Day 2 - 24 November 2021



Registration Opens



Data & Analytics: Chairperson’s Welcome



Building a holistic city-wide data ecosystem

  • How organizations can take a 4-pronged approach to ensure they do not miss out any key component: 
  • Data Governance, Data Infrastructure, Public-Private Partnerships and most importantly Use Case Development and Value Generation. 



Predicting trends with Natural Language Processing

  • Examining some use cases of NLP applications including spam detection, translation, chatbots & social media analysis 
  • Filling the gap between human communication and computer understanding 



The 7 Challenges introducing Data Science at the Fraud & Risk department @ bol.com

  • Details to follow…



Top traits of world-class data management

  • Where is your data management strategy falling short? 
  • How to ensure the agility, resiliency and availability of your data is up to scratch 
  • Aligning your data to your business goals 


Networking Break



Panel: Data analytics for intelligent decision making

  • Identifying target-rich, high-value data that can be used to generate business intelligence 
  • How to leverage data and analytics to optimize every decision, process and action 
  • Real time data analytics in practice – examples of how data is creating business efficiency and revolutionising working practices



The missing link: using RPA for unstructured data

  • How using robots can manage and move your data from unstructured to structures 
  • Insights into use of Optical Character Recognition and Natural Language Recognition 
  • Navigating human and non-human errors 



Making data accessible for everyone – Augmented analytics

  • Automating for ease – development, management and deployment 
  • Using data-driven insights to determine business strategy 
  • How augmented analytics can free up resource to focus on research that machines can’t yet support 



Data Solution Presentation

  • Details to follow… 


Networking Break



Afternoon Keynote: Working smarter not harder – Transforming your business post-pandemic

  • Why you should be digitalising your business processes 
  • Keeping your workforce online in the ‘new normal’ 
  • Increase predictability and performance through improved communication



Panel: Making sense of your data

  • Resource management – Utilising your old data and storage 
  • Identifying and breaking down silos 
  • Tips for extending business capability of your data projects and delivering insights 
  • Keeping your data lakes clear and navigable 



Data as a service

  • Improve the agility of your data workload and increase its reliability 
  • How using DaaS can maximise functionality and flexibility 



Data Solution Presentation 2

  • To follow soon.. 



Anil Panda

Data Scientist & ML Engineer - Risk & Pricing


Associated Talks:

03:30PM - Day 2

View Solving a cold start problem in NLP with Active Learning

11:20AM - Day 1

View Panel: Responsible delivery – the ethics of AI

View Full Info

Solving a cold start problem in NLP with Active Learning

  • One of the key challenges with creating a supervised machine learning system is the availability of labelled data. Scenarios where labelled data is not available, we can use human domain knowledge along with Active Learning to create labelled data and use that to train a ML model
  •  In this talk, we can see how Active Learning was used within ING to create initial models for early warning detection. We used active learning to create a labelled dataset using a combination of sampling methods
  • The final models thus created were able to meet the KPI’s and are used in production environment as well
. Anil Panda, Data Scientist & ML Engineer - Risk & Pricing, ING



Building a scaleable data platform

  • What are the main things to consider when building a data platform in 2021? 
  • Understanding modularization – finding the right solution for your project 



Kick-starting your next data science project

  • How data can help solve your immediate business processes 
  • Moving from proof-of-concept to pilot stage 
  • Where to go from here? 


End of Conference