The document outlines the necessity and benefits of data and analytics modernization, emphasizing the importance of integrating new data sources and providing real-time access to enhance decision-making. It highlights the shift required in technology, skillsets, and processes to adapt to modern data demands, advocating for a structured data strategy as a foundation for successful modernization. Key aspects include employing advanced analytics tools, ensuring data quality, and planning for scalability and flexibility in data management.

1. THE PATH TO DATA AND
ANALYTICS MODERNIZATION
W
E
B
I
N
A
R
TONY DAHLAGER
VP, Data Management
Analytics8
KEVIN LOBO
VP, Analytics
Analytics8
The business demands driving modernization, the benefits of modernizing, and how to get started.

2. Unleash the power of your data
Analytics8 is a data and analytics consultancy.
We help companies make smart, data-driven decisions by
translating their data into meaningful and actionable information.
For us, data is not just data. It's an opportunity to innovate, support, and
transform. We know data is power and with it, we will help you unleash yours.

3. DATA AND
ANALYTICS
MODERNIZATI
ON
THE BUZZIEST OF BUZZ WORDS
IOT

4. TECHNICAL DEMANDS DRIVING MODERNIZATION
EXPONENTIAL
DATA VOLUMES
DIFFERENT
TYPES OF
DATA
DIFFERENT
TYPES OF
CONSUMERS
CLOUD, ON-PREM,
AND HYBRID
SYSTEMS
SCARCE AND
EXPENSIVE
TALENT

5. BUSINESS DEMANDS DRIVING MODERNIZATION
EXPLOSION OF
DATA VOLUMES
AND DATA VARIETY
TECHNOLOGY
GROWTH AND
CHANGE
HIGH QUALITY
AND
REAL-TIME
INFORMATION
ADVANCED
ANALYTICS
EVERYONE WANTS
TO GET THEIR
HANDS ON DATA

6. SO HOW DO YOU SOLVE MODERN DATA PROBLEMS?
You need a modern approach to data and analytics
to solve your modern data problems.

7. Modern data and analytics solutions are future-ready, scalable, real-time,
high-speed, and agile, enabling broader and better use of data.
WHAT IS DATA AND ANALYTICS MODERNIZATION?

8. THE BENEFITS OF MODERNIZATION
INTEGRATION OF NEW DATA SOURCES
Organizations can quickly integrate new data sources and host the rising data volumes as they need
to. With a modern data architecture, organizations can quickly access all data, pull in real-time data, and
analyze changes.
FASTER TIME TO INSIGHT
Giving users the ability to quickly find value in data, as well as ingest streaming data to analyze events as
they unfold.
DEMOCRATIZES ACCESS TO DATA
Rather than siloes of data, a modern approach stores data in one place, empowering users to run reports
and share analytics as needed in a secure manner.
PLANNING FOR THE FUTURE
With a modern data foundation in place, a modern data architecture paves the road for more advanced types
of analytics, such as artificial intelligence and machine learning.
SCALABILITY AND FLEXIBILITY
Cloud-based infrastructures can scale to meet growing analytics needs. Allows users to spend their time on
analysis instead of database operations.

9. HOW DO YOU GET THERE? WHAT IS NEEDED TO MODERNIZE?
Modernization starts
by creating a data
strategy and
roadmap which acts
as the foundation
and guide for your
data modernization
initiative.
Data
Strategy
You need an agile,
cloud-based, future-
ready data backbone
that enables easier,
faster, and more
flexible access to
large volumes of
data and different
data sources.
You must have a
modern approach to
data management in
order to manage
your data and turn it
into information that
can be used by the
business to make
decisions.
Migrating to newer,
next-gen analytics
tools provide better
analytics capabilities
including real-time
analysis, embedded
analytics, enhanced
collaboration, and
more.
A modernization
project isn’t just a shift
in technology, it’s a
shift in the skillsets
required within your
organization and the
processes for how
data is handled and
used. You need the
right people and
processes in place.
Data
Architecture
Analytics
Tools
Data
Management &
Governance
The Right
People and
Processes

10. MODERNIZATION STARTS WITH A DATA STRATEGY
Before you begin a modernization initiative,
you need to have a defined data strategy
which acts as the foundation and guide.

11. WHAT IS INCLUDED IN A DATA STRATEGY?
People
What do the employees
need in order to more
effectively use data?
Process
What processes are
required to ensure the
data is high quality and
accessible?
Technology
What technology will
enable the storage,
sharing, and analysis of
data?
Data
What data is needed?
Where is it sourced
from? Is it of good
quality?

12. The best strategies do not start with the data or technology.
Start with what the business wants to achieve and how data can
help you get there.
START WITH THE BUSINESS

13. TECHNOLOGY AND DATA STRATEGY
The landscape is getting more complex,
your plan should take all of these areas into consideration.

14. DATA MANAGEMENT & DATA GOVERNANCE
Once you have a data strategy, you need a plan for how to
execute that strategy.
This is where data management and data governance
come into view.

15. MODERN DATA ARCHITECTURE
IS JUST ONE PART OF
MODERN DATA MANAGEMENT

16. MODERN DATA MANAGEMENT
• All Your Data Together: Can you combine data from different sources and systems to see the big picture?
• Agility: How quickly can you make new data and information available to those who need it? Are you able to take
advantage of new technologies and innovations as they become available?
• Risk Management: Mitigate the risk of bad decisions based on poor data with a holistic approach to data quality that
spans the entire data lifecycle.
• Scalability, Stability, and Security: Cloud, On-Prem, Hybrid. Do you have confidence that your data will always be
available and only to the right audience?
Your data needs to be accurate and available to the right people at the right time.
All Your
Data
Together
Agility
Scalability,
Stability,
and Security
THE PILLARS OF MODERN DATA MANAGEMENT
Risk
Management

17. SOLUTIONS ARE NOT ONE SIZE FITS ALL
Not all organizations require the same data
architecture to be modern.

18. MODERN DATA ARCHITECTURE EXAMPLE
• A modern data
architecture builds
alternate, less
governed, less
latent pathways to
data.
• The data
warehouse is still a
central component.
• A modular approach
is resilient and
opportunistic.
Image Credit: Matt Bornstein, Martin Casado, and Jennifer Li. “Emerging Architectures for Modern Data Infrastructure”.
Andreessen Horowitz. March 22, 2021. https://a16z.com/2020/10/15/the-emerging-architectures-for-modern-data-infrastructure/

19. DATA LAKE APPROACH EXAMPLE
Data-Enabled
Apps
Data
Exploration
Data
Science
Enterprise
Reporting
Data
Visualization
Data
Warehouse
ETL
ELT
Social Media
IoT
Non-Relational
Operational
Systems
Relational
Operational
Systems
CRM
Data
Lake
ERP

20. The goal of data management is to maximize the value
that you create from your data in your organization.
That value is generated by analytics, when you
actually use data.
ANALYTICS TURNS DATA INTO MEANINGFUL INFORMATION

21. THERE ARE SO MANY OPTIONS…

22. MODERN ANALYTICS TOOLS

23. THE MIGRATION PROCESS
PICK YOUR TOOL
1. • Consider your entire data architecture
• Do a tool bakeoff
• Take it for a test drive

24. THE MIGRATION PROCESS
2
1. Pick Your Tool
2. ASSESS SKILL SETS
• Factor your people into your decisions
• Determine the skillsets needed with
new technology
• Plan for training and enablement

25. 1. Pick Your Tool
2. Assess Skill Sets
THE MIGRATION PROCESS
3. FOCUS ON INITIAL BUILD PHASE
• Take opportunity to triage and
revisit requirements
• Select high value reports and
applications for initial migration

26. 1. Pick Your Tool
2. Assess Skill Sets
3. Focus on Short Term
THE MIGRATION PROCESS
4. PUT TOGETHER ROLL-OUT PLAN • Achieve user adoption through
preparation and education

27. THE RIGHT PEOPLE AND PROCESSES
• Plan for both developer and end-user training
• Determine how your org will receive training
• Determine load balancing method

28. THE RIGHT PEOPLE AND PROCESSES
Don't just lift and shift.

29. • Include technology, people, processes, and data in your strategy
• Cut through the noise; focus on what your organization needs
• Adopt a modular approach that can respond to new trends, opportunities, and risks
• Understand it's a program, not a project
• Don't take a “lift” and “shift” approach
• Emphasize training to ensure user adoption
TAKEAWAYS: DATA AND ANALYTICS MODERNIZATION

30. QUESTIONS?
SUBSCRIBE TO THE 8 UPDATE NEWSLETTER • Analytics8.com
TONY DAHLAGER
tdahlager@analytics8.com
Analytics8
KEVIN LOBO
klobo@analytics8.com
Analytics8

31. MODERNIZATION QUICK START

32. We know data is power and with it,
we will help you unleash yours.