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Abn amro clearing - How Tableau enabled ABN AMRO to visualize Big Data efficiently
- 1. Corporate & Institutional Banking How Tableau enabled ABN AMRO Clearing to visualize Big Data September 2018 Big Data Expo
- 2. Goals of this session • Clearing • Big Data & the Hadoop Ecosystem • Visualization • Demo
- 3. Marleen Meier Kristi Blaisdell Kristi Blaisdell Who are we?
- 6. Ecosystem
- 7. Useful Bite Quick and easy access to the data One central location where all data can be accessed
- 9. An Example Tom and Jada have 6 apples. How many apples do they each get?
- 10. Tableau
- 11. Tableau Journey Tableau Desktop (US) Tableau Desktop (EU) Tableau Server (US) Tableau Server (EU) User Interface Throughout office 2017 2018 20192016
- 12. Demo – Regulatory Dashboard From this…. To this….
- 15. Useful Bite Understanding data is key, and visualizing it makes it easier for the end user to understand.
- 16. The End Marleen Meier Kristi Blaisdell
Editor's Notes
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- 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.
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- 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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- K Training Videos, User Group Meetings, Wiki, biweekly Team-Up, Invite Zen Masters (Events), Meetups, Blog, Presentations, Workshops, Feedback Survey, Trainings
- 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
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