Big Data =Big Benefits For The Retail Industry · 2018. 10. 9. · business insights. Atos...
Transcript of Big Data =Big Benefits For The Retail Industry · 2018. 10. 9. · business insights. Atos...
Organizations are increasingly grappling with the “Big Data” problem. What is Big Data? How did “Data” evolve into “Big Data”?Smart devices, improved Internet connectivity, Social Media, and cheaper storage have contributed to a significant increase in the volume, velocity and variety of data generated every single day. Almost 80% of this data is unstructured – photos, videos, sound, media, e-mail, social feeds, blogs, locations, appliancesensors, text messages, and more. This “Big Data” is anincredible source of intelligence for organizations and apotential source of competitive advantage.
The retail industry is at the forefront of the Big Data revolution, with every point-of-sale transaction, website click, or social media post potentially revealing an insight into the customer’s preferences and buying behavior. The capability to harness this information effec-tively to provide optimal pricing and enhanced customer experi-ence can be a game-changer for retailers. The best way to unlock the power of this data is to collaborate with an innovative, established IT partner that will extract maximum benefits from Big Data solutions, and deliver value-added business insights. Atos Syntel’s Big Data Innovation Lab has built solutions around the pioneering open source platform—Hadoop—to empower its retail clients with valuable insights.
enable you to acquire,BI
G DATA
organize, and analyze Big Data in conjunction with traditional enterprise data to drive business value.
Our services have enabled clients to:
Transform key business processes in market-ing, merchandizing, and supply chain
Gain customer insights to enable personali-zation and influence purchase decisions
Improve profitability through dynamic real time pricing
Speed up reporting, analysis, and modeling
Atos Syntel
SERV ICES
Capitalize on changing market dynamics—predict trends and prepare for future
Identify business use cases with measurable outcomes
Start with existing data for quick successes
Build on small successes and integrate with transactional applications and web portals
OVERVIEW OF THE
BIG DATAINNOVATION LAB’S APPROACH
Develop organization-wide Big data strategy
Select the right tools and architecture for implementation
Run Project in sprints, with tangible and measurable outcomes
BIG BENEFITSFOR THE RETAILINDUSTRY
BIG DATA
CLIENTSITUATION
SOLUTION
Improved Customer Insight for Online Retail Store
BIGDATALeverage
weits Retail ClientsHow does help
BUSINESS VALUE
CLIENTSITUATION
SOLUTION
Personalized End-user Experience for Retail Store
BUSINESS VALUE
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Atos Syntel's
BIG D
ATAINNOVATION LAB
• Offering end-to-end Big Data services from data management, informationdelivery, to information lifecycle management
• A dedicated team of technical and business domain experts with hands-onexperience in developing and deploying Big Data solutions
• Cost-effective solutions to manage and integrate data to derive insights fordecision support
• Product capabilities, tools, accelerators, and frameworks to create tangiblebusiness value for clients
For more information, visit us at www.atos-syntel.net
• One of the largest online homeimprovement specialty retailers in theUS
• Teradata-based business warehousecould capture and store web-clickhistory for 6 months only
• Limited ability to leverage historicaldata to improve product offerings andincrease profitability
• One of the largest online homeimprovement specialty retailers in the US
• Inability to identify unique customers andpreferences due to duplicate customerrecords and limitations of their legacysystem
• Needed a technology solution to storemillions of customer records, interfacewith third-party services, and identifyduplicate and unique customers
• Re-architected the data model to storeraw data and perform aggregation inHadoop with aggregated results movedto Teradata
• Developed scalable and cost-effectiveBig Data solution to track and analyzethe click stream using:
• HDFS, a Hadoop distributed file system• Hive, an SQL-like interface that
abstracts complexities of Map-Reduce• Cassandra, a distributed columnar
NoSQL datastore• Single source of truth for customer
definition
• Enhanced ability to provide apersonalized end-user experience
• Peer-to-peer architecture eliminatedsingle point of failure and reducedapplication downtime
• Client saved $1 million by migratingfrom legacy database (mainframeprocessing cycles) to Hadoop
• Reduced batch job processing timedue to lower processing requirement
• Focused targeted marketing for bettercustomer satisfaction
• Ability to derive timely insights fromlarge historical dataset
• Client saved $500,000 by migratingfrom commercial data warehouse toHDFS
• Faster response from BI team tobusiness user’s requests
• Enhanced customer conversionswith cross selling ability
• Migrated data feed to HDFS andprocessed it on Hadoop
• Implemented Hive for data cleansing
• Leveraged data science techniques todevelop business logic for identifyingunique customers using Map-Reduceframework