Hello! We are Go Data Driven

We build solutions with data science. We know Big Data.

We are GoDataDriven. A team of passionate data scientists and software engineering practitioners. By combining these disciplines with large-scale, open source information platforms, we create data science solutions that add to our clients' bottom line.

What can we do for you?

Recommendations and online personalisation

Whether you are a online retailer, private bank, airline or brick-and-mortar shop with a in-shop mobile site: people take the trouble to visit your site because they are looking for something and if they fail to find anything they need or like, they will leave. Recommendation systems have this one objective: present potential customers with products or services that they need and like. Real world recommender systems take millions or billions of signals into account and make complex trade offs between different recommendation strategies and product selections.

We have experience building multiple custom recommender systems, both in the physical world based on point-of-sale transaction data as well as in e-commerce using clickstream and product catalogue data.

Computer vision

Want one of those apps where a user takes a picture of something and the app looks up all similar products in your catalogue based on the image? We have the technology to make it work. Ever wondered about correlations between your customers' favourite colour profiles and their geography? Let us analyse your product photography in combination with clickstream data and purchases and we'll tell you.

We have created image based search for complex product catalogues and worked with many other computer vision models on product photography and more.

On-site search optimisation

The days that on-site search is just a glorified point of access to a product database are gone. Does your search engine learn about synonyms automatically from user behaviour? Does your search engine automatically correlate search queries with the most likely candidate products? Does your type ahead autocompletion automatically change with user behaviour?

We have worked on several search implementations with all of the above requirements. Improving search through optimisations takes your users form landing to spending more quickly.

Financial transaction analytics

In large organisations and financial institutions, the flow of money tells its own story. Analysing financial transactions individually (as opposed to in aggregate, which is accounting), interesting patterns can be discovered, including new business opportunities, fraud and cash flow issues.

We have worked with multiple financial institutions and large corporates to reap information on opportunities hidden in financial transaction data, through data mining and automated discovery.

Text mining

What are the most common phrases and terms in e-mails from customers who are about to cancel their account? How common is a complaint? These and other interesting insights can be gained from processing large bodies of unstructured text data using text mining and natural language processing techniques.

We have worked on automatically recognising patterns and categorising text content in large, multi-terabyte contract and CRM data sets.

Anything else?

We are not one trick pony's. Please feel free to challenge us. If you send us a (anonymised) sample of your data sets and what business opportunites you hope to gain from it, we promise to give you our initial assessment of feasibility for free!


This is our expertise:

Data Science

The job of a data scientist is to take raw, mostly unstructured, messy data and turn it into valuable insight for the organisation. However, in our view Data Science goes beyond applying the scientific method using data found in organisations. Proving that there is insight hidden in a data set using predictive modelling is just the beginning. Bringing that model into production and acting upon that insight is the business goal. For example: a superior recommender model is what proves the viability of automated recommendations, but a recommender system in production is what makes you money.

This is why our data scientists are business minded, communicative people with actual scientific backgrounds, who are also fluent in programming languages and can work with database systems and Big Data technology.

Learn more at GoDataScience.com...

Engineering

It may take a rocket scientist to figure out how to get to space, but it takes an engineer to build a structure that survives re-rentry while all the buttons keep working. Especially within time and budget constraints. This is also true for (large scale) data science solutions. Without production ready software, Data Science solutions won't benefit you. This is why we apply solid software engineering principles to our projects when they go out of the experimentation phase.

Our world class engineering team is experienced in building production ready, scalable systems. They are comfortable building large scale, fault tolerant systems for high volume environments, such as web properties serving millions of unique visitors or large financial institutions handling millions of transactions daily.

Meet our team...

Big Data

Big Data analytics has become widely available. Technological advances have made it practical to both store and query large volumes of data effectively. What was only possible on the most expensive super computers ten years ago is now within reach on clusters of commodity hardware or even single machines. On top of that, most if not all of the software required for this processing is available as open source, mostly as part of the Apache Hadoop ecosystem without any license fees.

Some of the engineers of GoDataDriven have been using Hadoop since early 2009. Big Data wasn't a common term back then, but the technology opened up a business opportunity for our customer, which is what matters. We've since been the country's leading experts in many open source Big Data technologies. Nowadays, Hadoop is a common piece of technology in many organisations, but whenever we talk about Big Data, we still focus on what matters: the business opportunities of our customers.


Our customers:

  • bol.com
  • booking.com
  • ING
  • Sanoma Media
  • KPN
  • tomtom
  • Rabobank
  • Greenhouse Group
  • Tieto
  • Belastingdienst
  • Funda
  • Reed Busines Media
  • Essent
  • Wehkamp
  • coolblue.com
  • zorgdomein.nl
  • npo.nl
  • SchipholGroup.com
  • klm.nl
  • sonepar.com

Our partners:


The Data Driven way of working

Agile

Big Data technologies, like Hadoop, enable agile working in the data domain. This makes Hadoop a game changer. Work in multidisciplinary teams with software engineers, data scientists and business analysts and deliver value each sprint. Speed is important and Hadoop delivers. On average, Big Data projects deliver value in weeks!

Platform

Many Big Data projects start with exploring the value within unstructured data. You could say to explore what the potential business cases are. As a result of this fuzzy goal, the initial project budgets are often small. Since Hadoop is open source and runs on standard hardware, it gives you the option to start working with Big Data with a small budget.

People

Stop spending money on expensive technology. Invest in your people instead. Knowledge workers want to be challenged and choose the right software for the right purpose. Prevent vendor lock in situations. The Hadoop ecosystem is growing like no other technology ecosystem because it is both scalable and open source.

Big Data

To us Big Data is unstructured, often system generated data, that is too big to fit on a single machine. The volume of the data and processing time exceeds the capabilities of affordable relational databases. It affects every sector and every part of business. The challenge is to handle this tsunami of information to help businesses become better in what they do.


Technology we use: