Every day, we create roughly 2.5 quintillion bytes of data, platforms like snowflake supports data analysis at almost any scale, with the ability to process data from structured and semi-structured sources. As a result, users can compute with any business data or workload, using standard sQL instead of complex programming languages.
We spoke to Vimal Venkatram, Country Manager, Snowflake to understand how snowflake’s platform allows customers to get the most out of their data.
How do Data analytics help banking and other financial services?
Banking, financial services, and insurance (BFSI) are some of the sectors most heavily invested in data management related technologies. Today, financial institutions are compelled to deploy analytics and data-driven capabilities to increase growth and profitability, lower costs, improve efficiencies, drive digital transformation, and support risk and regulatory compliance priorities.
With data analytics, BFSIs can improve customer targeting, risk assessment strategies, as well as provide customised solutions to current customers.
Personalised experience: Personalisation has come to be expected in every bank-customer relationship. With access to a massive volume of consumer data, banks and financial institutions have the opportunity to deliver a specialised experience to customers.
For a personalisation strategy to be successful, it is fundamental to have full visibility into customer interactions in real-time. With the help of cloud platforms, businesses can house all types of data such as clickstream, transactional, and third-party data in one secure place.
This story is from the June 2021 edition of PCQuest.
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This story is from the June 2021 edition of PCQuest.
Start your 7-day Magzter GOLD free trial to access thousands of curated premium stories, and 8,500+ magazines and newspapers.
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