I was born in the age where ‘online’ became a word. My generation invented a lot of the digital concepts floating around. Data exponentially grew and up to today this trend still did not stop. An interesting wave of innovation is the amount of seemingly ‘free’ solutions found online, we don’t pay with money, we ‘pay’ for it with a new type of currency; data. This is why we know data is valuable and will enable us to see things from new perspectives. It’s up to us and next generations to make sure data will add to our evolution to create an exciting future. Lets go!
What About Me?
First and foremost; I love to translate data into insights. I know that building data-driven solutions, for learning and decision making, requires you to put in effort into multiple facets of this intriguing craftsmanship.
An optimal solution takes into account the many ways in which data can be transformed and calculated to measure or contextualize all these events and occurrences. Naturally, analysis is done in top-down fashion, breaking down the elements of a bigger picture to understand all the parts.
This means as an information and analytics designer you need to understand what this ‘big picture’ and associated logic looks like, to be able to build different types of analysis. Such solutions help a consumer follow its path from top to bottom, where in the end a conclusion or narrative can be derived.
Together we need to:
- Understand where the data is captured for what purpose
- Know which people might benefit from it in their daily lives
- How measurement of one thing might influence others
- Design solutions with consistency, flow and a holistic top-down methodology
- Talk to consumers about inefficiencies or next steps
- Keep asking ‘Is this the easiest way possible?’
- Experiment with data, representation and arrangement to understand the rules and constraints
What I Believe.
Adoption really comes from a user’s experience. If they can’t understand or use it, it is worthless.
Only the data and logic you apply can inform design decisions. If you don’t care about a metric’s logic and associations, you can’t analyze the outcomes.
Start @ End
Data is only valuable when it enables learning or decision making. You can only draw a conclusion at the end of an analysis. That is where a good design starts.
“It’s easy to make things complex.” Commit to turn this idea 180 degrees.
“We don’t know what we don’t know. Explore, experiment and break stuff to figure out.” This is the start for improvement or maybe see things from a whole new perspective.
Time = Valuable
Time is expensive, demand exceeds supply. Keep your things brief and relevant!
Tools and Apps – %
Skills and Techniques – %
MS Excel / Spreadsheets
Photoshop and Alike
Azure / AWS
MS SQL Server
PostgreSQL / MySQL
Tableau / Power BI
Miro / xMind / WordPress
Agile / Scrum
HTML / CSS
Design and UX
My Road Trip
Bonnet Financial Management
I worked here for 5 years fulfilling financial activities as a Business / Financial Controller.
Cendris Customer Contact
I started here as a Financial / Reporting Controller. It is here where I transitioned my role to be data-driven as a Business Intelligence Analyst.
My First Qlik App
I started creating data-driven analytics solutions here.
I had founded this company for a while here. At this time, in 2011, I intended to start my own Analytics Agency.
During my start-up of Credis, Qlik reached out to me. I decided to join; I couldn't possibly be closer to what mattered to me at that point.
My Online Presence
My LinkedIn Profile
This is my professional profile on LinkedIn. You can visit my profile to get more information.http://www.linkedin.com/in/gotoptw
On Qlikshow.com you can find articles on the intersections of data, design and ideas.http://qlikshow.com
At dataonthe.rocks you can find articles about data and analytics within a wide range of categories.http://dataonthe.rocks
My Twitter Feed
On my twitter feed you can see what I share with the world.http://twitter.com/creatuluw
For quite some time now I am into the Quantified Self movement. This means that over the years I have been collecting data that says something about me. Look at the tree structure showing what data within what topic I am collecting about myself.
Below you can see how I listen to music during an average day.