APAC Data Analytics Day (Online)

    Theme – Drive Pervasive Outcomes using Data

    AI, Machine Learning and Deep Learning is Re-inventing.
    Don’t get left behind.

    Data analytics is no longer the luxury of organizations with large budgets that can accommodate roving teams of analysts and data scientists. Every organization, no matter the size or industry, deserves a data analytics capability. Thanks to a convergence of technology and market forces, that’s exactly what’s happening.

    At APAC Data Analytics Summit, we will be learning the latest and innovations in Data Analytics technologies, processes and tools.

    Best practices while attending online conference:

    • Login to your system with the login detail 10 minutes prior to the start time
    • Should be connected to a good network to avoid interruptions.
    • Should be at a quiet place while taking your session.
    • Ensure all other windows are closed and no application is running. This will ensure good audio and video quality
    • Mute yourself if not expected to speak
    • Do ask the question via chat box to keep the session lively.
    • You can Ask questions
    Paul Macey
    Specialist Solution Architect, Big Data, Analytics & Insights, Australia & New Zealand
    Paul advises and supports customers looking to enable and gain insights from their data across the ANZ region. For over 20 years, Paul has been helping organisations including ANZ, Telstra, NBN and Australia Post to transform, reinvent, and deliver true value from their data. Paul is deeply passionate about the role technology plays in helping customers to innovate and transform, securely and with governance. AWS services are trusted by more than a million active customers around the world – including the fastest growing startups, largest enterprises, and leading government agencies – to power their infrastructure, make them more agile, and lower costs
    Craig Lawton
    IOT & Smart Cities Specialist, A/NZ Public Sector
    As a Solutions Architect specializing in public-sector IoT and Smart Cities initiatives across Australia and New Zealand, Craig Lawton is sought after by Governments at all levels to provide insights into the future of cities and how technology can improve the quality of life for citizens. Craig has worked across many organizations in both the public and private sectors for over 20 years. He first realised how revolutionary cloud computing would be whilst writing a book on cloud adoption that ultimately transformed into the popular blog, coffeescroll.com. The next big transformation will bring together big data, IoT and artificial intelligence in new and innovative ways. And it’s happening right now. Craig has held roles at organisations including Coles, NAB, Telstra, Thomson Reuters & Department of Justice, Victoria.
    Michaela Shea
    Senior Manager Data and Analytics Transformation
    Cam Potter
    Managing Director
    Cam is a seasoned CEO and founder with a demonstrated history of working in the computer software industry. He has experience with machine learning platform design, database management, data analytics, and biotechnology. Cam is a strong business development professional with a Bachelor’s degree in computer science and Master's degree focused in International Business, Trade and Commerce. In 2006 he founded Brooklyn Dynamics. Brooklyn Dynamics develops custom analytical software. They are making a difference in multiple industries and fields including; Banking Finance & Economics, Professional & Amateur Sports, Logistics, Tourism, Communication, Healthcare, Defence and Wildlife Resources. Brooklyn Dynamics’ focus is to provide agile solutions that accumulate and centralise data, and then create insights via analytics and modelling allowing prompt decision making. They seek to achieve this via efficiency, adaptive and innovative technology, integrity and meticulous quality control.
    Siva Anintheneni
    Independent Consultant
    Pankaj Gabale
    Data Scientist
    Pankaj is a Data scientist at EY's Data and Analytics practice based in Melbourne. He has closely worked with organizations designing and developing a machine learning approach. He has work experience with leading industries in with Banking, Sports & Entertainment, IT, Health and Telecommunications. He has participated and won several data science competitions like Melbourne Datathon, Melbourne Business School Analytics Datathon, EY global data science challenge. He loves sports and he is a big fan of English premier league team Liverpool.
    Sarath Nair
    Lead Consultant
    Sarath is passionate about unlocking the possibilities hidden in the data assets of organisations. His experience in data & analytics range from strategy engagements to solution delivery & operationalisation. He is a skilled analytics translator, proficient in bridging the gap between business stakeholders and technologists, and has consulted for clients from diverse industries in India, USA and Australia.
    Raja Akkireddi
    Senior Data Scientist
    Raj is a senior Data Scientist in Melbourne who has worked extensively across the Finance, Telecommunication, FMCG, Gambling and Not for profit sector. He specializes in the are of predictive modelling and the ethics frameworks in using these models. In his spare time, he still works as a university educator who still plays cricket and football, I also run volunteer tutoring programs in Collingwood and Footscray and work actively for a few charities in Melbourne these include Liberty Victoria and The Human Rights and Arts Film Festival
    Kurian George
    Executive Director & Board Member
    Kurian is a strategic Information Governance & Data Analytics leader and advisor, uplifting organisational capabilities for creating and sustaining competitive advantage for Businesses. He commenced his career at the turn of the millennium, evolving through tactical Management of Projects (certified PMP®) enabling decision support through data, direction of Transformation Programs (certified PgMP®) including Data migration and Strategic Portfolio Investments (certified PfMP®) in building Business Intelligence & Analytics capabilities. Kurian has established Data Governance and Analytics practices with continuing Product Lifecycle and Service Delivery Management, enabling Organisational Change through professional services across industries, utilising Scaled Agile Framework and is a Certified Scrum Master (CSM). An Executive MBA from Melbourne Business School has equipped Kurian with commercial acumen for Business strategy & execution. As an Executive Director and a Board member of the Melbourne Chapter of Project Management Institute, an NFP with around 1600 professional members, Kurian is a visionary devising chapter strategy and defining operations utilising data & analytics. He is passionate about Information Practice building and uplifting Enterprise governance capability by enabling organisations to leverage information assets for creating insights and thereby developing a competitive advantage in this digital age.
    Suresh Karanam
    Data Analytics & AI Practice Head – Australia & NZ
    Zak Khan
    Forecasting Data, Analytics & Systems
    Zak Khan is an accomplished data analytics strategist and thought leader with deep industry experiences. He has held diverse leadership roles across many facets of Information Management domain including data strategy formulation, building data quality and governance capabilities and operations management in Data warehousing, business intelligence & advanced analytics. Zak has global consulting experiences and assisted clients across Telecommunications, Utilities and Financial services sectors to uplift data analytics capabilities in order to solve complex business problems and deliver business outcome.
    Dr John Brudenell
    Chief Data Officer (CDO)
    John is currently the Chief Data Officer (CDO) at Zetaris Pty Ltd, which is a data management, analytics software company with deep expertise in data analytics, information management, virtual data warehousing and ‘big data’ technologies. In this role, John runs the data strategy, data management and data science practice in Australia and overseas for Zetaris’ clients.
    Amin Sadri
    Senior Data Scientist
    Amin is a Ph.D. qualified data scientist with years of commercial experience and a strong mathematical background who has won several national and international mathematics awards. With years of professional experience, Amin has been working on different types of data including time-series, spatio-temporal data (trajectories & GPS), card transaction data, graphs (networks), customer data, bank data, text logs, and sensor data. Currently, he is working at ANZ as a senior data scientist.
    Dr William Yeoh
    Associate Professor
    Dr William Yeoh is an associate professor at Deakin University. He is a leading researcher in business intelligence and analytics field. His research has appeared in high-tier journals and the top five information systems conferences. He is the Editor-in-Chief Emeritus of the International Journal of Business Intelligence Research. His work has been recognised with several prestigious awards, including the ICT Educator of the Year Gold Award (awarded by the Australian Computer Society ACS), internationally-competitive IBM Faculty Awards, Deakin's Vice-Chancellor Award, and Deakin Faculty Excellence in Research Award.
    Deepak Mane
    Enterprise Solution Architect
    Deepak S. Mane is a enterprise solution architect in Artificial Intelligence and Data Science domain at Tata consultancy Services . In his previous role he was Scientific Officer at Tata Research Fundamental Research (TIFR). He has published 12 papers in Conference Seminars , and has been conducting Seminar/workshop at various colleges in Maharashtra and MP under AIP/FDP activities-TCS. He's also a mentor for KreSIT, Indian Institute of Technology-Mumbai. He is currently pursuing research in Cloud computing, Performance Management, Disaster Recovery and Capacity management.
    Phil Watt
    Dr Champ Mendis
    Chief Data Scientist
    Champ Mendis is the Chief Data Scientist of Triple A Super, an adjunct lecturer, Charles Sturt University, Hony Assistant Secretary, IEEE VIC/TAS Section. He has more than 10 years of experience working in Artificial Intelligence & Machine Learning, Information Security and Computer Information Systems. He has worked in several industries, including Finance, Defence, Education, Transport, Telecom, Construction and Insurance. He had the opportunity to work for organizations such as Colmar Brunton, University of Melbourne, ACTU, DST (formerly DSTO), University of Sydney and ARRB. He holds PhD in Computing and Information Systems from University of Melbourne and was a member of one of the best research groups in AI in Australia. In his spare time, he plays Table Tennis and Chess, do cycling.

    Machine learning technologies are quickly transforming almost every sphere of our lives. From how we communicate to the means we use for transportation, we seem to be getting increasingly addicted to them. With these rapid advancements, massive amounts of talent and resources are dedicated to accelerating the growth of the technologies. Implementing open-source machine learning stack gives the organization more eyes for bug fixes and a wider set of features to cater to their machine learning requirements but at the same time organizations are tackling data security and access control regulations. While Open-source stack is preferred in many large organizations around the world, there is some serious decision making associated with it.

    Machine learning models are being increasingly used to make decisions that affect people’s lives. To paraphrase Uncle Ben from the Spiderman comics (even though I am a DC fan) “with great power comes great responsibility”, this is true as the models that we build can adversely or favourly affect demography’s of a population. So, to ensure that the model predictions are fair and not discriminating we need to ensure our models do not contain an inherent bias by those who design them.
    In my presentation I look to explore the idea of inherent model bias and potential strategems to tackle this issue.

    With a mission to become truly data driven, companies make significant investment in establishing data analytics platforms but many of them fail to realise the full potential due to poorly executed strategy underpinned by ineffective organisation design. In order to embed data analytics culture at the heart of the organisation, the importance of fit-for-purpose organisational model cannot be overlooked. How do you source, retain and deploy talent? Should you go with centralised, decentralised or hybrid model? How do you build a COE to that can maximise knowledge sharing, yet operate effectively to deliver value?
    This talk helps you explore what type of model would be most effective for your organisation and how best to implement them.

    Unlike typical software, Machine Learning applications do not have straightforward rules and usually act as a black box. Lack of explainability and interpretability reduces the trust of the product owners, legal counsels, and non-technical end-users. This talk helps you to understand the importance of interpretability and the trade-offs between interpretability and model accuracy among various machine learning models. It gives you some ideas to make machine learning more transparent and less of a black box.


    The Data Fabric’s automated data engineering provides the business with the mechanisms to manage sparse data sources so it can create an integrated information and analytics Virtual Data Platform, and agile business self-service while guaranteeing 100% data quality.
    For all intent and purpose, the ‘Virtual Data’ Platform (Data Fabric) refers to the set of data objects, including business entity types and business rules, that represent a Conceptual ‘Target’ Business Data Model (schema), which exist in memory within the Data Fabric Platform, and may or may not be persisted in a physical repository or a Virtual Data Warehouse (VDW). Once the Single View process applies all data integrity and data quality rules, the data objects are available to be accessed by the end-users and consumer applications directly from the Data Fabric Platform. This presentation explains a process that allows for agile business self-service to exploit business intelligence tools such as Qlik Sense, PowerBI, Tableau, MicroStrategy, etc., while providing for data provenance and data lineage as it relates to self-service.

    How to identify organisational needs. How to find the right candidate pool. Budgeting correctly for staff. Personalising training so it WORKS for everyone. Empowering and trusting in staff. Making sure everyone is a committed team member and has "skin in the game". (Important for retention). Various other facets of retaining staff, and building effective teams.Data Analytics Talent: Recruiting, Hiring, Organizing, Training and Retaining

    Many big data and advanced analytics investments fail to deliver significant and lasting benefits. Technology is rarely the issue. O’Reilly recently delivered the results of their study on AI adoption in the enterprise in 2020. Culture, skills gap and data quality as the as the biggest obstacles to businesses leveraging value from their data.

    Most large companies are incredibly well-placed to generate significant competitive advantage from their data. They’re sitting on a wealth of data; they have talented analysts and scientists, shelfware galore and plenty of pain points to work on. So why aren’t they generating success?

    AGL has embarked on an aggressive data and analytics transformation and is managing the significant change through four levers:
    • Mindset – shifting the collective mindset of the entire organisation to embrace data and analytics in decision making focusing on building executive sponsorship, re-aligning strategic imperative and developing new organisational metrics
    • Skillset – uplifting capabilities in technical expertise, data literacy and story-telling, and data driven leadership across the organisation through a purpose-built learning platform, guilds and career mapping
    • Toolset – demonstrating fast value through ‘activation’ of use-cases and initiatives requires a new model of engagement between technology and the business; this lever is the most difficult, but wins over the most sceptical of executives and is critical to success if it is planned and not left to chance
    • Dataset – embedding pragmatic data governance and stewardship that balances data privacy and security while not tying up data in red tape and bureaucracy.

    I’ve led the change in similar programs at Suncorp, NAB and now AGL. I can talk to why and how to do this and what the results are.

    - Building a winning culture
    - Stimulating the collaborative culture with enough opportunities to socialize and strengthen relationships
    - Getting away from Top Down hierarchical management approach to more equal footing accountability model.
    - Everybody takes ownership of the work and knows how that will contribute to the bigger team success.
    - Working style is more entrepreneurial and has continuous improvement.

    Realising quick and tangible return on analytics investments is critical to foster a thriving analytics culture. Ensuring the analytics strategy includes a value-driven, transparent and flexible roadmap of prioritised business outcomes rather than simply a technology timeline can be key to a successful analytics transformation.

    The talk introduces the value-oriented approach we use towards preparing actionable, outcome-focused road-maps and improving the ‘speed to insights’ by realising the outcomes incrementally and iteratively. The approach focuses on adopting a ‘right investment for right outcome’ approach and agile ways of working that can reassure the executive sponsors that business outcomes are given priority with minimal technical debt. Furthermore, the talk also provides an overview of how we have digitised the prioritisation and planning process to support, expedite and add flexibility to the analytics roadmap.

    Data Science is ubiquitous to such an extent, that organisations and citizens are both going to benefit from the sheer possibility of unravelling hidden insights across the business processes. On the other hand, embedding Machine Learning in all that the businesses do by simplifying the implementation is essential to its success. With all the hype surrounding this topic, it is vital that the latest trends driving this area are adopted by organisations and citizens alike with increase in productivity as the key focus.

    Artificial intelligence and Roboticsare hardly new,but the
    technologies have progressed substantially inrecent years. Advances
    in machine learning techniques,improvements in sensors and
    ever-greater computingpower have helped create a new generation of
    hardwareand software robots with practical applications in
    nearlyevery industry sector, especially in Banking and Financial
    sector.At present, artificial Intelligence (AI) technologies are
    increasingly being applied in the banking industry, mainly toward
    knowledge management, identity authentication, market analysis,
    customer relationship management, anti-money laundering, and risk

    But there are major challenges to decide/choose right architecture
    strategy for different application This presentation intends to talk
    about differnt architecture principles of AI&Robotics in Banking
    sector .

    In this talk, Phil will discuss tactical versus strategic data engineering, the importance of DataOps, matching the needs of data consumers with the outputs of data engineering and how to align with governance, risk, security and compliance needs of the business.

    Major problems currently exist in the data world! Centralised data management based on physicalisation has not worked. Dumping all data into a traditional Data Lake has not worked and has caused more problems than it purports to solve, including data management issues associated with data currency, synchronisation, security and data integration to name a few. The development of a new type of data platform, known as a Data Fabric, based on analytical data virtualisation, together with a systematic approach to data management overcomes these problems.

    For a long-lasting, flexible, agile and ‘future-proofed’ MDM solution the processes need to be built around the data; this is data-driven. This presentation explains how a Data Fabric-based architecture in the cloud or on-prem that allows the creation of ‘Virtual Data Warehouses’ enabling true analytical data virtualisation and ‘future-proofing’ your MDM solution.

    Customers of Triple A Super (TAS) are mainly retirees yearning to have a considerable income after retirement. They select Self-Managed Super Funds (SMSFs) and Fund Advisers, who can provide a good return on investment for a nominal cost. The Trust Deeds forms an integral part of documentation to be processed in SMSF Administration. It is an essential requirement for Trust Deeds to be compliant with SMSF legal process. Here we explore AI & ML based approach in verifying Trust Deed Compliance in order to expedite the SMSF administration process.

    Data & Analytics Leaders should consider how effective and useful data lakes will be in their overall data and analytics strategies. The key is to build data lakes for specific requirements of key user groups or analytics use cases. Failures can be avoided by reviewing the expectations of business units, availability of skills and infrastructure capabilities of the organisation.

    Data is a now a strategic asset for every organisation. However, siloed legacy systems, lack of data security and data governance are holding many organisations back. In this session will discuss the common challenges being experienced by organisations across the world and how, using AWS cloud, organisations can gain rich insights from data that is centralised, secured, and has governance.

    Standard - One Day Ticket
    Till 29 April
    AUD 349
    Standard - Two Day Ticket
    Till 29 April
    AUD 698
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    1 Comment
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      Samuel Beeny

      What other speakers are attending please

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