Corporate & Institutional Banking
How Tableau enabled ABN AMRO
Clearing to visualize Big Data
September 2018
Big Data Expo
Goals of this session
• Clearing
• Big Data & the Hadoop Ecosystem
• Visualization
• Demo
Marleen Meier
Kristi Blaisdell
Kristi Blaisdell
Who are we?
Clearing
16 Million
90 Exchanges
Data everywhere…
PowerPoint
Ecosystem
Useful Bite
Quick and easy access to the data
One central location where all data can be accessed
Visualization
An Example
Tom and Jada have 6 apples.
How many apples do they each get?
Tableau
Tableau Journey
Tableau Desktop (US) Tableau Desktop (EU)
Tableau Server (US)
Tableau Server (EU) User Interface
Throughout office
2017 2018 20192016
Demo – Regulatory Dashboard
From this…. To this….
Regulatory Dashboard
Risk
Anomaly Detection Dashboard
Useful Bite
Understanding data is key, and visualizing it makes it
easier for the end user to understand.
The End
Marleen Meier
Kristi Blaisdell

Abn amro clearing - How Tableau enabled ABN AMRO to visualize Big Data efficiently

Editor's Notes

  • #2 m
  • #3 marleen
  • #4 Both
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  • #6 k Reports and Files, Output per day, backdated ones had to be downloaded from the archive. With BD we can write queries in HUE selecting data from multiple days and its much faster | made ML possible because the Data is accessible | Existing Dashboards build in e.g. D3 need long time to be changed, whole IT cycle. Since we can access Data now via Impala in Tableau the business can adjust those db themselves.
  • #7 m
  • #8 M
  • #9 M Because of the way the human brain processes information, using charts or graphs to visualize large amounts of complex data is easier than poring over spreadsheets or reports.
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  • #12 K Training Videos, User Group Meetings, Wiki, biweekly Team-Up, Invite Zen Masters (Events), Meetups, Blog, Presentations, Workshops, Feedback Survey, Trainings
  • #13 Self Service Enablement tool -> story K: 1. third party - wait on weekly basis, any ad hoc had to be requested -> now: Big Data Hub: access the data myself and make reports that can go out on a daily basis + ad hoc analysis | it was so much data that querying on a data hub made it possible to perform efficiently
  • #16 K
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