Data & Analytics

• 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. 

• Details to follow…

• Hub and Spoke model
• Data democratization through self service data platform
• People & Data

• 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 

• 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

• 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 

• The amount of data is exploding, advanced technology are available at low-costs and digital-first is the new mentality. This will alter the way entire industries operate. Your ability to turn quickly turn data into value – isn’t a luxury anymore, you need to transform and become the digital and data-driven leader of tomorrow. 
• Within ABN AMRO we doubled down on our data & analytics journey to reinvent the customer experience, accelerate the substantiality shift and build tomorrow’s data-driven and agile foundation. With re-usable capabilities, an inspiring data strategy they forged a strong connection with business initiatives and got the organisation to rally behind data. 
• Get inspired to rethink your own data journey. 

• Discussing routes to faster and easier ways of monitoring high loads of granular data  
• How recent technological advancements in cloud-native storage can help  
• The potentials of the next generation of data 

• Details to follow…

• 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 

This insightful solo presentation will dive into how data must be treated within the Enterprise so that, all forms of Advanced Analytics to become accepted, trusted and available. From incorporating Data into corporate strategy drivers to making it a tangible and valued asset, Anwar will present how to ensure that Data, Analytics & Insights are valued by decision makers in every organisation.

• Adopting a basic data approach, methodology, framework and culture
• Helping the organisation realise the tangible value of its data and data quality
• Educating the workforce and embedding a data-driven culture
• A Business Strategy Roadmap with a Data Strategy embedded into the core of the organisation

• Understanding the difference between reporting and analysis – one is not the other  
• 3 key tips to ensure your data can improve results  
• Framing data analysis around your business outcomes 

• 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

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

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