Meetup topic

Data Science

Date

19 January 2024

Location

El Niño office Enschede


Speakers

  • Kelbi Kalbiyev

  • Jeroen Rinzema

  • Teun Lassche

Access the meetup slides here

Turning Data into Action

The El Niño Data Science Meetup showcased innovative applications of data across industries. Ali Kalbiyev demonstrated how Dynamic ESS leverages energy forecasts and linear programming to optimise battery use and reduce energy costs.

Jeroen Rinzema from CloudProud explored how Data Mesh and Data Fabric architectures empower organisations to scale data accessibility and governance.

Teun from DSIT presented how data-driven analysis enhances product recommendations and inventory management, boosting efficiency and turnover.

Together, these talks highlighted how intelligent data strategies can transform operations and decision-making at every level.

A group of people socializing at the data science meetup with some chatting and others enjoying food and drinks.

Dynamic ESS: Minimising Energy Costs at Every Scale

VRM collects a wide range of data that can be leveraged to determine the optimal times to charge and discharge batteries. Ali explained the mathematical approach behind creating such a system and how forecasts can be used to identify the most cost-effective charging and discharging periods.

A man in a black sweater speaks to an audience at the data science meetup, standing near a screen displaying a presentation slide.

Data Mesh & Data Fabric

Jeroen from CloudProud discussed the concepts of data mesh and data fabric, explaining how these architectures can be adopted within existing system designs to improve scalability and data accessibility.

A man in a brown outfit gives a presentation at the data science meetup, standing on a wooden box. A screen displays a slide with graphs and text.

Data at DSIT

Teun from DSIT demonstrated how data can be used to recommend complementary products often purchased or used together with items added to the cart. Additionally, this data enables analysis of product performance and stock levels, allowing warehouses to restock items based on real demand. This data-driven approach led to improved stock turnover and operational efficiency.

A person in a black sweater and light pants speaks to an audience, standing on a platform in front of a large window and a presentation screen.
People socializing at the data science meetup, with a man in the foreground serving food.
A man stands on a box, giving a presentation to an audience. A screen displays information beside him.
A group of people seated attentively at the data science meetup, with some standing in the background.
Two people engaged in a lively conversation indoors. One is facing the camera, gesturing with enthusiasm, while the other listens attentively.