This document discusses how companies are moving workloads to the cloud and democratizing data and analytics. It notes that 85% of organizations will embrace cloud-first principles by 2025 according to Gartner. Implementing modern data integration is challenging due to issues like real-time data changes, skills shortages, data accessibility, budgets, and data quality. Data silos negatively impact companies through increased costs, missed goals, and poor customer experiences. The document promotes Precisely's data integration and catalog solutions for building adaptable cloud environments and breaking down data silos.

1. Democratized Data
& Analytics for the
Cloud
John de Saint Phalle | Senior Product Manager

2. Business trends influencing how companies
are moving to the cloud
Financial
responsibility for
IT expenditures
Data-centric cloud
computing
Democratized
data

3. “85% of organizations
will embrace a cloud-
first principle by 2025”
- Gartner
“55% of leaders site
data modernization
as the reason for
their shift to cloud”
- Deloitte
“Approximately
$100 billion of wasted
migration spend is
expected over the
next three years”
- McKinsey & Company

4. Implementing a modern data integration
framework isn’t easy
Confidential: Prepared for Precisely Customers and Prospects
0
10
20
30
40
50
60
Real-time
CDC
Skills Governance Data
Accesibility
Budget Data Quality Legacy
%
of
People
Who
Consider
this
a
Top
Challenge
(Rated
1
or
2)
1. Real-time CDC: Keeping data up to date,
accessing and processing data in real-time
2. Skills/Staff: Shortage of skills and staff who
have an understanding across cloud and legacy
technologies
3. Data Accessibility: Making data accessible to
users across the business
4. Budget: Spending on maintenance and not
innovation
5. Data Quality: Poor data quality and lack of trust
in data
6. Legacy systems: Difficult to leverage data from
legacy systems (mainframes, EDWs, IBM i etc.)
with modern cloud platforms
7. Scalability: Ability to scale with and process
massive data volumes
Q. What are your top challenges when it comes to
implementing a modern data architecture?

5. Data silos impact to companies
Expense Reduction
• $800K (annual) expense
reduction
• Today, 4-hour peak is ~1000
MIPS which costs the
enterprise $1.0M.
• An 80% cost reduction
($800K annually) is expected
once CDC is fully
implemented by reducing the
4-hour rolling avg.
Leveraging inaccurate
and incomplete data to
make decisions
Unable to meet
company goals
Diminished
performance
Organizational
Current architecture is
expensive to maintain
and scale
Missed SLAs
Technology
Increased costs
Value of cloud
investment decreased
Value of mainframe and
IBM i investment reduced
Financial
Deliver a poor customer
experience
Slower bringing new
revenue driving
applications to market
Customers

6. Democratizing customer data
for cloud analytics
IT need standards for infrastructure
while it remains seamless
to employees
Cloud applications and platforms need
to be fed data that can be trusted
Users demand flexibility

7. Building an environment that can adapt
1
Data sharing
models
2
Business process
changes
3
Cloud
environment
interoperability
4
Deep IT
management
integration

8. Precisely’s single solution for your
cloud integration needs

9. Cloud / VPC / On-Premises
Data
Integration
Data
Observability
Data
Quality
Geo
Addressing
Spatial
Analytics
Data
Governance
Data
Enrichment
APIs and SDKs
Enterprise
Business Systems
• Enterprise apps
• Analytics tools
• Precisely industry apps
• BI dashboards
• AI/ML
Enterprise
Data Sources
• Business Intelligence
• CRM
• Workforce mgmt.
• Data warehouse
• ERP
• Billing
Data Integrity services
Data Integrity Foundation Data catalog Intelligence Agents

10. Precisely leads with a data integrity vision
You’ve struggled with traditional solutions. We believe there’s a better way.
Data access owned by IT Collaboration between IT and business data users
Massive, loosely integrated solutions Just the scalable, interoperable capabilities you need
Data must be brought to the solution Workflows designed for the cloud that run alongside data
Slow, batch ETL processes Streaming data pipelines to the cloud
Separate business and IT metadata Scalable, shared catalog of business & technical metadata
Rules-based data management AI-driven quality rules, alerts, and data enrichment

11. Data Integration
Break down data silos by
quickly building modern data
pipelines that drive innovation

12. Data Integration differentiators
Real-time data streaming gives you fast access to fresh data when and where
you need it
Business-friendly user interface allows first-time users to create data pipelines
without coding
Build once, deploy anywhere principle allows you to build data pipelines in the
Precisely Cloud and deploy them wherever your data lives
50+ years of domain expertise in mainframe and IBM i systems is built into the
Data Integration module to handle your complex data sources
Integration with the Data Integrity Suite Foundational enables Data Integration
to share metadata with other modules - exponentially building value and spurring
innovation

13. Data Catalog features & benefits
Enables users to maximize value and innovation by connecting all the suite
services
Easily adapts to customer processes and languages without code because of
a flexible, pre-configured metamodel
Faster and more complete asset discovery with built-in intelligence that
identifies and semantically tags assets
A single searchable inventory of data assets built and maintained by
automated metadata harvesting that crawl, profile, and manage data
Users gain a geographic frame of reference with a robust collection of pre-
loaded, analysis-ready attributes that enrich their data

14. Thank you