Modernizing your infrastructure can get complicated really fast. The keys to success involve breaking down data silos and moving data to the cloud in real time. But building data pipelines to mobilize your data in the cloud can be time consuming. You need solutions that decrease bandwidth, ensure data consistency, and enable data migration and replication in real-time; solutions that help you build data pipelines in hours, not days.
Watch this on-demand webinar to learn about the trends and pitfalls related to modernizing your infrastructure to cloud, how the pace of on-prem data growth demands accelerating data streaming to analytics platforms, and why mobilizing your data for the cloud improves business outcomes.
6. More often, organizations
are collecting and
analyzing this data
(Copyright TDWI, 2021)
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Video data
Audio data
Image still data
Clickstream data
Machine generated data (e.g., from sensors,…
Real-time event streams
External text data
Geospatial data
Semi-structured data
Internal text data
Time series data
Demographic data
Log data
Transactional data
Structured data
What kind of data is your organization currently
managing? Looking to manage in the next year?
Manage now Manage in next year
10. Why unify the
DW and DL?
• “[A unified DW/DL] provides more options for
managing an increasingly diverse range of data
structures, end user types, and business use
cases.” Corporate IT professional, healthcare
• “Modern data is both counting/reporting and
using data as an input into predictive models. The
structure and rigor necessary for full DW may not
be the best format for a model needing real-world
data in low latency; a data lake can meet that
need. An architecture allowing both would be a
good thing.” Corporate IT professional,
software/internet
• “We can tackle more use cases with a unified
architecture that were either difficult or not
possible on DW or DL individually.”
Consulting/Professional service
(Source: Q2 2021 TDWI Best Practices Report
on the Unified DW/DL)
13. Summary
• Organizations are collecting newer data types for analytics
• As part of this, they need to evolve their architectures. As organizations
evolve their architectures, they are moving to the cloud. Some are trying to
better architect and unify their environments
• Of course, organizational data resides in a variety of sources, including
legacy systems and SaaS applications.
• This can impact on processes like data integration, data governance, etc.
• Mobilization involves access, understanding, trust, and movement/update
• Organizations are looking for tools to help to mobilize their data
37. Legacy sources
cannot be
left behind
of executives say their customer-
facing applications are completely
or very reliant on mainframe and
IBM i processing.
Forrester Consulting, 2019
55%
Your traditional systems
– including mainframes, IBM i
servers & data warehouses –
adapt and deliver increasing value
with each new technology wave
72%
increase in transaction volume
on mainframe environments in
2019
BMC 2019
$1.65trillio
n
invested by enterprise IT
to support data warehouse &
analytics workloads over the past
decade
Wikibon “10-Year Worldwide Enterprise IT Spending 2008-2017”
38. What happens when legacy data is unlocked?
Enhanced BI and
analytics
Improved data
discovery
Data
democratization
with governance
Critical data
available for next-
gen projects – AI
and ML
39. Connecting mainframe
and IBM i to Snowflake
Bring rich transaction data to
the cloud
Improve cloud analytics and
insights
Speed delivery of information
Scale with next-generation
initiatives
40. Connect and Snowflake
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 capabilities
on-prem, in cloud or hybrid
environments
Mainframe
41. Customer Story
• Connect leverages IBM i journals to identify inserts, updates, and
deletes across over 1000 tables, replicating those to Snowflake in
near-real-time.
• Installation and proof of concept configuration was complete in 2
weeks, with IT able to demonstrate value to the business quickly.
• Sales now has greater visibility into the operations of subscribers,
seeing data that is fresher than the old ETL processes could provide.
• Core business operations continue to run on the IBM i while strategic
modernization initiatives can push forward on Snowflake.
About
New Zealand broadcasting company that offers
satellite pay TV with 70+ channels, sports and
entertainment streaming services, and broadband
internet service. Sky NZ has more than 990,000
customers and 990 employees, and was the first to
bring an all-digital and high-definition experience to
New Zealanders
Problem
Ability to derive business insights was hampered by
data silos. Billing, subscriber management, financial
management, and chart of accounts all run on core
IBM i platforms. Existing bespoke ETL processes
were slow to run and painful to maintain. Sky
needed to move faster, requiring data be delivered
in Snowflake in a near-real-time fashion.
Solution
Precisely Connect
Snowflake
44. CONTACT INFORMATION
If you have further questions or comments:
Fern Halper, TDWI Tarik Dwiek
fhalper@tdwi.org @fhalper tarik.dwiek@snowflake.com
Ashwin Ramachandran
aramachandran@precisely.com
tdwi.org