Applied Data & Analytics

Chairpersons welcome and opening remarks. 

• Maximising harvests and minimising waste – how data and analytics have proven to be the ultimate game changer for the agriculture sector through real-time crop insights.  
• How dealing with smaller data pools can help reduce risks. 
• A collaborative effort – how combining capabilities of ML, IoT and drones is continuing to help the sector flourish and meet growing demands in a sustainable way.  

When local entities work with global hubs, then this represents a federated business. Most multinationals today operate like this. In this talk, I share my experiences and lessons from building data products in this context. I will go into some key elements of the data architecture and include examples of products built that rely on personalisation and computer vision. 

• Centralised Vs de-centralised models – allowing for self-service analytics and non-technical users to access insights and make strategic decisions quickly.  
• Allowing for job growth and diversity as those without technical backgrounds can utilise data-led decision making.  
• Where data models need to alter to fit this de-centralised shift – is data mesh architecture the answer for irregular, scattered data?  

• Rising energy prices and optimization issues require the right information for enabling continuous improvement initiatives.  
• Learn how data analytics helps Cono Kaasmakers to meet their sustainability goals.

• What is AgroTech and main application.
• What are the main challenges.
• Some data & AI examples from AgroTech and Probelte.

• Answer common questions early DM adopters often have
• Reveal tried and true workarounds to frequent challenges faced within DM
• Discuss the latest terminologies surrounding DM software

Almost every product today is generating and collecting a lot of data. Don’t let that valuable data just sit there – give your users an easy way to analyse it and drive actions from the insights. In this short session, you will hear how CPOs and Product Managers from multiple industries:

• Increased revenue from subscription fees by up to 25%
• Deliver more value to their customers by interlacing embedded, actionable Analytics in their products, using solutions like Sisense Infuse

• Which obstacles to avoid in building your data stack.
• What features should you look for to be successful in building data pipelines.
• How to enable everybody in the company to work with data.

• Identifying target-rich, high-value data that can be used to generate intelligence. 
• Transitioning from big data to ‘right’ data analytics – how to dissect the data you need. 
• Collection, storage, exchangeability and security – how to ensure optimised processing of data for optimum response and actions. 
• Data as the core of digital – aligning strategies to maximise data capabilities. 

To follow soon …

View Day 1 Content Here:

Enterprise AI — Enterprise AI | AI & ML | Ethics | Automation | Industry Use-case

Digital Transformation Enablers & Innovations – Process Transformation | Model Transformation | Transformation Infrastructure | Hybrid Cloud | Supply Chain | Optimizing Enterprises