Friday, 13/09/2019

Level 1 Auditorium Auditorium A Conf Room 1 Conf Room 6 Conf Room 7
08:30
Main Foyer
08:30 — 30 min

Doors Open

09:00
Main Foyer
09:00 — 30 min

Keynote / Introduction

09:30
09:30 — 60 min

Crazy Data Science

  • Data Science
  • 200
09:30 — 60 min

Applying DevOps practices to Machine Learning

  • DevOps
  • AI & Machine Learning
  • 300
09:30 — 60 min

What's this Machine Learning all about?

  • AI & Machine Learning
  • Data Science
  • 100
09:30 — 60 min

DAX Gotchas

  • Business Intelligence
  • 300
10:30
Main Foyer
10:30 — 15 min

Break

10:45
10:45 — 60 min

Complex Azure Orchestration with Dynamic Data Factory Pipelines

  • Microsoft Data Platform
  • Azure Data Platform
  • Business Intelligence
  • Automation
  • 300
10:45 — 60 min

Benchmarking in the cloud

  • Administration
  • Database
  • Cloud
  • 300
10:45 — 60 min

Supercharge your Reporting Services: An essential toolkit

  • Business Intelligence
  • PowerShell
  • Administration
  • 200
10:45 — 60 min

Multi-server agent jobs administration with happy faces and pigeons

  • Microsoft Data Platform
  • Automation
  • Administration
  • Database
  • Management
  • 200
10:45 — 60 min

AI Capabilities for Power BI to make AI Accessible for Everyone

  • Business Intelligence
  • AI & Machine Learning
  • 200
11:45
Main Foyer
11:45 — 15 min

Break

12:00
12:00 — 60 min

Arguing with myself - self-service BI from an infrastructure perspective

  • Business Intelligence
  • Administration
  • 200
12:00 — 60 min

It's broken, now what?! (Practical problem solving)

  • Professional Development
  • 200
12:00 — 60 min

Don't cross the streams! A closer look at Stream Analytics

  • Azure Data Platform
  • Big Data
  • Development
  • 300
12:00 — 60 min

"Kubernetify" your Containers

  • Microsoft Data Platform
  • Azure Data Platform
  • PowerShell
  • 200
12:00 — 60 min

Guillotines, Sat-Nav and the Query Optimiser

  • Administration
  • Development
  • Database
  • 300
13:00
Main Foyer
13:00 — 45 min

Lunch

13:15
13:15 — 25 min

Lunch & Learn by F1F9

13:45
13:45 — 60 min

Exploring the SQL Tiger Team Toolbox

  • Administration
  • Database
  • 300
13:45 — 60 min

Pipelines and Packages: Introduction to Azure Data Factory

  • Data Warehousing
  • Development
  • Cloud
  • 200
13:45 — 60 min

Microsoft Flow Automation using Power BI API

  • Business Intelligence
  • Automation
  • 100
13:45 — 60 min

Feel Validated with dbachecks

  • Microsoft Data Platform
  • PowerShell
  • Automation
  • Administration
  • Database
  • Management
  • 200
13:45 — 60 min

Striking the right balance while staying relevant

  • Professional Development
  • 100
14:45
Main Foyer
14:45 — 15 min

Break

15:00
15:00 — 60 min

Containers vs Clones: Database provisioning made simple

  • Microsoft Data Platform
  • PowerShell
  • DevOps
  • Automation
  • Development
  • Database
  • 300
15:00 — 60 min

ETL with Azure Databricks, The Complete Introduction

  • Data Warehousing
  • Cloud
  • 300
15:00 — 60 min

You can run SQL Server on AWS?

  • Administration
  • Database
  • 100
15:00 — 60 min

Shape Maps in Power BI

  • Business Intelligence
  • 200
15:00 — 60 min

The Productive Data Professional

  • Business Intelligence
  • PowerShell
  • Administration
  • Database
  • 200
16:00
Main Foyer
16:00 — 15 min

Break

16:15
16:15 — 60 min

SQL Notebooks in Azure Data Studio for the DBA

  • DevOps
  • Database
  • 200
16:15 — 60 min

Advancing Databricks - Taking your ETL to the Next Level

  • Data Warehousing
  • AI & Machine Learning
  • Data Science
  • Big Data
  • Cloud
  • 200
16:15 — 60 min

Azure Data Factory V2; The Data Flows

  • Automation
  • Database
  • Cloud
  • 200
16:15 — 60 min

Using Source Control To Open Up A World Of Community and Collaboration

  • DevOps
  • Automation
  • Administration
  • Development
  • Professional Development
  • 100
16:15 — 60 min

When is data science the answer?

  • AI & Machine Learning
  • Data Science
  • 100
17:15
Main Foyer
17:15 — 15 min

Prize Draws / Closing

18:30
Main Foyer
18:30 – 23:00

After Party

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