About the event

Journey through an entire Data and Machine Learning lifecycle with the help of DJ James Hendry from The Pineapple Police Horse and teams from Servian, Google Cloud, Looker and Fivetran.

Follow 4 live demo sessions to set up an end-to-end data pipeline that takes advantage of cloud-based tools to help businesses achieve their end goal of understanding their customers better.

This event is for you if you:

  • Are interested in all things data
  • Are considering adding GCP, Looker and Fivetran products and services to your current workflows
  • Like good music and great DJs
  • Enjoy free food
  • Like prizes & giveaways

Date: October 1st

Time: 10am – 2pm (GMT+1)

Register for the Datapalooza below:

Session breakdown

Session 1 – Collection

Consuming online event data from you companies website opens up a huge number of possibilities for customer analysis. In this session Patrick Green, Data Engineer, will demonstrate how this pipeline can be built using Dataflow and a Pubsub topic to consume raw data straight from a customer’s browser window. 


You will learn how to:

  •  Read from pubsub
  •  Reorder and dedupe web events
  •  Combine web events to sessions
  •  Follow the customer journey
  •  Write to cloud storage

Session 2 – Transformation

Building for cloud-native data warehouses and ELT pipelines is not what it used to be. In this session, Simon Darr, Managing Consultant, will demonstrate modern cloud technologies and techniques for building a cloud data warehouse and ELT pipeline.


You will learn:

  • How to use and configure Fivetran to replicate data into BigQuery from Postgres, FTP, Cloud Storage
  • How to run Fivetran transformations on a schedule to model your data
  • Modern modelling techniques such as how to deal with Slowly Changing Dimensions

Session 3 – Machine Learning

What does machine learning (ML) on Google Cloud look like? Byron Alley, Senior Consultant, will discuss the fundamental requirement of feature stores along with how Google Cloud tools can be used to expedite the discovery, development and operationalisation of ML models.. 


You will learn how to:

  • Utilise a feature store 
  • Train an ML model 
  • Deploy an ML model 
  • Operationalise the ML model

Session 4 – Visualisation

Advanced data warehouses like bigquery and highly customisable visualisation tools like Looker can ensure any company can extract and deliver valuable insights from their data. We will look how LookML can enable highly interactive and explainable visualisations.


You will learn about: 

  • Enabling teams via LookML
  • Attribution dashboard. Using: Look ML parameters to weight touch points for attribution, calculated fields to flag bias insights, and aggregating awareness to visualise the customer journey
  • ML model governance 
  • Segmentation analysis

What else is involved?

Guest speakers

Ed Stephens

Partner Sales Engineer, Google Cloud

Sebastian Fabri

Sales Engineer, Looker

Eleanor Thompson

Alliances Manager, Fivetran

Tim Mannah

Managing Director, Servian

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