What are probabilistic digital twins and how are they used in asset management?
Digital twins are virtual representations of real-life manufacturing assets. But they are not only models of the physical objects; they serve as a bridge and co-creation between data scientists and engineers. However, what digital twins fail to capture is the risk of assets and the environment to prevent failure.
Is coronavirus (COVID 19) a black swan scenario for the world economy?
The world is undeniably facing a new, challenging and an unpredictable event with the outbreak of the COVID-19 virus, known as the coronavirus. So far, it has affected more than 550,000 people worldwide and has left business fearing total collapse.
How to create happy and high performing teams with the help of data
Happy and high performing teams are the key to every business success. But how can organisations truly measure happiness and performance? Can they put a number to them?
Three approaches to predictive maintenance of baggage handling systems
The baggage handling systems at airports are some of the most complex conveyor systems. They are the bloodstream of the airports, which makes them a vital component of airport operations.
Data security fundamentals: To protect your data, you need to understand it
In the data-driven era, data protection and data security are crucial for companies. However, they can’t protect their data, if they don’t understand it first. We had a chat with Derek Coetzee, CTO at Getvisibility, about how QBS Laknova along with Getvisibility help businesses get to know their data, by discovering, classifying and protecting it, before their attendance at the Data Innovation Summit […]
Up-close overview of data engineering from a data engineer’s point of view
Michal Gancarski, Data Engineer at Zalando, shared with us his perspective on the data engineering developments during the past several years and brought us closer to the process of buidling data pipelines and serverless data infrastructure.
Experts advise: How to turn data into insights in the AI industrialisation era
The decade of data and AI industrialisation holds great potential for organisations to see the full value of their data and AI investments. However, without a proper plan for adoption, firms can experience the detrimental consequences of resource and funding misallocation, warns Ashley Cline, VP of Sales at Cloud Interactive.
An ML model that facilitates employee transfer in a company
Adam McKinnon, Advanced People Analytics Practitioner at Merck KGaA, a German multinational pharmaceutical, chemical and life sciences company, demonstrated a case study involving a practical approach with text analytics for facilitating job rotation within the organisation at the Nordic People Analytics Summit 2019.
The IoT piece in the growing Nordic PropTech puzzle
The promising Nordic PropTech scene has been on the rise for several years and has attracted the watchful eye of industry experts. Assiduous PropTech companies are busy with creating smart solutions ready to answer the market demand for smart homes and smart buildings.
Ensuring data quality from top to bottom at Grundfos
And as data is at the core of their digital offerings, ensuring high data quality along their whole value chains is Grundfos’ most critical priority.
Democratising model building at ING Bank
Data science in banking may sound a bit boring. However, data scientists have had their hands full with working on some really interesting challenges that banks have been experiencing these past several years.
Business
Is coronavirus (COVID 19) a black swan scenario for the world economy?
The world is undeniably facing a new, challenging and an unpredictable event with the outbreak of the COVID-19 virus, known as the coronavirus. So far, it has affected more than 550,000 people worldwide and has left business fearing total collapse.
How to create happy and high performing teams with the help of data
Happy and high performing teams are the key to every business success. But how can organisations truly measure happiness and performance? Can they put a number to them?
Data security fundamentals: To protect your data, you need to understand it
In the data-driven era, data protection and data security are crucial for companies. However, they can’t protect their data, if they don’t understand it first. We had a chat with […]
Experts advise: How to turn data into insights in the AI industrialisation era
The decade of data and AI industrialisation holds great potential for organisations to see the full value of their data and AI investments. However, without a proper plan for adoption, firms can experience the detrimental consequences of resource and funding misallocation, warns Ashley Cline, VP of Sales at Cloud Interactive.
An ML model that facilitates employee transfer in a company
Adam McKinnon, Advanced People Analytics Practitioner at Merck KGaA, a German multinational pharmaceutical, chemical and life sciences company, demonstrated a case study involving a practical approach with text analytics for facilitating job rotation within the organisation at the Nordic People Analytics Summit 2019.
The IoT piece in the growing Nordic PropTech puzzle
The promising Nordic PropTech scene has been on the rise for several years and has attracted the watchful eye of industry experts. Assiduous PropTech companies are busy with creating smart solutions ready to answer the market demand for smart homes and smart buildings.
Ensuring data quality from top to bottom at Grundfos
And as data is at the core of their digital offerings, ensuring high data quality along their whole value chains is Grundfos’ most critical priority.
Democratising model building at ING Bank
Data science in banking may sound a bit boring. However, data scientists have had their hands full with working on some really interesting challenges that banks have been experiencing these past several years.
Data and AI Innovators – Henrik Göthberg
As we’ve entered into the data and AI industrialisation and stabilisation decade, and leaving behind us the pioneering/piloting phase, working to become Data/AI Ready is the next logical step for one data-driven enterprise.
How to reduce your employee turnover with ML
Luke Whelan, Head of Analytics at Talivest gave a talk at the Nordic People Analytics Summit in Stockholm last year on a machine learning solution he built that helped a call centre to reduce its employee turnover by 30% within six months. And this is his story of how it happened.
Tech
What are probabilistic digital twins and how are they used in asset management?
Digital twins are virtual representations of real-life manufacturing assets. But they are not only models of the physical objects; they serve as a bridge and co-creation between data scientists and engineers. However, what digital twins fail to capture is the risk of assets and the environment to prevent failure.
Three approaches to predictive maintenance of baggage handling systems
The baggage handling systems at airports are some of the most complex conveyor systems. They are the bloodstream of the airports, which makes them a vital component of airport operations.
Up-close overview of data engineering from a data engineer’s point of view
Michal Gancarski, Data Engineer at Zalando, shared with us his perspective on the data engineering developments during the past several years and brought us closer to the process of buidling data pipelines and serverless data infrastructure.
Deep learning applications for corrosion detection
Matias Ferrero, RAMS Engineer at Norwegian University of Science and Technology (NTNU) some state-of-the-art deep learning approaches at the Maintenance Analytics Summit 2019.
How Equinor deploys machine learning at scale
The usual way of implementing machine learning and AI in an organisation starts with doing proofs of concept and pilot projects for specific use cases. But this approach falls short of delivering any ROI for the business to be able to justify the cost.
How to build interpretable machine learning models
As AI and machine learning are becoming an increasing part of our lives and businesses, our need to interpret machine learning models so we can trust them and deploy them with confidence is also growing.
How VR Group uses machine learning to predict passenger number
The passenger number is a crucial figure in railway operations that impact the overall functioning of the commuter railway traffic. But in the case of VR Group, Finland’s government-owned railway company, with over 14 million passengers carried on long-distance rail services only in 2019, predicting passenger number requires additional helping hand by machine learning.
Why and where The LEGO Group deploys machine learning models
Francesc Joan Riera, Applied Machine Learning Engineer, Data Engineering at The LEGO Group, is coming to the Data Innovation Summit 2020 to demonstrate how they train, maintain and update deployed machine learning models for LEGO’s Moderation Service.
Data and AI Innovators – Clair Sullivan
Clair demonstrated a deep learning method that can be used to detect duplicate code at GitHub, which is more than half of all the code on the platform.
Can we trust deep learning to detect duplicate code? GitHub did it
Clair Sullivan talked about duplicate code on GitHub and how they make sense of it using deep learning on graphs of code.