Session ONE – Extracting Value, Insights and Meaning from Enterprise Data
- Exploring the Big Data value proposition for your enterprise
- Transforming your organisation into a data-driven company
- Harnessing disruptive technologies like AI and Machine Learning for better business value
- Posing and answering new business questions
- Identifying trends and patterns in your data assets to better understand your customers, users, transactions and systems
- Operationalising new processes based on the insights you discover
- Improving business forecasting and decision-making
- Turning data into new visibility and finding areas of your organisation that can benefit from harnessing data
- Gaining real-time actionable insights from your data
- Measuring the effectiveness of your Big Data programme
- Awareness of Big Data’s impactfulness and limitations
The Conference Chair’s Opening Remarks
Powering Digital Transformation with Big Data
Head of Business Intelligence and Big Data Section, The Bank of East Asia, Limited (invited)
The rise of big data has partly been driven by reducing cost and increasing innovation, but its roots go back to the concept of analysing large volumes data from first principles. The sources of this data are typically websites, sensors and other machine sources. Historically, Business Intelligence and Analytics has been a one way-street; applications and content pushing insight out to audiences in the business.
In this short presentation, we look at how:
- The analytical platform offers enormous value when information can also flow in the other direction
- The use of closed-loop information applications can be used to digitise manual processes
- Collecting telemetry from a ‘digital me’ embedded in these apps can address a wide range of challenges from resource management to emergency response.
World Class Data Governance - What It Is, Which Bits of It You Need and How You Can Make It Work for You
Enterprise Architecture, Strategy and Data Governance, The Hong Kong Jockey Club (invited)
Data governance is expensive, time consuming and often irritating. It slows you down or just stops you in your tracks. Better to just forget it and get on with ‘doing the doing’, right? Well, no – do it right and data governance can give you back so much more.
Join me for a lively session exploring what great data governance looks like.
- The value and protection it can give you
- Pick out the most important bits
- Look at the simple steps you can take to get governance benefiting your business
- Finally, taking a peek into the future we’ll see why great data governance might just be the thing that saves the world!
Hong Kong Smart City Developments and Opportunities
Office of the Government Chief Information Officer
As the need to better address issues which are centred on the built environment increases, global cities such as Hong Kong are increasingly adopting the tools necessary to better understand the needs of the population. Such needs range from mobility, living, environmental, people centred, governmental and economic.
In this talk, we will address how the effective use of data analytics can address current issues and provide lasting solutions to the challenge of large scale urbanisation.
Transforming the Customer Experience through Big Data Powered Recommendation Systems
Head Customer Intelligence Analytics, Prudential Corporation Asia (invited)
The rapid improvement in recommendation systems fed on big data and tuned by machine learning has revolutionised how businesses have connected with their customers. While bespoke goods and recommendations used to be prohibitively expensive, it is now possible to individually tailor products and content on a huge scale. Customer habits are changing as well, and there is a growing expectation that consumers should be treated as individuals.
The most successful enterprises will be those that understand and anticipate customer needs and embrace advances in big data and machine learning to tailor their content accordingly.
We discuss in this presentation:
- How recommendation systems can alter customer retention rates
- How you can utilise stored data to create intelligent recommendation systems
- How new advances in machine learning algorithms have defined and will define this space
- Ways in which recommendation systems can be deployed across different areas of business
Data Quality at Day One
Senior Solution Lead (Big Data), Cathay Pacific Airways (invited)
When used well, an analytics programme can have a transformative effect on an enterprise’s decision-making process. But if your business decisions are founded on poor quality data, then not only does it mean you are making decisions without objective value, you are also possibly steering your organisation in the completely wrong direction.
This presentation will explore:
- How you can improve your data hygiene at every stage of the data journey
- How to identify data quality issues – from user errors to processing inaccuracy
- How you need to introduce data quality awareness into every level of your collection and analytics programme
Elements of Good Data Visualisation
Vice President, Big Data and Marketing Analytics, Melco Resorts & Entertainment (invited)
Conveying clear, engaging messages for your insights is critical to effective data usage. Good visualisation allows you to tell compelling stories about your data and ensures insights aren’t lost in translation.
This session will provide an overview of how businesses can utilise visualisation tools and strategies to make sure these messages are communicated.
- Cutting through overwhelming volumes of data to highlight clear messages
- Ways of presenting unstructured data
- Using visualisation to improve forecasting
- Embracing the collaborative and democratizing effect good visualisation spreads across an organisation
- Making your data teams effective communicators
Questions to the Panel of Speakers
Refreshment Break Served in the Exhibition Area
Asia/Pacific Artificial Intelligence and Big Data Strategies
This presentation provides an insight into the key market trends, competitive landscape, technologies, and end-user buying behaviour from IT and LOB standpoints within and across the Asia/pacific region, with a focus on big data and AI and how such developments can assist your business strategy.
Such an insight will increase your understanding of the areas for growth, the competitive positioning of key actors, the priorities, challenges and plans of buyers and how the region is set to evolve.
Exponentially Growing Data Stores: a Burden or an Opportunity
Whilst data warehouses are the preferred method by which the ever increasing volumes of data are kept, many enterprises are coming to the view that other solutions must be adopted in order to address the changing ways in which they wish to analyse and use data.
One innovative solution which seeks to address such changing requirements is the logical data warehouse, which combines traditional storage and usage with alternative data management and access strategies by providing a single point at which global enterprises can view and manage data without creating additional platforms.
In this presentation you will learn about business-driven use cases for logical data warehouses, enabling technologies and practices that make the logical data warehouse fully practical today, and how you can implement it in your organisation.
Questions to the Panel of Speakers and Delegates move to the Seminar Rooms
(To view topics click here )
Networking Lunch Served in the Exhibition Area
Session TWO: HARNESSING THE POTENTIAL OF DATA COLLECTION AND ANALYSIS
- Ensuring Data Quality remains high
- Overcoming the Challenges of Unstructured Data
- Creating Scalable and Adaptive Database Architectures
- Creating Clear and Insightful Data Visualisation
Conference Chair’s Afternoon Address
Understanding Website Click Events Using Data Science and Machine Learning
The relationship between data science, analytics and machine learning is becoming ever more intimate. This is particular true today as organisations seek to gain a deeper understanding of the effectiveness of their landing sites, the layers which lie beneath it, and the impression made on the visitor.
In this talk, we address how you can:
- Capture a variety of search and click data
- Analyse, visualise, and understand the main patterns and groupings within that data
- Establish big data processing frameworks
- Extract and process click event data via ML
Why Data Quality Matters
“Only four types of organisations need to worry about data quality: Those that care about their customers; Those that care about profit and loss; Those that care about their employees; and Those that care about their futures.” – Thomas C. Redman (2006)
An organisations fortunes and failures can be squared directly to the quality of data they have in their possession, how they interpret it, allow it to inform decision making processes and store it for future use.
Good data is your most valuable asset, and bad data can seriously harm your business and credibility.
Data Science: Elements of Success
Being able to sift through data and source value from it is becoming an increasing challenge for large scale organisations just as the increasing complexity of data science as a discipline becomes apparent. Being able to make swift decisions for business benefit is also increasing the need to develop and deepen the role of CDO’s.
Being able to master data science means you will be able to cleanse, prepare and analyse data to a higher standard, make better decisions and improve organisational performance.
• Data Science: An Overview
• Data Wrangling: Challenges and Solutions
• Machine Learning: Techniques which underpin success of a data science project
• Examples of business cases
Questions to the panel of speakers
Afternoon Refreshments and Networking in the Exhibition Area
Building Great Digital Customer Experience by Breaking Down Business and Data Silos – Or How to Add ‘The Why’ to ‘The What’ in Digital Age Marketing
The digital age has transformed the means by which organisations conduct marketing exercises and the ways in which products are marketed to consumers.
In many respects it has also democratised the space in which organisations seek to engage with consumers. No longer can a well established brand name rely on a loyal customer base to ensure continuing success as innovative SME’s increasingly cause market disruption without having to secure significant inward investment thanks to low cost digitised campaigns and dynamic, horizontal management structures.
In this talk, we explore:
- How to design a digital experience improvement programme based on multiples sources of data
- How to break down organisational silos resistant to cross-discipline cooperation
- How to democratise data usage and accessibility
Applying Data Science to the AML Monitoring in Banking
This presentation will focus on applying data analytics to the Anti-Money Laundering (AML) transactions monitoring for investment banking. We will briefly review the most common unsupervised anomaly detection methods, including Isolation Forest algorithm.
One of the most important steps towards successfully detecting money laundering is to recognise that often a transaction can be defined as anomalous only under a certain set of factors. Such factors, being non-obvious, are revealed with the help of considerable subject matter expertise. Knowing the revealing factors allows one to use the right attributes, but still leverage unsupervised machine learning. We will also show why most of transaction monitoring techniques should not be built around a “single-factor” anomaly detection.
How to Build a Data Analytics Strategy for a Digital Bank
Just as the previous epoch in banking saw the expansion of consumer credit, the negative consequences of which are very apparent, the advent of digital banking will result in similar disruption to the sector. Whereas the effect of previous financial crises has disproportionately had a socio-economic impact on the general populace, the era of digital banking will displace banks which have failed to revolutionise their data analytics capabilities.
Every element of banking has been and will continue to be severely disrupted by the digital age unless there is an evident preparedness to develop a data analytics strategy to better understand their customers, their products and increase sales.
In this talk, we address:
- Establishing a challenging and coherent digital vision
- Value chain—from operations and IT to marketing and sales to product development and finance
- Applying advanced analytics to create targeted offerings
- Making data usable in real time
- Combining the data with analytical tools to generate insights
Questions to the Panel of Speakers
Closing Remarks from the Conference Chair
Conference Close, Delegates Depart
Whitehall Media reserve the right to change the programme without prior notice.