Optimised Data & Analytics

Chairpersons welcome and opening remarks. 

• 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? 

This session will delve into the current Data as a Service (DaaS) models, and how enterprises can capitalise on these services within markets.  

• Identifying and breaking down silos across departments and business data stacks.  
• How to maximise data sets and data pipelines.    
• Aligning data with specific business goals – making use of insights for targeted business e.g. seasonal buying cycles and customer demand. 
• Collection, storage, exchangeability and security – how to ensure optimised processing of data for optimum response and actions. 

• Where to start in 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. 
• Fostering a data driven culture to create a holistic data eco-system for optimised results.  

• The advantages of decentralizing data  
• Utilising the enterprises strategic advantage – how to unlock data’s value.  
• Studying current processes for capturing data and looking at next steps.  

• Understanding the challenges businesses are facing and looking at how data can be the answer, including data warehousing, mining and analytics.  
• Data as the core of digital intelligence – aligning strategies to maximise data capabilities.  

• How to get the most out of real time intelligence – what process need to be in place to aid this?  
• Tackling the issues around legacy systems and the lack of available data for intelligent decision making – what are the current market solutions that can help?  
• How being adaptable can lead to optimised services, reduced downtime and in some industries, help save lives.  
• Taking the next steps to semi and fully autonomous systems enabling advanced analytics. 

• Understanding regulatory and data privacy obligations – how to maximise trust and compliance across assets. 
• How to ensure your data environment is giving you the best opportunity to govern access and storage.  
• Best practices in DataOps for governance and compliance.  
• A future with synthetic data generation.  

• Understanding the real value of data before trying to add a price tag to deliverables.  
• How to measure data through KPI’s – creating a holistic business strategy where data is part of the chain.  
• Discoverability and data quality – the key pillars for being able to action and monetize capabilities.