Optimised Data & Analytics

Chairpersons welcome and opening remarks. 

This session will delve into the advanced considerations and best practices for implementing robust data lineage. 

We will explore the significance of data lineage in ensuring data quality, compliance, and trust, and discuss techniques for capturing, tracking, and visualizing data lineage across complex data ecosystems. 

Companies around the world are spending billions to harness the power of data to make better and faster business decisions. However, many modern data initiatives are not able to produce the intended value as companies are struggling to operationalize modern data initiatives. In fact, some analysts estimate that only 15% of modern data initiatives will make it to production. Learn how BMC’s Control-M is helping companies use orchestration, a key principle in DataOps, to not only get data projects into production faster but also run them at scale. Key takeaways include: 

• Data pipeline orchestration across hybrid environments spanning multiple clouds with on-premises 
• Value of the end-to-end view of data pipelines on premises and in the cloud 
• Avoiding missed deadlines with SLA management and critical issue resolution 
• Data workflow integrations into CI/CD toolchains by leveraging Jobs-as-Code approach 

• 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. 

• How to make the first meaningful steps in analytics.
• How to cope with data quality issues.
• How to flourish over the longer term.

• Understand the challenges data mature enterprises are facing as they enable self service reporting 
• Discuss how AI can be used to reduce inevitable analytics risks  
• Dive into cost optimization opportunities in enterprise reporting 

• Examples of rapid advances using transformers, LLMs and other applications in R&D (e.g. in Healthcare) 
• How data have presented expected and unexpected limitations to further advances 
• What can be achieved if organisations can address these limitations & how to find out more 

• 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.  

To follow soon …

• 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 monetise capabilities.