Building Data Science & AI

We can help build your AI Use-case

Building Data Science & AI

Artificial Intelligence and Data Science means applying techniques and mathematical methods to leverage data into action-oriented predictions or recommendations. Once the use-cases are prioritized, our Data Science expert can help co-develop Data Science in Spark, Python, Scala or R.



How can we help in Data Science and what is our approach?

element61 differentiates in Data Science development by taking a coaching and co-development approach. While building your Data Science use-cases, we train and onboard your internal team so they get acquainted with these new tools, methods and best-practices.

Our Data Science approach always consists of 3 phases:


Building Data Science & AI

Data Discovery
We mine the data for patterns and insights. We look at all the data and, with the business case in mind, our goal is to deliver new insights to the business in week 1.
Data Discovery is typically done in a local Python (small data) or a Spark Databricks environment (big data).

Results are presented in business steerco's in PowerPoint format.


Building Data Science & AI

Machine Learning
Using the learnings from our Data Discovery phase, we build the Data Science model; depending on the use case, we use a specific type of Machine Learning algorithm (regression, classification, clustering) . We iterate through various ML options and find the optimal approach.
In this phase we leverage Python, R or Spark (Pyspark or SparkR) to build features, try out models and identify a working machine learning fit.

Progress and model approach/accuracies are presented bi-weekly in a status-meeting.


Building Data Science & AI

Business Validation
We want to test the predictive model in a real-life scenario. This means running the model daily or weekly, providing recommendations to the business and gathering feedback. If possible, we recommend a quantifiable test including a neutral test group.

Results are presented in business steerco's and the process is iterated for continuous model improvement.


Read more on our Data Science Methodology

How to get started?

We are convinced that getting started with Data Science is accessible for organizations of any size and industry. Based on recent evolutions of the Cloud, a first Proof of Concept doesn't require big investments and tangible ROI can be achieved within 60 days.

Contact us for more information and let's get started!