2020 Business Intelligence Summit
Embracing BI as an integral part of business success
30 - 31 Mar 2020Heritage, Auckland
- Super saver price $2499 + GST
- Super saver ends on 28 Jan
- Last minute price $2799 + GST
- 30 - 31 Mar 2020
- Super saver price from $699 + GST
- Super saver ends on 28 Jan
- Last minute price from $899 + GST
- 1 Apr 2020
- Download Brochure
Registration and coffee
Opening remarks from the Chair
Development of BI as a business function
Opening Address: Development of the BI landscape – Is it “just” a tool or has it developed to a business function?
- Data literacy - analysis and analysts moving beyond creating reports to providing decisions
- Data security - reviewing, understanding and implementing concepts from Office of the Privacy Commissioner, Privacy by Design and other sources of leading thought to design privacy, confidentiality and security
- Data availability - Emerging themes of data virtualisation and data fabrics as the hype cycle for cloud adoption
Chris Collins , Manager of the Data Office, AIA NZ
Case study: Traditional BI vs. modern BI – what works best and why?
- Defining traditional BI and modern BI
- Why traditional BI needs to evolve - problems businesses face
- How can modern BI solve these problems?
Nakul Gowdra, Tech Lead – Data Engineering, Mercury
Case study: Efficient delivery of data led insights
- Advanced analytics to get a better understanding of customers so they can be targeted with relevant offers
- Making smart and business crucial decisions by linking customer experience to technology investments
Anshuman Banerjee, Chapter Lead, Business Insights & Advanced Analytics, Spark New Zealand
Case Study: Investigating the cultural and digital transformation measures required for successful change management
- Understanding the measures required to create active and effective environments to support change and to make your business future proof
- Creating the workforce capacity and capability to deliver a common skill-level by exploring a variety of training opportunities
- Looking into required fundamental leadership skills to enable change and success in a fast-moving and agile environment
Philip Hanson, Platform Owner - Analytics and Marketing platforms, ASB Bank
Case study: Journey to the successful integration of BI
- "Better Never Stops!" - Managing for transition, transformation and change at Aspire2
- Will a BI platform solve all our problems? Why the traditional approach wasn't going to work for Aspire2 - and probably won't for you either
- The challenges of building Trust, Quality and Empowerment
- Patterns, tools and platforms to solve for problems common to our business, and all others like it
- Doing it all on a dime! – achieving change with minimal and existing resources
- How is our strategy paying off for us?
Pieter Lootsma, Business Intelligence Manager, Aspire2 Group
Case study: Moving towards a data-driven strategy
- What underlying factors needed to be considered to transform a business strategy?
- What subsequent resources and measures are required for successful implementation?
- Explore how a data-driven strategy can support process optimisation and automation
Offline and Online Data Management
Data security – how to secure your data from emerging cybersecurity risks
- Exploring the need of data security - what data needs to be secured and why?
- How to mitigate the security challenge of moving big data offline vs. online – what are the regulatory requirements and what is most suitable for your business?
- Is your business ideally equipped for potential cyber threats?
Chetna Chaudhari, Lead Data Engineer, Kotahi Logistics LP Ltd
Case study: Increasing data quality throughout the enterprise and efficiency of internal processes
- Ensuring that the existing data is fit for purpose
- Reviewing techniques and processes for data quality management
- To what extent can predictions, reports and decisions be made based on trusted data?
- Winning hearts and minds through sustained business change management
Kalyn De Castro, Data Quality Manager, FMG (Farmers Mutual Group)
What does a data scientist do in the BI and Analytics team?
- How can data scientists help achieve business success in a agile environment?
- How to build end-to-end data solution?
- Looking into best practice of internal customer engagement
Dr Kristy Su, Senior Data Scientist, New Zealand Post
Summary remarks from the Chair & Networking Drinks
Welcome back from the Chair
How will the future of BI look like with emerging technologies disrupting the industry?
- Interrelationship of emerging technologies e.g. advanced AI & IoT devices and BI – exploring influence of technology on architecture, while complying to increased regulation
- Digital fairness – imbalance of access due to imbalance of resources?
- Forecasting the fast-paced tech and digital environment to firstly develop a social consensus and most importantly increase societal acceptance
Penelope Rae, Business Director, Beca
Building an effective BI strategy with your team
- Funding, prioritisation and escalation
- How users engage with BI and processes to ensure continuous delivery
- Reliable secure data for reporting and analytics
- Creating a vision for your BI team
- Personal growth and development of your people
- Building a high performing, driven team that works together
- Diving into Data Science
Dave Richards, Head of Business Intelligence, St John New Zealand
Case study: Visualising data for predictive analytics
- What are the latest technologies, trends and developments in data virtualisation?
- Defining metrics that are relevant to build a dashboard
- Enabling an increase in interactive communication through dashboards
- Learn how to design and tailor your dashboard for significant target groups
Case Study: Building an Agile environment through data vault modeling
- Looking at different stages of data vault automation: design, build and management
- Delivering resource efficiency through data vault automation
- Exploring the benefits of data vault modeling architecture compared to traditional data warehouse modeling
Case study: Strategy to merge and integrate data from different systems
- Highlighting the benefits of successful data merging including increased self-service BI, supporting metadata management, data lineage and data governance
- Understanding platform architecture for data integration – system design, main- and subcomponents, standardisation and its implications
- Integration failure – tips to discover wrongly and untrustworthy data early and explore opportunities to reduce failure
- Using modern approaches to enhance data to give users a more comprehensive perspective
- Creating and maintaining a centralised API for small bespoke solutions with limited or non-existent integration support
Sofia Ng , Business Intelligence Lead, Port Otago
Future Outlook of Emerging Technologies and BI
Exploring the interrelationship between: Agile, BI & DevOps
- Exploring Agile, Business Intelligence/Insights, DevOps
- Outlining best practices, challenges and opportunities
- Linking all three together to provide Enterprise BI capability
Stuart Pattison, Business Intelligence Lead, AIA NZ
Looking into how AI can impact your business operation
- Understand how to enhance systematic knowledge management and digital collaboration to create the fundamentals for deploying AI
- Training to enable digital workplace
- Customisation of digital workplace and collaboration solutions
- AI build upon strategically defined knowledge structures
- Best practices of computer vision, automation, cognitive computing and machine learning techniques e.g. deep learning, real-time style transfer
Kitty Ling , Senior Manager Analytics Transformation, Woolworths NZ
Case Study: Looking at realistic and cost-effective AI-driven analytics
- What is doable and affordable with restricted budget? In what ways can AI benefit your operations?
- What are the key prerequisites? Is your business ideally equipped for AI deployment?
- Defining an AI analytics roadmap for your business
Closing remarks from the Chair and end of conference