Date: 13th November 2018 Location: Self-Service Analytics Theatre Time: 15:10 - 15:40 Speaker: Marius Kaiser Organisation: Tableau About: Big Data platforms enable you to collect, store and manage more data than ever before. But what's the point of it if it's not useful to your organisation? People and companies that visualise their data are more than twice as likely to interact with and explore it. Tableau helps your people spot patterns in your data as they explore and ask questions of it in a visual way. This session will show you how to bring your big data down to eye level, and discover critical insights when you make use of your most valuable assets. Your data and your people.

1. Bring Big Data Up to Eye Level
Marius Kaiser
Solutions Consultant
Tableau

2. We help people
see and
understand
their data.BIG

4. People

5. Right data
Right time
Right level of
Granularity
“
“

7. Agenda
• Big Data Focus for Analytics
• Big Data Framework
• Practical Example
• Summary

8. Big Data Focus for Analytics

9. Big Data Focus
Connectivity
Access to all
data
Performance
Fast
interaction
with all data
Discovery
Finding the
right data

10. Data Strategy
• Selection of Technology
• Align Technology to the
Business Questions
• What questions do users
want to answer?
• How often? How responsive?

11. https://www.tableau.com/about/blog/2017/1/tableau-cloud-netflix-original-64442

13. Big Data Framework
Hot, Warm, Cold

14. Performance
DataSize

15. Hadoop
Relational DB
Analytical DB Hyper

16. Cold Warm
Hot

17. Hybrid Data Strategy
• A combination of in-memory and live query engines
• Designed for adaptability and flexibility
• Unified user experience for full range of data stores

18. Live Query Engine
• Supports the world’s largest
databases
• Attaches directly to enterprise
data stores
• Pushes down workload
• Leverage your Big Data
investments
Hadoop
Hadoop
Fast
databases
Data
warehous
es
Data
warehouses

19. In-Memory Engine
• Extremely fast
computational
ability
• Fast performance
with large data sets
• Optionally
aggregate data
before extracting
Data Extract API
& Web Data Connector
Hadoop Fast
databases
Data
warehouses
OLAP
OBRP
Online Analytical Processing
Online Beyond Relational Processing
one system one state no tradeoffs no d
one system for your transactional, analytical,
and beyond relational workloads
simultaneously process all
on efficient snapshots of on
no tradeoffs: ACID-compliant transactions information at your fingerti

20. Hyper
Fast analysis on data of all sizes

21. STORE ANALYZE SPEED UP CONSUME

22. Let me introduce Air Tableau

23. Cold – Data Lake

24. Flights Performance Data in the Data Lake
Amazon
S3

25. Amazon
S3
STORE ANALYZE SPEED UP CONSUME
Data Scientist
Analyst

26. Hive is too slow for Interactivity
Files

27. Warm - Analyze

28. Faster ways to query the Data Lake
Files
Amazon
Athena

29. Amazon
S3
Amazon
Athena
STORE ANALYZE SPEED UP CONSUME
Data Scientist
Analyst

30. Hot - Let’s Speed It Up

31. Amazon
S3
Amazon
Athena
STORE ANALYZE SPEED UP CONSUME
the computational database
OLTP
OLAP
OBRP
Online Transactional Processing
Online Analytical Processing
Online Beyond Relational Processing
one system one state no tradeoffs no delays
one system for your transactional, analytical,
and beyond relational workloads
simultaneously process all your workloads
on efficient snapshots of one single state
no tradeoffs: ACID-compliant transactions
and full SQL query processing, including
extensions for graph- and data-mining,
on internal data and on external sources
such as Hadoop HDFS
information at your fingertips: no delays
from extract transform load (ETL) phases and
highest performance in all your workloads
enabled by our efficient transaction and
query just in time compilation technology
Analyst
Data Scientist

32. Pre-aggregate
Optimize
Advantage:
Same results, vastly improved
performance
Hadoop Fast
databases
Data
warehouses
Bringing Data in-memory

33. Data Aggregation: Tableau Prep

34. Human Scale of Data

35. Human Scale of Data
Year
Quarter
Month
Week
Quarter
Year
Month
Week
Day
Raw Data

36. Consume

37. Amazon
S3
Amazon
Athena
Amazon
Redshift
STORE ANALYZE SPEED IT UP CONSUME
HyPerthe computational database
OLTP
OLAP
OBRP
Online Transactional Processing
Online Analytical Processing
Online Beyond Relational Processing
one system one state no tradeoffs no delays
one system for your transactional, analytical,
and beyond relational workloads
simultaneously process all your workloads
on efficient snapshots of one single state
no tradeoffs: ACID-compliant transactions
and full SQL query processing, including
extensions for graph- and data-mining,
on internal data and on external sources
such as Hadoop HDFS
information at your fingertips: no delays
from extract transform load (ETL) phases and
highest performance in all your workloads
enabled by our efficient transaction and
query just in time compilation technology
Data Science
Reporting

38. Human Scale of Data
Year
Quarter
Month
Week
Quarter
Year
Month
Week
Day
Raw Data

43. SW3: Cross data-source actions
• Use Action Filters to Jump from Tier
to Tier with a filter context
• Drill Down to the Details
• Leave the Data in the Appropriate
Data Architecture
COLD
WARM
HOT
• Dashboard or Document Acceleration
• High Performance
• Aggregations
• Persistence
• Row Level Security
• Live Connections
• Core Report Development
• Data Mining
• Detailed Data
• Raw Data
• Machine Learning

44. Use Big Data to
Design engaging Analytics for
People
Use the right technology for the right use case

45. Thank you!
Marius Kaiser
mkaiser@tableau.com