EDITOR ’ S QUESTION how to protect it – whether through masking , tagging , anonymisation or other processes . The next step is to implement a governance layer around features such as low-level security and access control .
Organisations must be clear about what business outcomes they are expecting from their generative AI applications . This provides the foundation to determine the data required : structured / unstructured and if this data is available internally or needs to be sourced externally . If the data is available internally they may need to build additional pipelines to bring the data into the enterprise data platform or get it from an external source or from the Snowflake marketplace from one of the data providers .
External data inputs can help organisations get a 360 view of the business and help build actionable insights . For example : if a retailer wants to expand its presence and open new outlets , what more can it do besides turning to the internal data sources and performance of its current stores ? The business could look at footfall traffic from telecommunications operators to parse data that covers age groups too and map this data using geospatial coordinates to determine the location of their new store . Training AI / ML models with these comprehensive datasets helps provide better business context , improves effectiveness and delivers differentiated business outcomes .
How has Snowflake been helping local organisations to unlock the value of data ?
Snowflake ’ s unified platform streamlines complexity and reduces costs . Canva , the popular graphic
design platform with over 150 million monthly active users worldwide , was able to build better AI products faster , helping more users design with ease . Canva also leveraged Snowflake to bolster organisationwide decision-making – including improving feature launches , optimising marketing spending , and helping executives build more informed strategies .
Meanwhile , global communications powerhouse Zoom uses Snowflake ’ s AI Data Cloud to support internal business functions and develop customer insights . By combining Snowflake Cortex AI and Streamlit , Zoom can utilise pre-trained LLMs to speed up app building . Zoom ’ s teams were then empowered with easy and swift access to helpful answers , facilitating AI democratisation without compromising on data security and governance .
Another example is Spark New Zealand . Using Snowflake to integrate AI and ML , one of New Zealand ’ s largest telecommunications and digital services providers aligned key processes across its organisation , from workforce management to supply chain . Their proprietary platform , BRAIN , utilises ML models to deliver precise messaging to customers and has improved the performance of marketing campaigns by 20 times . This allows Spark to predict customer needs with higher accuracy , driving greater ROI and operational efficiency .
Apart from that , solutions like Snowflake Horizon make discovery and access to critical data assets more seamless , while maintaining privacy compliance . Innovations like the Cortex suite , meanwhile , ensure access to data is paired with nocode interfaces that simplify AI development while upholding responsible AI . p
www . intelligentcio . com INTELLIGENTCIO APAC 35