The Client
Putnam Investments manages a portfolio of over $175 billion in assets and practices an active, research-intensive approach to investing. The firm, based in Boston, operates across North America, Europe, and Asia. With an increasing number of customers and a growing database, Putnam’s goal was to transform into a data-centric, cloud-based organization.
Objectives
Putnam sought to enable sustainable business growth and profitability by capturing efficiencies through improved data access.
Putnam needed to respond to the demands of its business and end users for the benefits available in the cloud.
Putnam engaged Mastek to develop to train and expedite the migration from Cloudera to Snowflake.
The Challenges
- Missing the expertise needed to make the transition to Snowflake.
- After ten months into the migration process, Putnam’s in-house team was still missing a consolidated data strategy.
Why BizAnalytica (a Mastek company)
- Proven expertise in migrating from Cloudera to Snowflake.
- Ability to create a business case to validate costs savings.
- Experience with building a data warehouse with Snowflake on AWS.
Why Mastek?
- Proven expertise in migrating from Cloudera to Snowflake.
- Ability to create a business case to validate costs savings.
- Experience with building a data warehouse with Snowflake on AWS.
The Solution
Our team took a fresh approach to develop Putnam’s overall data strategy and helped the firm decide to implement Snowflake on AWS to replace their on-premises data lake built on Cloudera’s Distribution of Hadoop platform. As part of the consulting engagement, the team worked hand-in-hand with Putnam’s data architecture team to redesign and built a data warehouse with Snowflake on AWS. The firm was able to leverage our organization’s pre-built frameworks to accelerate the migration significantly.
- Migrate 20 on-prem applications, 23 Essbase Cubes, 4000+ reports and 28 integration touchpoints to the cloud
- Migrate 100 GB of data from legacy systems to Oracle Cloud
- Gain a bird-eye’s view of operations by incorporating dashboards
- Drive better insights from data, improved reporting, top-notch data security, governance and compliance
The Solution
Our team took a fresh approach to develop Putnam’s overall data strategy and helped the firm decide to implement Snowflake on AWS to replace their on-premises data lake built on Cloudera’s Distribution of Hadoop platform. As part of the consulting engagement, the team worked hand-in-hand with Putnam’s data architecture team to redesign and built a data warehouse with Snowflake on AWS. The firm was able to leverage our organization’s pre-built frameworks to accelerate the migration significantly.
- Migrate 20 on-prem applications, 23 Essbase Cubes, 4000+ reports and 28 integration touchpoints to the cloud
- Migrate 100 GB of data from legacy systems to Oracle Cloud
- Gain a bird-eye’s view of operations by incorporating dashboards
- Drive better insights from data, improved reporting, top-notch data security, governance and compliance
These Solutions Included
- Creating a unified front-end that makes data workflows highly customizable and accessible for application development.
- Rewriting queries and processes that were defined in Oracle to AWS-friendly SQL.
- Building a secure, continuous data sync between legacy systems and the cloud.
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Client, XYZ Company
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Client, XYZ Company
Benefits
Improved Quality and reliability of services.
Improved customer satisfaction & confidence.
Average monthly critical system issues reduced by 60%.
Reduced staffing and systems management time.
Average monthly performance issues reduced by 90%.
The Outcome
Putnam’s migration was completed in just 60 days. With many Python based, self-service utilities set up; the data architecture team was able to support an acceleration in customer analytics processes and go-to-market plans.
Improve query response by 10x.
Accelerate internal adoption and usage of Snowflake by 12x.
Improve query response by 10x.
Accelerate internal adoption and usage of Snowflake by 12x.
Benefits
Putnam’s migration was completed in just 60 days. With many Python based, self-service utilities set up; the data architecture team was able to support an acceleration in customer analytics processes and go-to-market plans.
- Speed – In just 60 days, Putnam’s migration was wholly transformed
- Performance – 10X improvement in query response times
- Affordability – 19% reduction in previous IT spend(~ $2M over 3 years)
- Agile Processing – Workflow adjustments in data lake made in minutes
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