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Teknion Utilizes Matillion to Move Public Transit To The Cloud

Public Transit Client engages Teknion to assist in maturing their data pipeline by migrating their data warehouse to the cloud.

About Client:

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Industry:
Transit
 
Location:
North Eastern United States
 
What Client Does:

Created an app that allows for quick and convenient payment for parking in urban areas and ticketing on public transport.

Solution Focus:
Cloud-based data warehouse paired with advanced visual analytics

The Client's Data Challenge


This client is a global leader in urban mobility technology. They approached Teknion in 2019 seeking consulting services which entailed conducting a Tableau Server assessment, providing recommendations, upgrading their production environment, and continuing Server maintenance and support. After spending extended time with our team, the client looked to Teknion to provide further guidance supporting their need for data improvements and visual analytics enhancements. The first recommendation was for the client to migrate their data to a cloud-based data warehouse to make their data storage solution lighter, faster and more agile. Teknion provided an extensive demo of Snowflake, a cloud-based data warehouse platform, which convinced the client to make the move to the cloud. A senior data architect leveraged Matillion, a best-of-breed cloud-native data transformation tool, to accomplish:

  • Developing load tables and data sources
  • Defining calculations and business rules
  • Building dimensions and fact tables
  • Configuring permissions and security (environment, data, source system, warehouse, role-based, etc.)
  • Enacting job auditing, notifications, and scheduling
  • Establishing an iterative, well-tested process for adding new client data
  • Implementing a multi-tenant system that follows data warehousing best practices
  • Creating security tables and views

A data visualization expert was then able to build numerous Transit Detail dashboards in Tableau connected to the cleansed and consolidated datasource built through Matillion in Snowflake and publish them up to the recently upgraded Tableau Server for ease of accessibility. This suite of dashboards currently provides the client with further visibility into the details and aspects of their data as a whole.

The client's wow outcomes

  • With the help and guidance of only two members of the Teknion team, the client was able to set up an Enterprise Data Warehouse for internal use smoothly and quickly within a month. The power of Matillion shone through by enabling them to create one workflow that generated individual Secure Share views per Client in order for them to have visibility and access only to their own data. New clients can be added via a simple control table making the process extremely scalable and sustainable. Changes can be made quickly and efficiently to all customers at once without any duplication of effort. Adding new customer data, which sometimes took the client more than a week to complete, could now be accomplished within a matter of minutes, all thanks to Matillion. Employing Matillion to successfully handle this arduous yet crucial process with minimal effort saves the client significant time and manpower, freeing their team up to focus their efforts on the more human-centric tasks of growing the business.

  • Tableau allows the client to easily consume their parking and transit data and perform comprehensive visual analytics through the creation and maintenance of customizable dashboards. The stories told by the interactive and informative graphs and charts within these dashboards empower the client to ultimately make better data-driven business decisions.

  • Software Highlights
    • Tableau
    • Matillion
    • Snowflake

  • Recommendations
    • Observe a demo of Snowflake
    • Make data system cloud-based and lighter
    • Use Matillion to handle ETL/ELT processes
    • Build a suite of Tableau dashboards to better present truths buried in their data

 I would like to learn how Teknion can help me solve my organization's unique data challenge.