Fivetran

Transcript

1. Enabling Real-Time
   Analytics with CDC at Philips
   

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2. Divya van
   Mahajan
   Introduction
   Marco
   Blanca
   Chief Product Owner SRC
   Philips
   Lead Big Data Consultant
   Devoteam
   Frank
   Knot
   Sr. Enterprise Solutions Architect
   Fivetran
   

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3. Agenda
   3
   ● The Company
   ● Fivetran technology
   ● The Challenge
   ● The Solution
   ● Use Cases
   ● The Journey
   ● Key Learnings
   

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4. © Koninklijke Philips N.V.
   At Philips, we’re empowering people
   to take care of their health and
   well-being and helping doctors and
   nurses to provide better, more
   sustainable and more convenient care
   – in hospitals, clinics and the home.”
   Roy Jakobs
   CEO Philips
   “
   

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5. Strong positions across our portfolio of businesses
   Last 12 months’ sales
   Connected Care
   29% of sales
   Personal Health
   20% of sales
   Diagnosis & Treatment
   47% of sales
   Diagnostic
   Imaging
   Monitoring Sleep &
   Respiratory Care
   Personal Health
   Ultrasound Image Guided
   Therapy
   Enterprise
   Informatics
   Systems, smart devices, software and services, powered by
   AI-enabled informatics
   Supporting precision diagnosis and minimally invasive
   treatment in a growing number of therapeutic areas such as
   cardiology, peripheral vascular, neurology, surgery, and
   oncology
   Ambulatory, home-based and in-hospital monitoring and
   workflow solutions fueled by advanced interoperability and
   patient data insights
   Connecting patients and caregivers across care settings,
   delivering clinical, operational and therapeutic solutions
   Broad range of
   consumer solutions
   to support people
   in proactively
   managing their
   health and
   well-being
   Market-leading capabilities integrating platforms, informatics, and services
   

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6. 6
   Data Lake and Analytics at Philips
   Data Lake foundation in Azure supporting DaaS; Real-time data; data application initiatives
   

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7. 7
   Marco Blanca
   Introduction
   Tribe Lead Data & AI
   Strongest capabilities
   Cloud | DevOps | Data-Driven | Integration & API
   Local partnerships Some known clients
   Key facts & figures
   300 tech experts | 100+ satisfied clients
   Strategic partnership focus
   

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8. Reference Architecture
   Events
   Databases
   (Cloud or on prem)
   Application
   Files
   Data Sources
   Destinations
   Data Lakes
   Cloud Data
   Warehouses
   Data Tools
   Orchestration
   Governance
   Observation
   etc.
   Data Lakes
   Cloud Data
   Warehouses
   Fivetran
   Event
   Platforms
   End to End Automation, Reliability and Scalability
   

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9. 9
   The Challenge
   Architecture before Fivetran/HVR adoption
   ● No Real-Time
   ● Source deletions
   cannot be replicated
   ● Limited extraction time
   window
   ● Synapse not suited for
   very large Audiences
   

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10. The Solution: Fivetran & Databricks to deliver great value
    

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11. ● Increase the digitalization of factories and enable Data Driven decision to improve
    KPIs like productivity
    ● Standardize the landscape, increase data quality and reduce manual work
    Digital Factory
    

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12. ● Provide Supply Chain information in a timely manner, safely and cost efficiently.
    Supply Chain Optimization
    

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13. 13
    2020
    Start
    Replication with ADF, Synapse
    Dedicated as a target
    Paradigm Shift
    Replication via Fivetran for ERP,
    First tables landed on Delta Lake
    as a target
    2021
    Consolidation
    5 main ERP Systems and
    manufactories on-boarded
    2022
    Optimization
    Introduction of Databricks
    Streaming Jobs to reduce costs
    and increase flexibility
    Summer
    2022
    Scale
    Introduction of Unity Catalog and
    Salesforce Fivetran connectors
    Today
    # Data Sources: > 50
    # Tables: > 9000
    Volume: > 1 PiB
    # Changes Daily (average): >
    180M (with spikes > 3B)
    #Streaming Jobs: > 80
    Our Journey to a Mature Data Lake
    

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14. Close collaboration with business to deliver
    data at the expected velocity
    14
    Fivetran and Lakehouse have proven to be an
    efficient solution to extract data from SAP
    60% Cost saving achieved using Spark
    Streaming for Silver
    Automate-First approach to properly handle
    the amount of data sources
    Key Learnings
    Close collaboration with Fivetran is a key
    success factor for technical challenges
    

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15. Questions?
    

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