Get Mainframe and IBM i Data to Snowflake

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Cloud ecosystems have the power to transform a business by delivering quick insights at a low cost. But when you must connect legacy systems like mainframe and IBM i to the cloud, your project can become expensive, time-consuming, and reliant on highly specialized skillsets. So much for low cost and efficiency! Learn from one customer’s story on how easy and cost efficient it can be to get mainframe and IBM i data into Snowflake’s cloud data platform – in 3 minutes or less!

Get Mainframe and IBM i Data
to Snowflake
Precisely Connect and Snowflake
Partnership Overview
Ashwin Ramachandran | Senior Product Manager

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2

Why choose a cloud data platform approach?
3
Build scalable data
warehouses very quickly
Support migrations from
on-prem data warehouses
to the cloud
Enable analytics and
insights at a faster rate
Lower hardware and
software costs

Customer story:
Tracking shipments in real-time

Business Mandate
1. Connect customer and
shipment information that
resides on multiple systems of
record
2. Improve integration and
replication of changes to meet
real-time demand
5

Challenges
• Legacy data formats (e.g., mainframe and
IBM i) are not readily readable and
consumable within cloud data warehouses
• Binary data formats
• REDEFINEs in data fields
• Complex record structures
• Making data movement between on-
premises and the cloud data warehouse was
slow and delayed
• Complex integration architectures, made it
harder to connect to the cloud data
warehouse
6

Results
1
Integrate and replicate
hundreds of z/OS
tables to Snowflake
2
Power customer
dashboards for “near
real-time” reporting
3
Improve productivity
with hourly
dashboard updates
for employees
4
Provide shipment
information in a
way that no other
competitor can
8

Mainframe
(Db2, VSAM)
IBM i Traditional ETL
sources, files, RDMBS,
etc.
Convert mainframe, IBM i and
data from other sources to be
shared anywhere on
Snowflake
BI and Analytics Tools
Deploy Connect on-prem, in
cloud or hybrid environments
9

10
Demo highlights:
• Break down legacy silos to
leverage the scalability, cost
effectiveness, and flexibility
of Snowflake
• Automatic transform of
EBCDIC encoded records
for use in Snowflake
• How you can include high-
value data assets in your
cloud data warehouse

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1. Get Mainframe and IBM i Data to Snowflake Precisely Connect and Snowflake Partnership Overview Ashwin Ramachandran | Senior Product Manager

2. Housekeeping Webinar Audio • Today’s webcast audio is streamed through your computer speakers • If you need technical assistance with the web interface or audio, please reach out to us using the Q&A box Questions Welcome • Submit your questions at any time during the presentation using the Q&A box Recording and slides • This webinar is being recorded. You will receive an email following the webinar with a link to the recording and slides 2

3. Why choose a cloud data platform approach? 3 Build scalable data warehouses very quickly Support migrations from on-prem data warehouses to the cloud Enable analytics and insights at a faster rate Lower hardware and software costs

4. Customer story: Tracking shipments in real-time

5. Business Mandate 1. Connect customer and shipment information that resides on multiple systems of record 2. Improve integration and replication of changes to meet real-time demand 5

6. Challenges • Legacy data formats (e.g., mainframe and IBM i) are not readily readable and consumable within cloud data warehouses • Binary data formats • REDEFINEs in data fields • Complex record structures • Making data movement between on- premises and the cloud data warehouse was slow and delayed • Complex integration architectures, made it harder to connect to the cloud data warehouse 6

7. 7 +

8. Results 1 Integrate and replicate hundreds of z/OS tables to Snowflake 2 Power customer dashboards for “near real-time” reporting 3 Improve productivity with hourly dashboard updates for employees 4 Provide shipment information in a way that no other competitor can 8

9. Mainframe (Db2, VSAM) IBM i Traditional ETL sources, files, RDMBS, etc. Convert mainframe, IBM i and data from other sources to be shared anywhere on Snowflake BI and Analytics Tools Deploy Connect on-prem, in cloud or hybrid environments 9

10. 10 Demo highlights: • Break down legacy silos to leverage the scalability, cost effectiveness, and flexibility of Snowflake • Automatic transform of EBCDIC encoded records for use in Snowflake • How you can include high- value data assets in your cloud data warehouse

Editor's Notes

Connect’s connectivity to Snowflake ensures that all enterprise data is made available in cloud data warehouses for faster, richer analytics

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Editor's Notes