Services

Data-capture

We help you to get and organize information from public data or different websites with scrapping.

Data-cleaning

We structure databases with information from multiple databases in multiple formats. Organization of information and standardization of variables.

Visualization apps

We create public data visualization applications so that your users can know and explore databases. We use the latest technologies in data visualization to communicate information.

Algorithms

We implement artificial intelligence algorithms to facilitate your work with data, from predictive algorithms to pattern recognition.

Web specials

We develop interactive web specials based on data. The specials have different visual components to guide your readers. See examples of our specials.

About us

Datasketch is a digital platform of investigative and data journalism. Our portal allows journalists, data scientists, social scientists and citizens in general to learn and consult on data visualizations, tools, software and in-depth research on various short-term issues. We have free data tools and different projects to bridge the gap between data and citizenship that facilitates the democratization of knowledge and a critical review of social realities based on information contrasts.

Our team

Juan Pablo Marín

Electronic engineer with a master's degree in computational statistics. Expert in data science with applications in multiple areas such as economics, hydrology and journalism.

Camila Achuri

Statistics and expert in R programming language. She has developed various applications of data visualization in mobility and open data subjects.

Juliana Galvis

Politologist and candidate for a Master in Digital Humanities. She is currently leading the development of the Who Is database, as well as supporting journalistic research and the creation of databases.

David Daza

Bachelor of Electronics. Expert in development of applications and websites with emphasis on data journalism and content management of multiple databases.

Verónica Toro

Anthropologist and researcher. Responsible for the management and organization of the data-community in Colombia and Latin America and provide support in journalistic investigations and the creation of databases.

Andrea Cervera

Journalist responsible for writing articles, provide investigative support and community manager.

Ana Hernández

Mathematician and expert in R programming language. She has collaborated for various projects such as Infraestructura Visible and in the development of visualization tools.

Contact

This is how you can think like a Freak when handling data

June 12, 2017

The best-selling Freakonimics authors explain how they’ve been creating a data culture all their own, showing the world how to make smarter, savvier decisions with data.  What is their main advice to, in other words, think like a Freak? 

How can you make better data? How can you share stories and have an impact in people with what you’re doing? This is the question that Stephen Dubner and Steven Levitt, the authors behind the series Freakonomics, tried to answer during the Microsoft Summit. 

 Stephen Dubner is an award-winning author, journalist, and radio and TV personality. Steven Levitt is a tenured professor at the University of Chicago's economics department and was the 2003 recipient of the American Economic Association’s prestigious John Bates Clark Medal, given to the country's best economist under 40.

 They are best known for the Freakonomics series, including Freakonomics, SuperFreakonomics, Think Like a Freak and When to Rob a Bank. They have sold more than seven million copies in more than 40 countries. Dubner is also the host of the Freakonomics Radio podcast, which gets five million downloads a month. 

The best-selling authors gave the closing Keynote at the Summit explaining how they’ve been creating a data culture all their own, showing the world how to make smarter, savvier decisions with data. 

What is their main advice to, in other words, think like a Freak?  

 

 

1. Don’t look for talent but for topics

Sometimes, people focus too much on developing a talent and being unique with that talent. But the Freaks recommend to tackle and investigate topics that are being overseen by people or that none one else wants to tackle. Talent can be developed by anyone, but tackling interesting and different data or stories is key to success. 

2. Make data useful

One of the biggest mistakes data scientist or journalist make is giving people data they don’t understand or they can’t use in their daily life. If you want your information to have an impact, people needs to understand it and you need to make it extra simple for them. EXTRA SIMPLE. Don’t show off!

3. Build knowledge together

Sometimes, teams tend to rely on just one person who knows how to do it all. This is not good. To avoid this, the Freaks recommend to build knowledge together and to make sure this knowledge is stored in a document that everybody can access and where anybody can pour new knowledge. 

4. Let people interpret data

Telling people exactly what a number means gets them mad. Especially when they feel you don’t know the whole story behind that, or that you’re framing the information. So instead of interpreting data for them, give it to them. Explain it to them and guide them through your analysis, but let them make the choices or the conclusions. 

5. Use data to highlight problems

People tend to say there are issues and support their views with opinions, not data. Don’t do that! Highlight problems by doing data analysis and explain the issue with data, not opinions. Then, find solutions through opinions and examples. 

 6. Stories are more important than data

Nothing sells better than when people can feel related to what you want them to see. This is why stories are incredibly important to sell the data. People can’t relate to numbers or statistics, they relate to stories. So find a story that allows them to navigate your data and engage with what you’re proposing. 

María Isabel Magaña

Journalist, Master in Investigative Journalism and #DataViz. Thus, I see data everywhere. Promoting transparency through queremosdatos.co