representation of the mountains.

Moreover, Läuppi has moved his studio to the museum and on certain days you can actually see him completing a precipitation map from an Asian region using a rapidograph and a box with carefully labeled Caran d’Ache color pencils to differentiate rainfall ranges.

Läuppi’s work is at he crossroads between science and art. His extensive research (documented on video) evidences his background as an engineer, and his will power to temporarily move his studio to the museum borders on performance art.  It’s also evident that Läuppi knows a thing or two about visualization. His maps are very eloquent when it comes to representing data and explaining their meaning.

Personally, I consider that the staging of this desk in the middle of the exhibition with the rest of the unfinished pieces sends a message: maps are made by people and it’s hard to draw maps.

All of this reminded me of a post about the wireframes and skeletons for web apps and pages and the opinions of some experts who believe presenting sketches instead of perfect lines gives your output a “work in progress” feeling, opening the doors for engagement and getting better and more timely feedback from your clients.


In Sketchy Rendering for Information Visualization, Jo Wood, Petra Isenber, Tobias Isenberg, Jason Dykes, Nadia Boukhelifa and Aidan Slingsby, propose drawing visualizations as if they were made with a marker on a board, in order to communicate that the design is not complete, that is open to criticism and changes, and that visualizations and dashboards represent a narrative in progress. Also, unlike architectural drawings or industrial designs, graphics don’t represent tangible objects, so they don’t need to be accurate. Their goal is to help tell a story. Just as the proverbial business plan written in a napkin, graphics with sketches aim to illustrate a point and it’s ok to sacrifice some accuracy.

The imprecision suggested by sketchy features may reinforce perceptions of simplicity and thus reduce the expectation of cognitive effort required to interpret the visual scene

As part of the method illustrated on paper, authors have created a free library to be used with Processing that provides astonishing results:

They seem hand-drawn, right?

And maybe there’s another key: just as with Läuppi’s maps, these graphics convey the idea that visualization was thought out and made by a human and that there’s meticulous work behind them.

A Handsome Atlas gathers visualizations completed at the end of the XIX century for the US census. These are graphics of great beauty, charts that tell a story and that are truly different from the automatic output done on excel.

We forget that graphics need to be well-thought; that they should communicate something, be memorable and situate themselves between art and science.  And although a computer does the rendering job on the screen, when visualizing data we’re also drawing the world by hand.

Läuppi’s expo will be displayed at the Glacier Garden until September 15th of 2013.