From our 2021 Enterprise Automation Awards, the Data Innovation Award recognized the customer that innovated the business or disrupted the industry by using data.
For global shipping and mailing company Pitney Bowes, data is key. Data provides:
- Information about how a company is doing in terms of its products, sales, and revenue
- Insights into customer behavior and customer usage patterns on products
- Insights into the performance of various business processes and how that impacts the business
Without the appropriate integration platforms or products it was difficult to gather, consolidate and process data requested by the business units. Several business units within Pitney Bowes were gathering data from various source systems like Salesforce, SAP_HANA, GUAM, and OKTA to create their own individual analysis related to Performance, Sales, Revenue, Growth, Customer Satisfaction, Product Subscriptions, and Authentication. Due to this, each team used to use their own set of tools for integrating with these source systems and gathering the data into their own repository. Many times, even though multiple teams were getting the same data, the analysis would be different as teams may be gathering the data at a different frequency or with different logic, causing questions on the validity of the data.
Pitney Bowes searched for an Integration Platform that would not only integrate with the multiple sources but also create a single repository of the data that the different business teams could use. They invested in an AWS-based S3 Data Lake and selected the SnapLogic Integration Platform to gather the data from these source systems into the Data Lake. When the need to combine data from these systems increased, Pitney Bowes invested in an Enterprise Cloud Based Data Warehouse – Snowflake – so that people could easily combine and share analysis and insights with others in the company. With SnapLogic, Pitney Bowes was able to integrate over 25 applications to their data repository for over 20 business units (or over 300 users).
Sourcing data from the source systems and gathering it in their S3 Data Lake and Enterprise Data Warehouse significantly improved from a few days to a few hours. In addition, some of the core Data Movement Integrations are developed, tested and implemented in Production in less than 2 hours resulting in tremendous savings in Time and Effort.