Data is often siloed by rigid architectures that separate information according to functional area and data type. This often results in splintered views and difficulty accessing data, ultimately limiting the value of analytics. In this track you’ll learn how to collect data of every type, regardless of where it lives in your organisation, to help enable flexibility in the face of ever-changing data sources. With new high-performance data virtualisation technology, you can now access data across multiple types, sources and locations within a single view. This real-time virtualised data helps simplify how you fuel your AI initiatives without moving data, dealing with the complexity of data duplication, the cost of additional storage or extract, transform, load (ETL).

12:45-13:05pm AEST
14:45-15:05pm NZST

Make your data simple and accessible

In order to successfully infuse AI throughout your business, you need to be able to collect data of virtually every type —regardless of where it lives in your enterprise — to help enable flexibility in the face of ever-changing data sources. Attend this session to learn how, IBM is innovating in the data collection business, and how companies are gaining competitive advantage in the new reality of today's complex and hybrid data ecosystems.

Speaker:

Trevor Noseda Team Leader, Hybrid Data Management Technical Sales, IBM

13:05-13:25pm AEST
15:05-15:25pm NZST

Eliminate data silos: Query many systems as one

Attend this session to learn about Data Virtualisation in IBM Cloud Pak for Data. Data Virtualisation is a unique new technology that allows users to access data across multiple types, sources and locations within a single view. This real-time virtualised data helps simplify how you fuel your AI initiatives without moving data, dealing with the complexities of data duplication or extract, transform and load jobs, nor the costs of additional storage.

Speaker:

Hui Sim Ng Information Architecture Technical Sales Specialist, IBM

13:25-13:45pm AEST
15:25-15:45pm NZST

IBM Cloud and hybrid databases: An unprecedented range of services

This session will showcase IBM's current and evolving suite of cloud and hybrid cloud databases, including proprietary and open source technologies like Db2, Netezza, PostgreSQL and MongoDB. With the help of tech demos, we’ll discuss how to create a unified experience across a range of cloud and private environments with IBM.

Speaker:

Isaac Tranis Information Architecture Technical Development Manager, IBM

Gloria Yi Data and AI Technical Development Manager, IBM

Building your hybrid multicloud: Why the foundation matters

Everyone accumulates data, from their smart phone to their Netflix viewing habits and social posts. Now, more than ever, data is almost universally recognised as being of significant value. As organisations seek to take advantage of their data from various sources - such as customer and patient data, product usage and data from the internet of things (IoT) like remote sensors - one thing is very clear. Data is only useful if it is integrated via a platform that makes it easy to consume and harness for insights.

This session explores options for building the architecture and platforms to sustain the demand for ingestion of data. Your data serves no purpose if it becomes trapped in artificial silos amongst different layers of infrastructure and cloud providers. Learn about the importance of building open platforms that enable you to take advantage of world leading software defined storage platforms and hybrid and multicloud management at a scale that was once thought impossible to deliver.

Speaker:

Damon Wynne Client Technical Manager, IBM

DataOps (data operations) is the orchestration of people, processes, and technology to rapidly deliver trusted, business-ready data to data citizens, operations, applications and artificial intelligence (AI). Discover how you can organise all your data into a business-ready foundation with built-in governance and protection. By automating data cataloguing, preparation and quality controls, you can deliver a self-service data pipeline designed to improve data scientist productivity. This automation also helps ensure the data that fuels your AI is secured.

IBM DataOps: Create a business-ready analytics foundation

IBM DataOps capabilities help create a business-ready analytics foundation by providing market-leading technology that works together with AI-enabled automation, infused governance, data protection, and a powerful knowledge catalogue to operationalise continuous, high-quality data across the business. Join this session to learn how IBM's DataOps capabilities can assist you with delivering business-ready data.

Speaker:

Sagar Kulkarni Data and AI Champion, IBM

Deliver test data for DevOps at the click of a button

Learn how to deliver test data to aid development at the click of a button, through the use of Database Virtualisation using Infosphere Virtual Data Pipeline and securing test data through Optim Data Privacy.

Speaker:

Hans Siebrand Hybrid Data Management Technical Sales Specialist, IBM

Unleashing business-ready data with Watson Knowledge Catalog

As organisations strive to make the leap to AI, how can they ensure they are using quality, governed, and compliant data to build their AI models? Is it even possible? In this session, you'll learn how IBM has brought about the unification of various governance capabilities, supporting cloud and on-premises structured and unstructured data. Join us for a discussion and demonstration of our next-generation data catalogue that infuses AI to automate governance and support regulation and quality, so you can rest assured the data you’re feeding your AI models is business-ready.

Speaker:

Felix Yong DataOps Specialist, IBM

Introducing smart data protection

As you aim to protect all types of data from sophisticated threats across diverse on-premises, hybrid, and public cloud environments, how do you simplify operations while complying with privacy requirements? Attend this session to learn about our smart data protection platform that offers actionable insights, real-time controls, and automated compliance support.

Paul Griffin Client Technical Professional, IBM Security, IBM

Analyse your data in smarter ways and empower your team to gain new insights and make more informed decisions. With AutoAI technology, you can automate the majority of the AI lifecycle, from data preparation to model creation, through to optimising operational explainability, bias mitigation and accuracy. Discover how you can simplify the AI lifecycle of preparing data and building, deploying and managing your models.

Build a machine learning model with the next generation AI automation

Learn how to rapidly automate the task of building, deploying and then integrating AI into business applications using IBM AutoAI. In this session, we’ll demonstrate the latest AI techniques to accelerate and optimise the creation of machine learning and data science workflows.

Speaker:

Keith Doan Enterprise Analytics Architect, IBM

Supercharge your customer experience with Watson Assistant

Supercharge your customer experience across their preferred channel (web, mobile, Slack, Facebook, voice and SMS). In this session we’ll demonstrate how to incorporate machine learning predictions into your digital assistant processes and make these available over web, voice and SMS channels.

Speaker:

Stuart Maclean Technical Sales, Watson, IBM

Operationalise a machine learning model with Watson OpenScale

In this session you'll learn how to operationalise your machine learning models using Watson OpenScale. We'll go through how OpenScale opens up the machine learning black box and how it enhances model transparency and explainability in real-time.

Speaker:

Nicholas Renotte Data Science and AI Specialist, IBM

Watson for contact centre insights

By the end of 2020, customer experience will have overtaken product and price as the key brand differentiator. Customers have more choices than ever – leading to three trends: sky-high customer expectations, struggling agents, and rising costs. Companies have adopted all sorts of strategies to lead the pack in customer experience, but there is one that is clearly winning today. Leading organisations are applying AI in customer service to deliver better customer experience, increase agent productivity and reduce contact centre costs. Join this session to learn how equipping your contact centre supervisors with Watson Discovery will allow them to gain actionable insights from calls, emails and chats so that they can properly align, resource, and prioritise your customer experience strategy.

Peter Elford Unstructured Data and AI Technical Specialist, IBM

Getting started with Kubeflow and open source machine learning platforms

IBM is one of the industries’ largest contributors to open source projects and recently, has invested significant resources to support Kubeflow, an open source machine learning toolkit that runs on top of Kubernetes. In this session, you’ll learn why open source platforms are a great entry point into enterprise grade data science and machine learning platforms, delving into an AI lab case study from a large telecommunications organisation running Kubeflow and the IBM Power System AC922 server (designed for Deep Learning and GPU accelerated analytics). Join this session to understand where to begin your AI platform journey and how to evolve it from experimental to mission-critical.

Ben Swinney AI Platform Specialist, IBM

While rethinking your business practices and workflows, consider applying prebuilt enterprise AI applications that speed up time to value across key domains, such as customer service, financial planning, risk management and IT operations. Discover how you can infuse AI into your workflows to predict and shape future outcomes, automate complex processes, and optimise your employees’ time.

RegTech: AI powered governance, risk and compliance

In today’s complex regulatory environment, companies must lower costs and deliver greater transparency to enhance and preserve client and stakeholder trust. As part of digital transformation, firms must understand regulatory compliance is no longer an acceptable minimum. They must proactively manage change to best practices in a constantly evolving market to win, serve, and retain customers. With the unique combination of technology and regulatory expertise, IBM enables institutions to make more risk-aware and timely decisions. We apply the latest advancements in AI, machine learning and automation to the risk and compliance process, increasing operational efficiency, accelerating insight and improving transparency. Greater oversight and understanding helps our clients preserve institutional trust and enhance value to their shareholders and customers alike.

Speaker:

Stephen Fox Governance Risk and Compliance Lead, Asia Pacific, IBM

Conquering the age of insights with AI-infused financial planning and analytics

As we enter a new era of finance transformation, forward-thinking businesses are implementing strategies focused on process automation, agility, transparency and data-driven decisions. Technologies such as augmented intelligence, predictive analytics and cloud are changing the way professionals work and increasing the value they bring to their organisation. Join us to find out how planning and analytics solutions with AI built in can transform and empower your teams and business.

Speakers:

Karen Hardie Senior Technical Sales Consultant, IBM

Kevin Jessop Lead Solutions Specialist, Performance Management Analytics Solutions, IBM

Frauds and scams in the new normal

Isolation has increased the adoption of digital strategies such as online banking which have been driven to new levels. The ability to find people at home at all hours has increased opportunities for global scammers. Find out how much has changed and how banks are protecting their customers.

Moderator:

Stephen Scheurmann RegTech Solutions Leader, IBM

Panellists:

Angus Stewart Financial Crime Management Lead, Asia Pacific, IBM

Owen Loefellechner Chief Safety and Security Officer, Bank of New Zealand

Chatbots and Virtual Assistants. Pitfalls to avoid. The why, the what and the how.

In this session, we discuss the mistakes we have seen organisations make when creating their own virtual assistants and how to avoid them. We also look at why you might want a chatbot in the first place (the answer is not as obvious as you might think) and how to take your first steps into this exciting new world of customer engagement.

Paul van der Linden Director, OutThought | AI Assistants

Modernise and simplify how you collect, organise and analyse your data within a multi-cloud platform - while unifying your AI models with the data they need. The combination of IBM’s proven framework, open platform and deep industry expertise can help you build a successful AI strategy, optimise talent and deploy AI capabilities at scale to help achieve the innovation, speed and agility your business needs.

Accelerate your journey to AI using IBM Cloud Pak for Data

Challenged with a multitude of technologies that are hampering collaborations between your business and technical teams? Struggling to find and access your corporate data for analytics and data science projects? In this session we’ll highlight our enterprise insights platform, IBM Cloud Pak for Data, and take you through the collaborative process and user experience for your data and business users. Watch as our Data Analysts search for the data they need and request access to that data, how Data Engineers fulfil those requests, and how Data Analysts and Data Scientists can collaborate together on data analytics projects.

Speaker:

Tim Brown Data and AI Solution Engineer, IBM

Ian Godsell Data and AI Analytics Architect, IBM

Taking the IBM Cloud to the orbital edge: Previewing IBM Cloud Satellite

There are many modern workloads - particularly those that supply data and AI intensive applications - that require the power and low latency of distributed compute and network resources but also benefit from the agility, speed and flexibility offered by cloud based services. Supporting these requirements can lead to inconsistencies between public cloud and on-premises environments, causing many enterprises difficulty in gaining visibility and control of applications that run across hybrid architectures. In this session, we'll be previewing some of IBM's latest technologies that will help you realise the benefits of hybrid architectures to deliver IBM Cloud services anywhere, as-a-service from a single pane of glass and controlled through the public cloud. See what it takes to run data and AI applications in their optimal location supported by low latency access to on-premises systems, local data processing and local data storage. This session will preview IBM Cloud Satellite and how it can support workloads critical to supporting the next wave of data and AI applications.

Speaker:

Andrew Assauw Distinguished IT Specialist, IBM Cloud and AI Solutions Software, IBM

ModelOps: DevOps for Machine Learning Models

The original intent of DevOps was to increase velocity and quality to delivery of applications by bringing automation, repeatable processes and stakeholder collaboration together. The original intent of DevOps can also be extended to Machine Learning Model delivery too. ModelOps describes how delivery can be automated using a defined process with Data Scientists, Data Engineers, and Model Engineers. Come, listen, and discuss how DevOps intersects Machine Learning Models at ModelOps.

Speaker:

Andrea C. Crawford IBM Distinguished Engineer, DevOps Garage Solution Engineering, IBM

Building the AI pipeline in your enterprise

AI solves very complex business tasks, but it does not have to be complex to implement - in any industry! AI Lab Services have a proven track-record of identifying the right service candidates for your Auto-AI Pipeline, and embedding them in high volume business transactions. Using a combination of industry-standard (open-source) libraries, and the IBM Cloud Pak for Data platform, we also have deep expertise in designing hybrid serverless patterns for cloud and on-prem components to deliver high-performance and highly-available API's.

Ross Davis Asia Pacific Architect, IBM