Big Data Insight:
Tableau on AWS and AWS with Tableau
Lennart Heuckendorf | Pre-Sales
lheuckendorf@tableau.com
@tableau | @AWS_Germany | @classmethod_aws
2007 – 2011: Bachelor WI HTW Berlin
2011 – 2013: Master WI HTW Berlin
2013 – 2016: BI Consultant T-Systems MMS
2016 - … : Pre-Sales Tableau
The Big Data Journey from a Tableau perspective
Real-life Case Studies
How to do it in AWS
Hyper Hyper
Agenda
The Big Data Journey from a Tableau perspective
A practical definition of Big Data
When your data sets become so large and diverse that you have to start
innovating around how to collect, store, process and analyze data.
Evolution of the
Apache Hadoop
Ecosystem
The Beautiful Science of Data Visualization
There is one constant in the Big Dataverse
A Modern Analytics Stack
• There is more to this stack thanTableau + the
database (i.e. Hadoop)
• Three areas to consider for success analytics
projects:
1. Data ingestion & preparation in the lake:
moving from landing to production
2. Hadoop – the core components from
storage, security, resource management, etc.
3. The Hot Tier – making queries run fast
What is in the Stack?
Real-life Case Studies
What is in the Stack?
What is in the Stack?
What is in the Stack?
What is in the Stack?
What is in the Stack?
Is there a pattern?
Is there a pattern?
Cold Warm Hot Framework
COLD
+ The Data Lake
+ Store Everything and Anything
+ Unknown Questions with Unknown Answers
+ Unstructured / Data Mining / Data Science
WARM
+ Data Warehouses
+ Data Marts prepared for Entity Analytics
+ Known Questions with Unknown Answers
+ Regularly Refreshed Business Concepts
HOT
+ In-Memory Computing
+ Precomputed Aggregates to Answer Specific Questions
+ Known Questions and Known Answers
+ Analytical Dashboard Already Constructed
Cold, Warm, Hot Strategy
Aggregated dataPrepared data
Data
Size
Performance
Large data (raw or prepared)
Hadoop Technology Creep
Tableau Hyper Creep
How to do it in AWS
A Modern Data Warehouse on AWS
A closer Look
Hyper Hyper
Hyper
Hyper as the Data Engine Replacement
Desktop Online Public Server
Hyper
THANK YOU
More question ? Feel free to contact me:
Twitter: @LHeuckendorf
LinkedIn: www.linkedin.com/in/lennartheuckendorf
Email: lheuckendorf@tableau.com

Developers.IO World in Berlin / Tableau Presentation

  • 1.
    Big Data Insight: Tableauon AWS and AWS with Tableau Lennart Heuckendorf | Pre-Sales lheuckendorf@tableau.com @tableau | @AWS_Germany | @classmethod_aws
  • 2.
    2007 – 2011:Bachelor WI HTW Berlin 2011 – 2013: Master WI HTW Berlin 2013 – 2016: BI Consultant T-Systems MMS 2016 - … : Pre-Sales Tableau
  • 3.
    The Big DataJourney from a Tableau perspective Real-life Case Studies How to do it in AWS Hyper Hyper Agenda
  • 4.
    The Big DataJourney from a Tableau perspective
  • 5.
    A practical definitionof Big Data When your data sets become so large and diverse that you have to start innovating around how to collect, store, process and analyze data.
  • 6.
    Evolution of the ApacheHadoop Ecosystem
  • 7.
    The Beautiful Scienceof Data Visualization There is one constant in the Big Dataverse
  • 8.
    A Modern AnalyticsStack • There is more to this stack thanTableau + the database (i.e. Hadoop) • Three areas to consider for success analytics projects: 1. Data ingestion & preparation in the lake: moving from landing to production 2. Hadoop – the core components from storage, security, resource management, etc. 3. The Hot Tier – making queries run fast
  • 9.
    What is inthe Stack?
  • 10.
  • 11.
    What is inthe Stack?
  • 12.
    What is inthe Stack?
  • 13.
    What is inthe Stack?
  • 14.
    What is inthe Stack?
  • 15.
    What is inthe Stack?
  • 16.
    Is there apattern?
  • 17.
    Is there apattern?
  • 18.
    Cold Warm HotFramework
  • 19.
    COLD + The DataLake + Store Everything and Anything + Unknown Questions with Unknown Answers + Unstructured / Data Mining / Data Science WARM + Data Warehouses + Data Marts prepared for Entity Analytics + Known Questions with Unknown Answers + Regularly Refreshed Business Concepts HOT + In-Memory Computing + Precomputed Aggregates to Answer Specific Questions + Known Questions and Known Answers + Analytical Dashboard Already Constructed
  • 20.
    Cold, Warm, HotStrategy Aggregated dataPrepared data Data Size Performance Large data (raw or prepared) Hadoop Technology Creep Tableau Hyper Creep
  • 21.
    How to doit in AWS
  • 22.
    A Modern DataWarehouse on AWS
  • 23.
  • 24.
  • 25.
  • 26.
    Hyper as theData Engine Replacement Desktop Online Public Server Hyper
  • 27.
    THANK YOU More question? Feel free to contact me: Twitter: @LHeuckendorf LinkedIn: www.linkedin.com/in/lennartheuckendorf Email: lheuckendorf@tableau.com