In this webinar, Cloudera and AtScale will showcase: How a company can modernize their analytic architecture to deliver flexibility and agility to more end-users. How using AtScale’s Universal Semantic layer can end the data chaos and allow business users to use the data in the modern platform. Highlight the performance of AtScale and Cloudera’s analytic database with newly completed TPC-DS standard benchmarking. Best practices for migrating from legacy appliances.

1. CONSOLIDATE YOUR DATA MARTS FOR
FAST, FLEXIBLE ANALYTICS
Alex Gutow | Cloudera
Josh Klahr | AtScale

2. 2 © Cloudera, Inc. All rights reserved.
TRENDS WITHIN DATA WAREHOUSING
Expand to
Do More
Nearly 40% want greater capacity for
growing data, users, reports,
analyses, etc1
Improve
Responsiveness
67% of users are requesting to do
more BI/analytics on their own2
Balance Business
Critical & Exploration
42% looking to augment EDW with
modern platform1
1Data Warehouse Modernization In the Age of Big Data Analytics, TDWI, 2016
2Achieving Greater Agility with Business Intelligence, TDWI, 2014

3. 3 © Cloudera, Inc. All rights reserved.
FIRST GENERATION
EDWETL

4. 4 © Cloudera, Inc. All rights reserved.
THE RISE OF NEW TOOLS
EDWET
L
ET
L
Analytic
Appliances
Curated Data
Sets/OLAP
Cubes

5. 5 © Cloudera, Inc. All rights reserved.
POLL QUESTION #1
What analytic appliances or data marts does your organization use? (Select all that apply)
• Netezza
• Vertica
• AWS Redshift
• Snowflake
• Exadata
• BI Tool Extracts (Tableau, Qlik, etc)
• EDW
• None/Unknown
• Other

6. 6 © Cloudera, Inc. All rights reserved.
RISE OF THE DATA LAKE
EDW
ET
L
Analytic
Appliances
Curated Data
Sets/OLAP
Cubes
Data Hub
/Data Lake

7. 7 © Cloudera, Inc. All rights reserved.
LIMITATIONS OF EXISTING INFRASTRUCTURE
• Not able to take on more reports,
use cases, users, etc.
• Constrained exploration to prevent
risking critical SLAs
• Proliferation of data silos to address
additional workloads
• Maintain data copies causes
inefficiencies for storage,
processing, and people
• Need to contain costs for
existing workloads
• Difficult to justify budget and
maintenance for expansion
• Struggle to do more with less
• Designed for curated reports, not
iterative, self-service analytics
• Not built for elasticity or object
store integration
Compute
Store

8. 8 © Cloudera, Inc. All rights reserved.
POLL QUESTION #2
What pain points or limitations are you facing with your data mart(s)? (Select all that apply)
• Cannot meet internal SLA for delivering data
• Struggle to contain costs
• Long wait times for new data
• Limited data for querying
• Data exists across silos
• Cannot connect BI tools
• Migrating to cloud
• Other

9. 9 © Cloudera, Inc. All rights reserved.
DATA WAREHOUSING OPTIMIZATION & CONSOLIDATION
CLOUDERA DATA WAREHOUSE
ATSCALE UNIVERSAL SEMANTIC
LAYER
ENTERPRISE DATA
WAREHOUSE
DATA MART(S)
OPTIMIZE
THROUGH
OFFLOAD
COMPLETE
MIGRATION

10. 10 © Cloudera, Inc. All rights reserved.
ADVANTAGES OF MODERN DATA WAREHOUSING
Data Flexibility
• Iterative modeling and
self-service accessibility
• Portability: No proprietary formats
or storage lock-in
Go Beyond SQL
• Consolidate data silos with
an open architecture
• Shared data across SQL
and non-SQL workloads
High-Performance SQL +
Cost-Effective Scalability
• Elastic scale in any environment
• Cloud-native integration for
optimized pay-per-use costs
• Proven at massive scale
Hybrid Decoupled Architecture
• Runs across multi-cloud & on-
prem
for zero lock-in
• Multi-
storage over S3, ADLS, HDFS,
Kudu, Isilon, etc
Shared Data

11. 11 © Cloudera, Inc. All rights reserved.
MODERNIZING FOR THE DATA AGE
Fixed
Reports
DATA SOURCES MODERN DATA WAREHOUSE
Flexible
Reporting
Advanced
Analytics
Self-Service
BI/Ad Hoc
Dashboards/
Analytic Apps
EDW
UNIVERSAL SEMANTIC LAYER

12. 12 © Cloudera, Inc. All rights reserved.
MORE VALUE AT A LOWER COST/TB
AverageCostperTB
Observed 80%
decrease
in TCO
Note: TCO calculations and migration opportunity is dependent on your environment
and types of workloads. Please work with Cloudera to calculate potential savings for
your environment

13. © Cloudera, Inc. All rights reserved.
PROOF OF PERFORMANCE & OLAP FUNCTIONALITY

14. 14 © Cloudera, Inc. All rights reserved.
IMPALA OUTPERFORMS ANALYTIC DATABASES
• Impala outperforms on
both single and multi-
user tests at 10TB
• Impala lead expands
with concurrency
• Other SQL on Hadoop
engines failed at 10TB
Streams Impala QpH MPP DB QpH Impala Times Better
2 41 20 2.05x
4 75 20 3.75x
8 133 16 8.31x
Metric Impala MPP DB Impala Times Better
Total seconds 11,898 21,093 1.77x
Geometric mean 33 92 2.79x
Single-user Test – 10TB
Multi-user Test – 10TB

15. 15 © Cloudera, Inc. All rights reserved.
TPC-DS 1TB: SINGLE-USER
• The analytical db cohort
(Impala / MPP) leads
SQL on Hadoop
• Impala outperforms
• Presto by 8.3x
• Hive w/ LLAP by 4x
• Spark SQL by 2.8x Impala Greenplum Spark SQL
Hive with
LLAP
Presto
Total 100% 97% 283% 405% 826%
Geomean 100% 250% 367% 450% 1317%
0%
200%
400%
600%
800%
1000%
1200%
1400%
RelativePerformance
TPC-DS 1TB Single-user (Lower is Better)

16. 16 © Cloudera, Inc. All rights reserved.
TPC-DS 1TB: MULTI-USER
• At 1TB the analytic db
cohort (Impala / MPP)
expands lead with
concurrency
• With 16 streams Impala
outperforms
• Spark by ~22x
• Hive by ~20x
• Greenplum by ~3x
4 streams 8 streams 16 streams
Impala 495 865 1,315
Greenplum 381 417 462
Spark SQL 76 70 61
Hive with LLAP 58 62 66
0
200
400
600
800
1000
1200
1400
QueriesperHour
Multi-user TPC-DS 1TB Queries/Hour
(Higher is Better)
20x

17. 17 © Cloudera, Inc. All rights reserved.
COST-EFFECTIVE PERFORMANCE
With Cloudera + AtScale
Cloudera + AtScale can meet or
exceed the performance needs of
traditional database users
• Impala provides leading analytic database
performance at high user concurrency
• AtScale’s Intelligence Platform improves
query performance
• Dimensional Calc Engine allows complex
OLAP-style calculations to run directly on
cluster
Fortune 50 Insurance Company
Use Case Netezza
AtScale +
Cloudera Speedup Factor
Metric Trends 4.0 0.3 15.6 times faster
Customer Growth 6.8 0.3 20.6 times faster
Segment Benchmark 2.4 0.9 2.7 times faster
Time Series 5.5 1.1 4.9 times faster
Transaction Dashboard 5.5 0.4 12.7 times faster
Top Customers 5.4 0.9 6.1 times faster
Product Heatmap 5.5 0.2 34.8 times faster
Top Products 5.5 1.9 2.9 times faster
Top Suppliers 5.5 0.8 6.9 times faster

18. 18 © Cloudera, Inc. All rights reserved.
BI ON BIG DATA IS ABOUT MORE THAN JUST PERFORMANCE
AtScale adds OLAP to Cloudera’s Analytic DB
Benefits of AtScale + Impala
• OLAP is the language of BI
■ Provides business users access to functions like: time-
intelligence, drill-down, and slicing and dicing
• AtScale is optimized for Impala
■ Provides intelligent queries, optimized data structures

19. 19 © Cloudera, Inc. All rights reserved.
DATA SCIENTISTS AND BUSINESS USE THE SAME DATA
Curate the data once - deliver self-service BI and Data Science
Benefits the AtScale Universal Semantic Layer
• Keeps the data in the Cloudera cluster
• Avoids extractions or data marts
• Simplifies and modernizes your data architecture
• Allows any BI tool to access the data, including Excel, PowerBI, Tableau,
etc.

20. 20 © Cloudera, Inc. All rights reserved.
POLL QUESTION #3
Which BI tools are you using? (Select all that apply)
• Tableau
• SAP Business Objects
• Excel
• PowerBI
• Qlik
• Spotfire
• Microstrategy
• Zoomdata
• Cognos
• Other

21. 21 © Cloudera, Inc. All rights reserved.
ATSCALE PRESENTS DATA FOR BI USERS, NOT DATA ENGINEERS

22. 22 © Cloudera, Inc. All rights reserved.
DASHBOARDS DEMAND CONCURRENCY, THROUGHPUT

23. © Cloudera, Inc. All rights reserved.
JOINT CUSTOMER SUCCESS

24. 24 © Cloudera, Inc. All rights reserved.
TOYOTA
Self-Service BI for Finance & IoT
Cloudera + AtScale
• Deliver sub-second queries
• Supports ad hoc Tableau and
PowerBI
• Data science embedded with
business units and goals
• Enable and protect enterprise
data consumption
Faster time-to-insights
Self-service users
Databases migrated
Self-delivered dashboards

25. 25 © Cloudera, Inc. All rights reserved.
GLOBAL PHARMACEUTICAL
R&D Information Platform
Cloudera + AtScale
• Consistent, shared data access
through BI tools (Tableau, Tibco)
• Interactive query speeds
• OLAP capabilities
• HIPAA compliant
Time-to-insights in minutes, not years:
• Reduced cost and time to identify
clinical trial groups
• Accelerate new drug development
• 1st time metrics and monitoring on
compliance data
structured + unstructured
100% unstructured data
captured
Analytic Users
70% Execs/Managers
25% Analysts
5% Data Scientists
Reduction in silos
Use cases

26. © Cloudera, Inc. All rights reserved.
THE OFFLOAD PROCESS

27. 27 © Cloudera, Inc. All rights reserved.
WHERE DO YOU START?
12 am 12 pm 12 am
1.6M
1.2M
800K
400K
6 am 6 pm
Query volume can be huge
• How do you determine what workloads to run
on Cloudera’s platform?
• Will the queries run efficiently?
• What does it take to migrate?
• How do you prioritize?
Numerous databases, thousands of tables,
many users and applications
Queries can be very complex

28. 28 © Cloudera, Inc. All rights reserved.
DATA WAREHOUSE OPTIMIZATION
Tools & Framework to help you through the process
Plan Offload Optimize
Estimate Effort
Risk Analysis
Schema Design
Test & Validate
Evaluate
Identify Use Cases Impact Analysis
Set Objectives
Prioritized Plan
Initial POC
Offload each workloadEvaluate the need and scope
Impact analysis, prioritized
plan
Optimize for performance
Identify Suitable
Workloads
Offload Actions
Capacity Planning
Fine Tuning Data
Model on Hadoop
Optimize Queries for
Performance
Validate ROI, Cost

29. 29 © Cloudera, Inc. All rights reserved.
WHERE TO LEARN MORE
Learn more how GSK and Toyota
brought BI to the Data Lake:
http://info.atscale.com/webinar_do_dont_bi_on_
data_lake_2018-0
Get the report for how to offload BI
workloads:
https://www.cloudera.com/content/dam/www/ma
rketing/resources/analyst-reports/efficiently-
offloading-and-optimizing-bi-workloads-to-
hadoop-with-cloudera-navigator-
optimizer.pdf.landing.html
Contact us or check out:

30. THANK YOU