re-engineering data landscape on snowflake for leading us
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Re-Engineering Data Landscape on Snowflake for Leading US-basedCoffee & Beverage Company
Case Study
The client is a publicly-traded American beverage and beverage-maker conglomerate, with
headquarters in Massachusetts. It sells coffee, sodas, juices, and other soft drinks.
Challenges
The client wanted to transform the existing data landscape into a serverless cloud platform
by decommissioning the legacy SAP BW application in its landscape.
High cost of data storage on the existing SAP platform with lack of scalability and flexibility.
End of the support period of the existing landscape, with renewal subscription cost being
exuberant.
LTI Solu�on
Re-engineering and migration of the existing trade promotion and demand management
application into Snowflake.
Re-design overall data model, staging and DSO layer having views in Snowflake and
ingested using Informatica Cloud and SnowSQL.
Build a semantic data layer on top of Snowflake using Atscale to enable self service
capability for business.
Client
LTI (NSE: LTI) is a global technology consulting and digital solutions Company helping more than 400 clients succeed in a converging
world. With operations in 31 countries, we go the extra mile for our clients and accelerate their digital transformation with LTI’s Mosaic
platform enabling their mobile, social, analytics, IoT and cloud journeys. Founded in 1997 as a subsidiary of Larsen & Toubro Limited, our
unique heritage gives us unrivalled real-world expertise to solve the most complex challenges of enterprises across all industries. Each
day, our team of more than 30,000 LTItes enable our clients to improve the effectiveness of their business and technology operations
and deliver value to their customers, employees and shareholders. Find more at www.Lntinfotech.com or follow us at @LTI_Global
Business Benefits
~50%reductionin overall datahandling cost
~ 600Objects
migrated intoSnowflake
~ 175Tables
Historical loadingested into
Snowflake
40%SLA time
improvement forreport generation
20%improvement
in overall datasystem availability