The Datapred blog

Raw materials, energy, procurement and technology.

Energy buyers: speculation vs. optimization

Measuring the risk of your energy hedging strategy: two simpler alternatives to Value-at-Risk

How much do natural gas storage levels really influence natural gas price fluctuations?

Testing seven gas hedging strategies - And finding the best one

Datapred announces support for power purchase agreements

How often should you reassess your energy procurement strategy?

Datapred announces integration of GPT-4 into energy procurement software

5 limitations of Excel for energy buying reports

Datapred announces new Situation module

What is the impact of China on European gas prices?

Datapred starts coverage of Italian gas prices

Do you have the right buying/hedging strategy?

In such hard times, how can commodity buyers leverage quantitative analysis?

Combining analysis and optimization - Datapred's buyometer

The coal-gas spread and the price of emission allowances

Datapred starts coverage of European emission allowances

A procurement digital twin in the time of rising raw material prices

A digital twin for raw material procurement?

What is driving current European CO2 prices?

The 12 time windows of Procurement

Datapred announces the move of its Paris office to Maison RaiseLab

8 ways machine learning can boost your buying process

Staying ahead of procurement change

How raw material buyers can contribute to emission reduction

5 findings about contextual data and raw material price analysis

Covid-19 and raw materials - The many shapes of instability

Datapred raises Series A from JOIN Capital

Prediction and prescription - Continuous intelligence twins (Part 2/2)

Prediction and prescription - Continuous intelligence twins (Part 1/2)

The next big thing (in business intelligence)

Stop stacking, start aggregating

Datapred wins Airbus’s 2019 time series modeling challenge

Datapred named a Cool Vendor in Sourcing & Procurement Applications

Direct material procurement: beating the market is not the point

Custom loss functions - What they are and why you need them

Productizing machine learning models - What is required?

How should you handle seasonality?

Advanced cross validation tips for time series

Best practices for bulletproof time series modeling

A better Facebook Prophet

Random Forest for predictive maintenance: Try harder

Machine learning for demand prediction: what works and what doesn’t

The basics of backtesting

The problem with deep learning and time series

What is time series, and why is it special?

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