Glidewell Laboratories moved data to Amazon Redshift using Attunity CloudBeam to enable analytics and business intelligence. Attunity CloudBeam extracts data from Glidewell's on-premise databases, applies transformations, and loads the data into Amazon Redshift. This provides Glidewell's employees access to timely data in Redshift to support analytics using Tableau and Dundas Dashboards. The migration addressed Glidewell's challenges around managing growing data from multiple sources and providing a robust analytics platform to support their global expansion.

1. Glidewell Laboratories Moves Data to Amazon
Redshift with Attunity CloudBeam
October 20, 2015

2. Agenda
• Overview of Amazon Redshift by Mike
Ruiz, Solution Architect, AWS Emerging
Partner Team
• Overview of Attunity CloudBeam by
Rodan Zadeh, Director of Product
Management, Attunity
• Glidewell Customer Story by Mike Selberis,
CIO, Glidewell Dental Laboratories

3. Agenda
• Overview of Amazon Redshift by Mike
Ruiz, Solution Architect, AWS Emerging
Partner Team

4. Amazon Redshift
Fast, simple, petabyte-scale data warehousing for less than $1,000/TB/Year

5. Data warehousing done the AWS way
• Easy to provision
• Pay as you go, no up front costs
• Fast, cheap, easy to use
• SQL

6. Constant Innovation: 95+ new features since launch…
• Regions – N. Virginia, Oregon, Dublin, Tokyo, Singapore, Sydney, Frankfurt
• Certifications – PCI, SOC 1/2/3, HIPAA and FedRamp
• Security – Load/unload encrypted files, Resource-level IAM, Temporary credentials,
HSM/CloudHSM, Audit Logging
• Manageability – Snapshot sharing, backup/restore progress indicators, SNS Alerts, faster cluster
creation, cross-region backups, faster resize, WLM resource management
• Query – Regex, Cursors, MD5, SHA1, Time zone, workload queue timeout, approximate count
distinct, distributed tables, concurrency increased to 50 from 15, user defined functions
• Ingestion – S3 Manifest, LZOP/LZO, JSON built-ins, UTF-8 4byte, invalid character substitution,
CSV, auto datetime format detection, epoch, load from EMR/HDFS/SSH…
Full list: http://docs.aws.amazon.com/redshift/latest/dg/doc-history.html

7. Amazon Redshift architecture
• Leader Node
– SQL endpoint
– Stores metadata
– Coordinates query execution
• Compute Nodes
– Local, columnar storage
– Isolated from end-user
– Execute queries in parallel
– Load, backup, restore via Amazon S3
– Parallel load from Amazon
DynamoDB
– Load from EMR/HDFS/SSH *New*
• Single node version available
10 GigE
(HPC)
Ingestion
Backup
Restore
JDBC/ODBC

8. Amazon Redshift lets you start small and grow big
Single Node (2 TB)
Cluster 2-32 Nodes
(4 TB – 64 TB)
Cluster 2-100 Nodes (32 TB – 1.6 PB)
Dense Storage Node (dw1.xlarge)
2 TB, 16 GB RAM, 2 cores
Dense Compute Node (dw2.large)
0.16 TB, 16 GB RAM, 2 cores
8XL Dense Storage Node (dw1.8xlarge)
16 TB, 128 GB RAM, 16 cores, 10 GigE
8XL Dense Compute Node (dw2.8xlarge)
2.56 TB, 128 GB RAM, 16 cores, 10 GigE

9. Amazon Redshift integrates with multiple data sources
Dashboarding
Reporting & BI
Ad Hoc Analysis
Amazon Redshift
Amazon EMRAmazon DynamoDBAmazon RDS Amazon S3
On-Premise
database
Flat
files
On-Premise
Warehouse

10. Amazon Redshift works with your existing analysis tools
JDBC/ODBC
Amazon Redshift

11. Common customer use cases
• Reduce costs by
extending DW rather than
adding HW
• Respond faster to
business drivers by
avoiding procurement
loop.
• Improve performance by
an order of magnitude
• Make more data
available for analysis
• Access business data via
standard reporting tools
• Add analytic functionality
to applications
• Scale DW capacity as
demand grows
• Reduce HW and SW costs
by an order of magnitude
Extend On-Premise DW Companies with Big Data SaaS Companies

12. Redshift powers Clickstream Analytics for Amazon.com
• Performance
– Scan 2.25 trillion rows of data: 14 minutes
– Load 5 billion rows data: 10 minutes
– Backfill 150 billion rows of data: 9.75 hours
– Pig  Amazon Redshift: 2 days to 1 hr
• 10B row join with 700 M rows
– Oracle  Amazon Redshift: 90 hours to 8 hrs
• Reduced number of SQLs by a factor of 3
• Cost
– 1.6 PB cluster
– 100 node dw1.8xl (3-yr RI)
– $180/hr
• Complexity
– 20% time of one DBA
• Backup
• Restore
• Resizing

13. Resources
• Detail Pages
– http://aws.amazon.com/redshift
– https://aws.amazon.com/marketplace/redshift/
• Presentations & Webinars:
– http://www.youtube.com/watch?v=JxLpj_TnisM (SF Summit Presentation)
– http://www.youtube.com/watch?v=R1m-fwzXMow (Best Practices 1 of 2)
– http://www.youtube.com/watch?v=7ySzRTOyK6o (Best Practices 2 of 2)

14. Agenda
• Overview of Attunity CloudBeam by
Rodan Zadeh, Director of Product
Management, Attunity

15. Right Data. Right Place. Right Time.
DW
HD
To Analytic Platform To Many Locations
To One Location
Enable Analytics Share & Distribute
Scale Reporting Consolidate
Away from
OLTP

16. Attunity CloudBeam – Highlights
• Simplicity – Automated, “Click-to-Load” Solution
• Performance – Optimized data transfer
• Real-time Data – Incremental/Continuous data loads
• Free Trial – “Try before you Buy”
• One-Stop Shop – Integrated into the AWS Redshift
16

17. Attunity CloudBeam – Solutions for AWS
• Amazon Redshift:
– Load data for BI / Analytics
– One time and incrementally
• Amazon RDS / DBs on EC2:
– Migrate data from on-premise data centers
– Enable disaster recovery (on-premise to cloud)
• Amazon S3:
– Transfer data for archiving, storage, content availability
– Enable disaster recovery

18. Attunity CloudBeam for Amazon Redshift & S3
Simplicity: Automated,
Click-2-Load Solution
Performance: Optimized
data transfer
Real-time: Continuous
data loads
Free Trial: Try before you
Buy
1-Stop-Shop: Integrated
with AWS Marketplace
Pricing Options: Express (hourly), Premium (hourly) and BYOL

19. How Attunity CloudBeam Works
1. Extract data from source database
2. Apply filters and transformations
3. Generate data files for transfer
4. Make optimized transfer to Amazon S3
5. Orchestrate COPY and MERGE for Amazon
Redshift
6. Provide CDC (change data capture) for
incremental loading AWS Region
EC2 Machine
M3.Large
Attunity AMI
RedshiftS3
On-Premises
Source DB(s)

20. Agenda
• Glidewell Customer Story by Mike Selberis,
CIO, Glidewell Dental Laboratories

21. Glidewell Laboratories
• Founded in 1970 and based in California
• Largest dental lab in the United States with a market presence in Europe and
Latin America
• Provides high-quality dental lab products, services, and materials to dental
professionals
• Over 4K employees worldwide
• Over 3M custom units processed and manufactured annually

22. Technology
• Hybrid cloud environment with multiple on-premise datacenters
and AWS as public cloud provider
• Use Attunity CloudBeam to synchronize data between on-
premises databases and Amazon Redshift
• Provide end users with timely access to data on Amazon Redshift
to support business analytics and business intelligence
• Tableau Software and Dundas Dashboards are used for analytics
and data visualization

23. CAD/CAM Digital Manufacturing
MillScan Design

24. Glidewell Data Explosion
• Lab management system (ERP/CRM)
• Case tracking, logistics, technician performance
• Manufacturing data (CAD/CAM)
• Manufacturing Automation
• Robotics
• Cloud-based manufacturing system (CloudPoint)
• IoT (Future)
Introduction of Digital Manufacturing

25. Our Challenge
• Managing an explosion of data and disparate data
sources
• Bridging on-premise data with cloud-generated data
• Providing a robust data analytics platform for our
employees, customers, and engineers
• Development resource constraints
• Global expansion
• Speed of action

26. Our Solution
Dundas
Dashboards
Tableau
Analytics
Ad Hoc reporting
and analysis
Amazon Redshift
Transactional Data
(ERP/CRM)
CloudPoint
Customer DataScan, Design,
& Manufacturing Data
Scan, Design,
& Manufacturing Data
Legacy Manufacturing Data

27. Glidewell Laboratories Moves Data to Amazon
Redshift with Attunity CloudBeam
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recorded webinar