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.
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 […]
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.
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.
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 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.
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.
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.
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.
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.
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.
Peter Jönsson, a Solutions Architect at Tableau Software and two-times Data Innovation Summit speaker, shares his views on the most notable breakthroughs with data analytics, as well as the current challenges decision-makers are dealing with, and his predictions for data analytics.
Andy Cotgreave, a Technical Evangelist at Tableau Software, is a data visualisation guru who helps people understand their see and data. He is coming to the 5th edition of the Data Innovation Summit to present how to make an impact with data and encourage people to engage with the information they have at hand.
It’s been several years since the term CDO first appearing on the CXO map. We’ve also previously covered presentations from other speakers that have had the position of a CDO and tried to depict what a Chief Data Officer does, their mandate in the organisation as well as challenges related to the position.
Richard Branch, the VP and General Manager at Semarchy, is going to deliver a presentation at the Data Management Stage at the 5th edition of the Data Innovation Summit 2020 where he will touch upon several MDM points such as why it’s important, traditional vs. modern MDM tools, and the evolving data management needs that call for an innovative and comprehensive MDM platform.
We are going to see Klarna’s story from an engineer’s and data scientist’s point of view, where first we look into their data organisation and structure, and later we’ll devote the white space to their machine learning models for superb purchase experience.