---
title: Introduction to self-service analytics - webinar on demand
description: TrendMiner webinar on demand - watch the Introduction to Self-Service Analytics webinar and discover five ways to improve your production process.
---

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**Introduction to self-service analytics**

Available on demand

 

In this webinar, we discuss the 5 ways to improve your production process through self-service analytics. This approach allows process engineers and other subject matter experts to analyze, monitor and predict process performance without depending on data scientists.

 

Watch this webinar to discover:

1. How to analyze process performance to set your golden fingerprint   
2. How root cause analysis can improve process performance  
3. Ways to monitor the process and give early warnings in case of deviations  
4. How to predict process performance using historical production patterns  
5. How to share knowledge and collaborate to improve processes across sites

![Webinar on demand: Introduction to Self-service Analytics](https://forms.trendminer.com/hs-fs/hubfs/TM2017/5ways-screen-DEMAND.png?width=300&name=5ways-screen-DEMAND.png "Webinar on demand: Introduction to Self-service Analytics")

To watch this content on demand, please complete the form on the right.   
You will be shown the webinar immediately.

**Why watch this webinar?**

Data science is not just for data scientists

 

Analyze

Learn why a self-service analytics tool can help you improve your manufacturing processes. Easily identify the root cause for production deviations or find the best production runs as golden batch.

![Analyze-small.png](https://forms.trendminer.com/hs-fs/hubfs/TM2017/Analyze-small.png?width=125&name=Analyze-small.png "Analyze-small.png")

 

Monitor

Discover the role that fingerprints play in monitoring production process. Notifications are the basis for active learning within the organization – learn how they also help to improve operational performance.

![Monitor-small.png](https://forms.trendminer.com/hs-fs/hubfs/TM2017/Monitor-small.png?width=125&name=Monitor-small.png "Monitor-small.png")

 

Predict

Benefit from past process performance data to predict the future. Provide control room with early warnings to ensure product quality, reduce waste and reduce energy consumption.

![Predict-small.png](https://forms.trendminer.com/hs-fs/hubfs/TM2017/Predict-small.png?width=125&name=Predict-small.png "Predict-small.png")

![Thomas Dhollander](https://forms.trendminer.com/hs-fs/hubfs/TM2017/ThomasDhollander2017.jpg?width=150&name=ThomasDhollander2017.jpg "Thomas Dhollander")

**Presented by: Thomas Dhollander**

VP Products & Co-founder of TrendMiner

 

Thomas is an expert in algorithm design and time series analytics for process data. From 2005 to 2008 he was active as a data mining and machine learning research engineer at the KULeuven University in Leuven, Belgium. Thomas holds a Master in Science in Mechanical-Electrotechnical Engineering (data mining & automation) from KULeuven and a Master of Arts in Cognitive and Neural Systems from Boston University.

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