Three key takeaways from my presentation at Garter Data & Analytics Summit 2022, Mumbai & Gartner keynotes.

I have engaged with hundreds of enterprises and have seen some amazing transformations, outcomes & innovations. Yet, while technology has been evolving rapidly, the foundational challenges remain the same.  If there are just three focus areas that can guarantee success, these would be 

Data – We have seen a need for real-time vs. batch, the complexity of integrating data sources almost triple, adapting to the change in the source system as a de-facto design. We have seen monumental failure with the data lake approach of a single repository. The Data Fabric architecture provides a practical approach that doesn’t require a significant transformation or large investment and focuses on the core of all integration challenges i.e., metadata consolidation. When Machine Learning is applied to this consolidated metadata, it provides a magical view of data relationships, usage patterns, data quality, and profile. Data fabric accelerates data consumption, provides data governance and protection mechanism adaptable to change in the eco-system, and facilitates data sharing.

2. Talent – How fast you and your team can “unlearn” is the most critical aspect of learning in recent times. Community-based learning in the enterprise is vital to keep pace with the changes and build a skill that can help you leverage data. Tools like AutoAI is a great starting point for learning ML/AI for someone new to the field.

3. Trust is built when we put the user in the pilot position and provide a cockpit that offers access to all the relevant information. TrustWorthyAI is an initiative toward ensuring we don’t get into a machine-human conflict, and the model makes a better decision by removing some of the inherited bias.

In terms of the Gartner keynotes themselves, the three key takeaway was 

1. Gartner claimed that by 2030, synthetic data would completely overshadow real data in AI models. 
2. De-emphasis on big data and finally acknowledge small data can equally contribute to success if appropriately harnessed.
3. Governance was emphasised as a way of working rather than control; however, personally, I was a bit disappointed it came late in the framework.