Modernize your Infrastructure and Mobilize Your Data

Fern Halper Ph.D.
VP and Senior Director, TDWI
Advanced Analytics
Modernize Your Infrastructure and
Mobilize Your Data

FERN HALPER
VP, Senior Research Director for
Advanced Analytics
TDWI

DATA TRENDS WE SEE AT
TDWI
Copyright © 2021 TDWI

A Complex Data
Environment
Modernization is
critical
Volume and types of
data are increasing
Data Volume
> 50%
Already manage 10s of TB of
data, Of this,10% manage
PBs
Modernize platforms
> 45%
State that they need to
expand their data warehouse
strategy

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

Data resides in
numerous systems
(% data by system type)
0% 5% 10% 15% 20% 25% 30% 35% 40%
RDBMS (e.g., SQL server, Oracle,…
SaaS applications (e.g., Salesforce,…
NoSQL database
Graph database
Time series database
Non-SaaS applications
1-25%
0% 5% 10% 15% 20% 25% 30% 35% 40%
RDBMS (e.g., SQL server, Oracle, etc.)
SaaS applications (e.g., Salesforce, Workday)
NoSQL database
Graph database
26-50%
0% 5% 10% 15% 20% 25% 30% 35% 40%
RDBMS (e.g., SQL server, Oracle,…
SaaS applications (e.g., Salesforce,…
NoSQL database
Graph database
>50%

Organizations
want to perform
analytics using
data from
multiple
sources
• Enriched data for customer behavioral
analysis
• Sensor data and other internal data for
proactive maintenance
• Internal and external data for risk
analysis.
Median number of data sources: 11-25

0% 10% 20% 30% 40% 50% 60% 70%
Tools for analytics on premises
Data warehouse on premises
Tools for data integration on premises
Tools for analytics in the cloud
Tools for data science on premises
Data warehouse in the cloud
Data lake in the cloud
Tools for data integration in the cloud
Tools for data science in the cloud
Data lake on premises
Other
In your analytics data ecosystem today, which of the following are in
production?
Organizations are evolving
their DM strategies to the cloud
Converged platforms too

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)

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
Other
We don't need a data lake at this time
Not enough information on how to get started
Lack of data privacy compliance
Our inadequate skills for big data
Poor quality of big data
Interoperability with existing systems or tools
We already have a data lake complementing…
Risk of exposing sensitive data (e.g.,…
Immaturity of the data lake concept
Lack of compelling business case
Lack of data integration tools and skills
Lack of business sponsorship
Our inadequate skills for designing big data…
Our inadequate skills for data lake design
Lack of data governance
In your organization, what are the most likely barriers
to implementing a data lake that complements and
integrates with an existing data warehouse?
There are challenges,
too

0% 10% 20% 30% 40% 50% 60% 70%
Other
In-memory functions
Event processing tools
Microservices for data
Data prep tools
Orchestration and workflow management tools
Interface and API management
Self-service for data access and exploration tools
Business glossary
Data pipelining tools
Data dictionary
Data lineage tools
Data quality tools
ETL tools
Data catalog
Assuming the coexistence of a data warehouse and a
data lake in an analytics ecosystem, which of the
following tool types can help to unify the two by enabling
integration, interoperability, and cross-platform
processes?
Organizations looking
to various tool types
to help to mobilize data

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

TARIK DWIEK
Head of Technology Alliances
Snowflake

© 2021 Snowflake Inc. All Rights Reserved
MODERNIZE YOUR
INFRASTRUCTURE AND
MOBILIZE YOUR DATA -
SNOWFLAKE OVERVIEW
Tarik Dwiek - Head of Technology Alliances

DATA SILOS PREVENT VALUE REALIZATION
Finance
Web/
Log Data
Product
Usage
Agencies OLTP
Databases
IoT
Enterprise
Applications
Sales Suppliers Third-Party
87%
of firms are expanding
their ability to source
external data1
1 “The Insights Professional's Guide To External Data Sourcing” Forrester, 2020

THE DATA CLOUD IS A GLOBAL NETWORK
18
One global, unified system connecting companies and
data providers to the most relevant data for their business

ACCESS GOVERNANCE ACTION
UNLOCK
YOUR DATA
PROTECT
YOUR DATA
KNOW
YOUR DATA
3RD PARTY
DATA
ECOSYSTEM
DATA
ANALYSTS
PRODUCT
DEV TEAMS
BIZ DEV
TEAMS
DATA
SCIENTISTS
BENEFITS OF THE DATA CLOUD
ORGANIZATION
DATA

© 2021 Snowflake Inc. All Rights Reserved 20
PROVEN BY THOUSANDS OF CUSTOMERS

THE DATA CLOUD TODAY
A software company shares
terabytes of data with hundreds
of customers
COVID-19 data is available live on
Snowflake Data Marketplace from a
US State, and other organizations
Today’s financial data is
accessible immediately without
data pipelines
Thousands of companies share
data with suppliers, partners, or
other business units
* Visualization based on actual Data Cloud sharing activity as of July 31 2021
THOUSANDS OF
ORGANIZATIONS
ARE SHARING
DATA WITH
THEIR
ECOSYSTEM

PLATFORM
ELEMENTS
OF THE
DATA
CLOUD
+
CONTENT
Applications Customer
Data
3rd Party
Data
Data
Services
SaaS
Data
Partner
Data

PLATFORM REQUIREMENTS
23
FAST FOR ANY
WORKLOAD
IT JUST
WORKS
CONNECTED TO
WHAT MATTERS
Run any number or type of
job across all users and data
volumes quickly and reliably.
Replace manual with automated
to operate at scale, optimize costs,
and minimize downtime.
Extend access and collaboration
across teams, workloads, clouds,
and data, seamlessly and securely.

SNOWFLAKE PLATFORM
Under the hood

ELASTIC PERFORMANCE ENGINE
Data science
ETL
BI/Visualization
Dev/QA
One engine for every workload
Simplify your architecture. Power complex
pipelines, analytics, data science, interactive
applications, and more.
Leading performance and concurrency
Fast, reliable performance every time with no
tuning or contention. Instantly and cost-
efficiently scale to any amount of users, jobs, or
data.
Support any user or skillset
Get the accessibility of SQL, with the flexibility
to support Java, Scala, Python, and more. Run
external tools directly for extended capabilities.

MAINTENANCE
& TUNING
Automated and fully managed for you
Focus on what matters. Fully managed with
automations that encrypt data, control access,
and eliminate manual maintenance and
troubleshooting.
High availability, high reliability
Automate complex replication and failover
cross-clouds and cross-regions. Stay up-and-
running no matter what happens.
Optimized costs for all data
Usage-based model paired with patented
compression and fine-grained controls to right-
size costs. Continual improvements for new
efficiencies.
INTELLIGENT INFRASTRUCTURE
Snowflake Managed
MULTI-CLUSTER
COMPUTE RESOURCES
ADMINISTRATION
NETWORKING &
ENCRYPTION
DATA
MANAGEMENT
CENTRALIZED
STORAGE

SNOWGRID
AWS GCP
Azure
Snowflake Regions
Maintain global business continuity
Eliminate disruptions, deliver better experiences, and
comply with changing regulations through unique cross-
cloud, cross-region connectivity.
Share data with no ETL or silos
Remove the barriers to data, regardless of cloud, region,
workload, or organizational domains. Get instant access
and distribution through a single copy of data.
Cross-cloud governance controls
Simplify governance at scale with flexible policies that
follow the data for consistent enforcement across users
and workloads.
Tap into the extended ecosystem
Enrich insights with a network of third-party data.
Discover and run new functions for extended workflows.

© 2021 Snowflake Inc. All Rights Reserved 28
Traditional Methods
Copy and move data
Data is delayed
Costly to manage and maintain
Unsecure, once data is moved
Error prone; pipelines break
SNOWGRID UNLOCKS DATA SHARING
Snowflake
FTP | APIs | ETL | Cloud buckets Secure Data Sharing
Single copy of live data, no delays
No costs of moving, copying, ingestion
No more data lake silos
Privacy compliant
Governed, revocable access

SHARE AND COLLABORATE IN THE DATA CLOUD
DISCOVER AND BE DISCOVERED
IN THE DATA CLOUD
SHARE ACROSS YOUR
BUSINESS ECOSYSTEM
Access data and services
from 150+ providers
SNOWFLAKE DATA
MARKETPLACE
Market and deliver your
products to customers
DIRECT SHARE
Share with other
Snowflake customers
YOUR
EXCHANGE
DATA EXCHANGE
Administer group sharing
and data discovery across
business units
READER ACCOUNTS
Share with companies not
yet on Snowflake
YOUR
ACCOUNT

CONNECT TO THE MOST RELEVANT CONTENT
Discover and be discovered with data
and services from 150+ providers across
16+ categories.
Thousands of companies share data with
suppliers, partners, or other business units.
Hundreds of applications that businesses
rely on run in the Data Cloud.
SNOWFLAKE DATA MARKETPLACE
SNOWFLAKE CUSTOMERS
POWERED BY SNOWFLAKE APPLICATIONS
Partner
Data
Applications
Data
Services
Customer
Data
3rd Party
Data
SaaS
Data

DATA CLOUD GROWTH
Oct 2021
April 2020

SNOWFLAKE CUSTOMERS SEE
SIGNIFICANT BENEFITS
32
84% 96% 95%
of customers surveyed
decreased administration effort
through use of Snowflake
of customers surveyed able
to better manage organizational
risk and decrease cost of service
of customers surveyed
achieved more of a
competitive advantage
RISK
COST
GROWTH

BUSINESS IMPACT OF SNOWFLAKE
33
The Total Economic Impact of Snowflake’s Cloud Data Platform, a commissioned study conducted by Forrester
Consulting on behalf of Snowflake
https://www.snowflake.com/resource/2020-forrester-tei-report/
Return on
Investment over
3 years
612%
50%
75%
Faster Time to
Roll Out the
Business Product
Reduction in
Effort for the IT
Support Team

THANK YOU

ASHWIN RAMACHANDRAN
Senior Director of Product
Management, Data Integration
Precisely

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”

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

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

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

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

Modernize your Infrastructure and Mobilize Your Data

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

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