This presentation will concentrate not on what to do, but what not to do including; Over-complicating what is at heart a simple topic. Failing to delineate between content and technology. Thinking you need top down support. Being seduced by Big Data. Selling instead doing.Speaking
Expanding the remit of data and analytics past regulatory needs and switching to an ‘offensive’ approach. Data as a corporate asset – how to move the data analytics function from cost center to profit center. Structuring Data Governance and analytics to optimize outcomes.Speaking
What are the challenges and barriers to becoming more data-driven and facilitating faster, broader access to data? Is it people, process, technology? What best practices help you break down these barriers and create the desired agility? What are some of the best examples of putting data to use in financial services that have created big results?… Read more.Speaking
Struggling to harness the dozens or even hundreds of different data silos across your organization? How can you enable business users to maximize the value of constantly changing sources and volumes of data? Hear best practices for the analytics architecture used to ensure enterprise-wide data governance. Learn about how Networked Analytics can transform an organization’s… Read more.Speaking
Getting the basics right is more important now more than ever, but, ow do you navigate data quality and governance initiatives when the ROI is not so clear? How do you engage the business on these initiatives in the age of machine learning, AI and Blockchain? Examining best practices and implementation of data management, Reference… Read more.Speaking
Evaluating how Governance of data stands at the epicenter of managing enterprise risks as a direct and growing avalanche of new data, technologies and networks become available to the business. Identifying how organizations can optimize compliance and data management with minimal disruption to business process and architectures. What can effective lineage bring to your organisation?… Read more.Speaking
Discussion Group Session 1
Why organizations struggle to realize full data/analytic value, and identifying broken processes. Navigating the complex analytics software and platform ecosystem. Integrating consistent, reusable analytics across diverse data sources and applications. Enabling self-service and agility, while still providing powerful enterprise-level safety, security, and governance.
Discussion Group 1B: Empowering financial marketers and deepening customer relationships through analytics understanding and application
Creating intimate, personalized and convenient customer relationships in the age of digital. Highlight how financial services can remain competitive in relation to customer experience and what customers expect from today’s businesses. Evolving platforms for engagement and new trends.
Discussion Group Session 2
Analytics teams – the key to data monetization – are facing unprecedented change. Amidst a technology transformation (to open source, automation, machine learning and AI…), while facing crushing business demand, and a global talent shortage, analytics leaders are at a cross-roads. How do they balance the talent/technology transformation forging a practical path forward until such… Read more.
How has the scale of big data affected your Analytic Process the most? What benefits have had the biggest impact on your analytic outcome? What detractors have you witnessed with the emergence of far more data involved in your analytic scrutiny? What disruptive technological advances in data have ‘changed the game’ of the analytic process… Read more.
The AI skillset is relatively new and many data scientists do not possess it – do you upskill or hire in? Understanding the impact your next hire will have on your current and future projects. Building a team that complements each other for maximizing business impact. Working within a budget to offer maximum valueSpeaking
Discussing the opportunities and areas prone to disruption from machine learning in financial services. How can machine learning optimise core financial services functions including: risk management, compliance, fraud and customer engagement. The power of storytelling – How do you assure key stakeholders of the benefit generated by machine learning?Speaking