Data storage solutions aid the firm to store data in the cloud or data servers efficiently with ease of retrieval and management. Data storage solutions also ensure the security of the data, ensuring that only authorized personnel can access and amend data. The solution resolves upscaling data access and storage issues for firms. The solution allows integration of data into a data lake and enables data compression, resulting in 80% reduction of data storage as compared to traditional data storage. The solution enables faster processing and data recollection, allowing the firm to operate swiftly. Find out more at www.ey.com/sg/fintechhub. For enquiries, contact us via email at fintech@sg.ey.com.

1. Scaling up data access and storage without
scaling up costs
Case study
Context:
A top Indian bank was faced with a large
increase in its data warehouse volumes
because of a number of reasons: post-
acquisition, organic growth in customer base
and increasing data from online channel. Data
growth was set to double over the next few
years, and data compression within a ‘data
lake’ was an option for cost-effective archival.
However, the bank sought to ensure fast
access to active warehouse data, while
ensuring secure access to compressed data in
parallel.
Recommended configuration:
• To demonstrate the platform’s capabilities,
data was loaded to a Hive-staging table.
Vendor solution was deployed to join the
Hive-staging table with existing data
warehouse tables using sample queries.
• A sample interface was created to generate
account statements based on consuming
data from both data sources.
• The solution included advanced data
capabilities such as compression,
encryption through customized functions
and in-memory parallel processing.
Client impact:
• Migration to a data lake plus data
compression enabled an 80% reduction in
data storage.
• Data queries ranged from 2 to 30 seconds
depending on the query complexity.
• It resulted in ease of deployment, fast
performance and scalability.
Contact us
Challenges faced by institutions
Inaccurate data extraction from
legacy systems
Resource-intensive reporting
Isolated data sources Lack of data storage infrastructure
Data segregation and security
issues
Advanced analytics processing
requirements and complexities
Varun Mittal
EY Global Emerging Markets FinTech
Leader
varun.mittal@sg.ey.com
Futureproofing institutions for the big data revolution
Data unification
Real time
High-speed
processing
Storage
optimization
Minimum data
replication
Machine
learning and AI
Leading-edge tech capabilities
Transaction
system or
CRM data
Online reviews
or social media
data
Data
analytics
Regulatory
reporting
Online
applications
Vendor Solution: Single view Data visualization On cloud On premise
Data lake for
structured and
unstructured
data
Different kinds of API exposed by
vendor/organization
Real time
(non-API based
Kafka
Database
Comma-
separated
values
(CSV) files
With data
lake
Skip data lake Data
warehouse
</> REST API
Website: www.ey.com/sg/fintechhub
Email: fintech@sg.ey.com
Sahil Gupta
EY ASEAN FinTech Manager
sahil.gupta@sg.ey.com

2. EY | Assurance | Tax | Transactions | Advisory
About EY
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on our promises to all of our stakeholders. In so doing, we play a
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more, of the member firms of Ernst & Young Global Limited, each
of which is a separate legal entity. Ernst & Young Global Limited,
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clients. For more information about our organization, please visit
ey.com.
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All Rights Reserved.
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intended to be relied upon as accounting, tax or other professional advice. Please
refer to your advisors for specific advice.
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