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


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.


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.

Mariana Villamizar

Systems engineer and designer. Expert in user experience, data visualization and graphic communication. Feminist.


This course will teach everything you need to know about Excel for #ddj

June 05, 2017

Datasets are mostly never clean, neat or organized.They have  errors, missing values, wrong formatting… most of the times it’s a nightmare.

Understanding what story the numbers are telling is the most important thing when doing #ddj, but getting there is hard. Facing data is a messy business. Datasets are mostly never clean, neat or organized.They have  errors, missing values, wrong formatting… most of the times it’s a nightmare.


In order to face this challenge, journalist and people working with data need to learn how to use tools to clean and structure the information. When datasets include multiple cells and numbers, this process can’t be made manually because you risk making errors and you will waste too much time.


Thus, if you don’t know any programming tool, Excel is a great option for you. This Learno.Net course is a great way to learn how to clean, transform and analyse data using this tool. You’ll also learn some strategies and tricks for managing data cleaning processes.


The course instructor is the data journalist, data designer and visualization consultant Maarten Lambrechts, who has worked with  MO* magazine and was later hired as a data and multimedia journalist by Mediafin, the publisher of Belgian newspapers De Tijd and L’Echo.


The course is free, online and the total running time is 84 minutes divided in 4 different modules.  No prior knowledge is needed, but a little knowledge of Microsoft Excel will come in handy.


You can sign up here.

María Isabel Magaña

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

This is the ultimate dataset to find reliable sources

June 04, 2017
This is the ultimate dataset to find reliable sources