Watch full webinar here: https://bit.ly/3H5AYZf Implementing a logical data fabric as an architecture makes absolute sense when you have data spread across various sources in the cloud, including data warehouses, data lakes and even realtime data. In this session our customer will discuss the ways in which they implemented Denodo as a logical data fabric and how it helped them reduce risk and speed up time to access data.

1. Logical Data Fabric: The Future of Data
Management and Analytics

2. #DenodoDataFest
Implementing a Logical Data Warehouse
Data Architect, Sharp Healthcare
Holly Burch

4. Introduction:
Holly Burch
• Primary Denodo architect and platform administrator
Denodo Journey
• Jon McManus, new VP Enterprise Analytics, arrives Oct 2018 with the vision of
implementing a Logical Data Warehouse
• Began implementing Denodo platform Summer 2019
• Currently at more than 100 data sources from more than 40 source systems
• Denodo 8.0 platform currently on-premise and planning to move it to the cloud

5. Vision:
Logical Data Warehouse
• Apply an architectural approach that enables access to multiple, diverse data
sources (both on premise and multi-cloud) while appearing as one “logical” data
source to users.
Data Marketplace
• Provide a single place to browse, consume, and create consumable content.

6. Starting State:

7. Frustrations:
• 30 projects/year
• Process = Slow grind
• New Source
• 2 – 3 months
• Enhancement
• 2 – 3 weeks
• Limited access for
end-users
• Hard to blend data
AGILE? NO

8. Logical Data Warehouse

9. Transformation:
• Centers of Excellence
• Process = Agile teams
• New source: 2 – 3 weeks
• Enhancement: 2 – 3 days
• Easy to blend/enrich data
• Navigate EMR and ERP system
changes
• Back-end migrations with no
impact to end-users
• Marketplace access
• Many ways to deliver
AGILE? YES
Logical Data Warehouse

10. Use Case: Migration off Cloudera Impala to Snowflake
Cloudera Impala
• Real-Time streaming of HL7 messages – Lab orders/results, Scheduling
• Real-Time streaming of Electronic Medical Record data
• Denodo views of Lab data feeding to critical covid dashboards
• Denodo views of Scheduling data exported hourly for patient feedback
Snowflake Migration
• Migrated storage of data from Impala to Snowflake
• Brought in new Snowflake base views to Denodo
• Updated existing integration layer views to source from Snowflake base views instead
of Impala base views.
• 3 - 4 weeks to fully test and implement in Denodo

11. Summary:
Logical Data Warehouse with Denodo as a key component allows us to:
• Create a Data Marketplace for client consumption
• Bring on-prem and cloud-based data together to appear as one “logical” source
• Blend/enrich data between sources
• Navigate major EMR and ERP platform changes
• Migrate back-end sources without impacting end users
• Support agile workflows

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