Data Governance Workshop

CCG:
Upcoming Workshops
Analytics in a Day Ft. Synapse Workshop | March 16th | 9:00 AM – 1:00 PM EST
• Learn how to simplify and accelerate your journey towards the modern data warehouse.
Introduction to Machine Learning Workshop | March 23rd | 9:00 AM – 11 AM EST
• Designed to provide you with an overview of machine learning concepts, real world applications, and some user-friendly tools.
Data Modernization in a Day | March 30th | 9:00 AM – 12:00 PM EST
• This workshop will cover everything from whiteboarding migration strategies to hands-on experiences with data migration tools.
Analytics in a Day Ft. Synapse Workshop | April 20th | 9:00 AM – 1:00 PM EST
• Learn how to simplify and accelerate your journey towards the modern data warehouse.
Data Governance Workshop with CCG+Profisee | May 4th | 9:00 AM – 12:00 PM EST
• Learn how leveraging an MDM strategy within the context of Data Governance drives organizational alignment, ensures data quality, and
accelerates Digital Transformation.
Read more and register at ccganalytics.com/events
Follow us on LinkedIn @CCGAnalytics to stay up to date on events

CCGDG
Data Governance Workshop

Agenda
Housekeeping
Introductions
Data Governance (DG) Workshop
– Fundamentals of DG (Drivers &
Benefits)
– CCGDG Framework; Top 5
Components of An Effective
Data Governance Program
– Quick Break
– Competency/Marker Level
Analysis and Scoring
– Prioritization

PLEASE POST QUESTIONS
IN THE CHAT!
PLEASE MUTE YOUR LINE
WHEN NOT SPEAKING!
CCG WILL CONTROL
MUTING AND UNMUTING.
LINKS:
SEE CHAT WINDOW
WORKSHEET:
SEE HANDOUTS WINDOW
THIS SESSION WILL BE
RECORDED.
WE WILL SHARE SLIDES
WITH YOU.
TO MAKE PRESENTATION
LARGER, DRAW THE
BOTTOM HALF OF SCREEN
‘UP’
Housekeeping

How We Do The Work of the Workshop
Worksheet
• We supply you with this blank Word document for you to
fill out as we go through the Workshop.
• It is your private set of takeaways that you develop from
the Workshop.
Interactive
• The intention is for the workshop to be as interactive as possible.
• Please ask questions, or make comments, at any time in the chat.
• Make sure to participate via the EasyRetro links when prompted:
https://easyretro.io/publicboard/kRrYZ45adsOKCd4ni0xJTtlp8fe2/5
8e43325-74ba-410d-938e-747c926c082a
• Sami will share the link in the GoToWebinar Chat

Data Governance Specialist, CCG
Forrest has designed and led data governance program implementations
at multiple clients across a variety of operating models and industries
while leveraging CCG’s RapidDG Framework & Methodology. He is also
experienced in Business Analysis & Intelligence, Model Governance, and
Metadata Management. His industry experience spans across Finance,
Tech, Retail, Lottery & Gaming, Restaurant & Hospitality, Logistics, Digital
Media, and Real Estate Investment Trusts.
Contact: fhook@ccganalytics.com
Learn more by clicking on the links below:
https://ccganalytics.com/solutions/data-governance-data-
management
www.linkedin.com/in/forresthook
Forrest Hook

Data Governance Expert, CCG
Ahmet Temizsoy is a data and analytics leader with 20 years of
experience in data industry and specialism in the areas of strategy,
governance and quality. Through his career, Ahmet took leadership on all
parts of data lifecycle from acquisition to curation and from insights
creation to value generation and risk mitigation. Ahmet has the
experience of supporting both start-ups and Fortune 500 companies in a
variety of sectors with an ability to guide on best-practices in a data
domain agnostic manner.
Contact: atemiszoy@ccganalytics.com
Learn more by clicking on the links below:
https://ccganalytics.com/solutions/data-governance-data-
management
https://www.linkedin.com/in/ahmet-temizsoy-95428913/
Ahmet Temiszoy

Case studies available on our website:
https://ccganalytics.com/resources/case-studies
CCG Quick Facts
Microsoft Gold Partner in Data Analytics and Cloud. Our consultants have a
passion for helping clients overcome business challenges by leveraging modern
analytic solutions.
Corporate HQ– Tampa, Florida
Founded by 4 former Arthur Andersen consultants (they still own 100% of
our company)
Data & Analytics Solutions & Services since 2006

CCG Data Governance Solutions
Data Governance is a journey, and CCG offers a range of solutions to meet you where you are.
From accelerating your DG Program launch to leading your DG initiatives, we have the expertise to guide you at every step.
• Data Quality Program
• Master Data Mgmt.
• Metadata Mgmt.
• Model Governance
• Privacy Assessment
• Tool Selection & Implementation
• Data Warehouse Health Assessment
DG Implementations
Gain insight into your organizations need for
data governance and what you can do to
improve your success using this lightweight
framework that delivers an actionable
roadmap to guide your next year of data
governance.
• DG Operating Model Completion
• DG Roadmap Oversight & Execution
• Business Case Development
• Communication Planning
• Corporate Training & Education
• Policy Assessment & Gap Analysis
• Workflow Design & Implementation
• Budget & Resource Planning
DG Enablement
CCGDG
RapidDG Accelerator

Virtual Introductions
Name, Company, Title, What do you hope to get out of today’s workshop?

2
Assess your organizations DG needs using the proven
CCGDG framework
Develop an actionable plan
3
1
Describe what Data Governance is, key drivers, and
benefits
1
Workshop
Learning
Objectives

Take one minute to write a short definition of data governance in EasyRetro.
Defining Data Governance (DG)
https://easyretro.io/publicboard/kRrYZ45adsOKCd4ni0xJTtlp8fe2/58e433
25-74ba-410d-938e-747c926c082a

Data Governance Defined
What is Data Governance?
Data Governance is the organizational approach to data and information management, formalized as policies and
procedures that encompass the full lifecycle of data, including acquisition, development, use, and disposal. - CCG
Data Governance is a collection of practices and processes
which help to ensure the formal management of data assets
within an organization - DATAVERSITY
The exercise of authority, control and shared decision making
(planning, monitoring and enforcement) over the management
of data assets. - DAMA
Data governance is the specification of decision rights and an
accountability framework to ensure the appropriate behavior in
the valuation, creation, consumption and control of data and
analytics. - Gartner

 The enterprise is responding to a specific issue or problem (e.g. data
breach or audit).
 The enterprise is facing a major change or there is a potential regulatory
threat to the organization (e.g. GDPR, acquisitions, or preparing for a
public offering)
Passive
Reactive
Proactive
Levels of Data Governance
 There are some aspects of DG employed within the organization, but
there are no enterprise standards in place (e.g. the IS team has
developed a data dictionary)
 The enterprise recognizes the value of data and has decided to treat data
as a corporate asset (e.g. recruitment of a CDO, budgeted DG program,
etc.)

Increase Revenue
 Improve profitability with better
analytics for improved decision making
 Increase opportunity through
availability of information for business
insights and competitive advantage
Business Drivers & Benefits of Data Governance
Reduce Cost
 Create standardized and high-quality
information through operational
efficiencies
 Lower IT costs by mitigating duplicate
work effort or re-work
Minimize Risk
 Reduce regulatory compliance risk
and improve confidence in operational
and management decisions
 Improve reporting to regulators and
authorities through defined data
processes and data management

CCGDG establishes five proven competencies that are
the backbone of our data governance framework.
CCGDG Framework
CCG believes that there is no "single" way to
organize Data Governance.
“All models are wrong, but some are useful” -
George Box
We needed to assess faster, deriving actionable
insights that could be quickly implemented with
minimal disruption.
To achieve this, we developed a more lean,
simplified, & targeted framework and
methodology.

I don’t trust my data
(Data Quality)
Data architecture is the wild,
wild west
(Information Architecture)
There is no single way to
request data/reports
I don’t know how my metrics
are defined
(Metadata Management)
I can’t tell you what source
system the data came from
(Metadata Management)
I don’t know who has access to
the data
I don’t know who is responsible
for the data
(Program Management)
We don’t classify or manage
sensitive data
I’m not sure what policies and
procedures exist for approving
access or if they’re up-to-date
(Data Privacy)
I’m responsible for
implementing GDPR or CCPA
and I have no idea where to
start
(Data Privacy)
Most Common Challenges/Themes
What are your challenges?

We will return in 5 minutes
Quick Break

At CCG, we measure maturity across 5 competencies, each comprised of several
markers. We rate Program Management on a 1-5 scale, and the others on a 1-3 scale.

The organization of resources and employees to
achieve business goals through action items, processes
and policies.
Program Management
What are your
challenges & ROI?
Post in EasyRetro!
Marker Definition
Organizational
Structure
The units of the enterprise that carry out Data Governance, their responsibilities and scope,
and how they work together.
Strategic
Positioning
The alignment of data governance to the strategic goals of the enterprise. Understanding your
organizations strategic positioning is key to the success of a DG program.
Data Literacy
Support for everyone in the enterprise to have the basic skills to work with data and obtain
reliable results with it. The ability to read, write and communicate data in context, including
an understanding of data sources and constructs, analytical methods and techniques applied.
Education &
Training
Activities for the improvement in the capacity of users in the enterprise to better understand
and work with data. Data specific onboarding best practices usually consist of privacy policies
along with where to find and how to access data.
Policies &
Standards
The processes to formulate and promulgate data policies and standards to improve data
governance and management across the enterprise. Data policies and procedures provide a
broad framework for how decisions should be made regarding data.
Organizational
Change
Management
Driving cultural change in the enterprise for the successful adoption of Data Governance. How
users are equipped with the awareness, desire, knowledge, and ability to adopt change.
Includes reinforcement of new ways of working.
SharePoint

1
Shared
Accountability
Governance is centrally
controlled. Adherence is
measured. Continuous
monitoring and program
improvements are made
as the organization scales.
Emerging
Enterprise-wide DG
Program planning &
requirements gathering
has begun.
Business units are
primarily siloed and
making governance
decisions locally.
Sponsored
An enterprise-wide
sponsored DG Program
has been defined.
Business units are
encouraged to adhere.
Adoption in critical
business units started.
Undisciplined
There is no Enterprise-
wide DG Program or
enterprise support.
DG is not considered a
priority and/or is managed
locally within individual
business units.
2
3
5
Data Governance Program Management
Maturity
Capability
4
Enforced
The enterprise-wide DG
Program is well
established. Adherence is
mandatory for assigned
business units.
Business units rely on the
Enterprise Data
Governance for direction.
Organizational Structure | Data Literacy | Strategic Positioning | Education & Training
Policies & Standards | Organization Change Management
Rate yourself!

What are your
challenges? Post in
EasyRetro!
Information Architecture is a broad term that refers to the
set of policies, standards, functions, methods, processes,
procedures, tools, and models that govern and define the
type of data, information, and content collected, and how it
is used, stored, managed and integrated within an
organization and in and between its data stores.
Information Architecture
Marker Definition
Self-Service
Analytics
The support needed from a data perspective to help end users develop their own reports and
analytics. Line-of-business professionals are enabled and encouraged to perform queries and
generate reports on their own, with nominal IT support.
Information
Access &
Sharing
The mechanisms by which business users can discover data, request access to data, and satisfy
requests to use data. This involves ensuring data will only be used in permitted ways.
End User
Computing
The governance of data that is managed by business users outside of corporate applications.
This is usually, but not always data on endpoints such as personal computers. Are end users
editing output and improperly reporting findings?
Data Security
The ways in which Data Governance supports Information Security (or equivalent) in protecting
the information assets of the enterprise.
Business
Information
Models
Models that describe business information and its interrelationships without any concern about
how this information may be stored as data (i.e., without specifying any database design or
storage model). BIM represents the semantics of the data in an organization, and not a
database design.
Master Data
Management
MDM is the set of practices needed to manage Master Data. Mastering subject areas like
Customer and Product. Where subject area data is matched and merged across disparate
systems creating a Golden record applicable throughout the enterprise.
Azure Security
Center
Azure Synapse
Profisee
MDM
Azure Data
Factory
Azure Active
Directory
Azure Sentinel
Azure Data Share
Analysis Services

Information Architecture
Capability
Self-Service Analytics | Information Access & Sharing | Business Information Models
Data Security | Master Data Management | End-User Computing
Maturity
Adapting
1
2
3
Rate yourself!

What are your
challenges? Post in
EasyRetro!
The behavioral model through which the
administration and management of an organization’s
metadata resources can take place.
Metadata Management
Marker Definition
Data Catalog
A tool that assists in the governance and management of all data and information assets in an
enterprise. It may incorporate Business Glossary and Data Dictionary. An organized inventory
of data assets in the organization. It uses metadata to help organizations manage their data. It
also helps data professionals collect, organize, access, and enrich metadata to support data
discovery and governance.
Business
Glossary
A tool to manage and govern information assets at a busines conceptual level - usually business
terms and their definitions. Business glossaries help define terminology across business units to
break down data siloes. They offer clear definitions across the entire enterprise with the goal of
keeping terms consistent and helping everyone stay on the same page.
Data
Dictionary
A tool for inventorying all data stores and their components in an enterprise - usually relational
database schemas, tables, and columns. Descriptions can include data attributes, fields, or
other properties such as data type, length, valid values, default values, relations with other data
fields, business definition, transformation rules, business rules, constraints etc.
Data Lineage
The tracing of how data flows across a production data landscape. It can be at a high level
(dataset) or a low level (usually column) of detail. Data Lineage practices typically consists of
source to target documentation best practices in which data movement and transformation is
tracked.
Reference
Data
Management
The upkeep of data used to classify or categorize other data. Typically, they are static or slowly
changing over time. Reference Data is code tables & RDM is the governance and management
of these code tables. Over 50% of business semantics may be in these tables in any enterprise.
Business Rules
A form of metadata that express the guidelines an organization has established for using or
modifying a particular data element or data set. The governance and management of atomic
pieces to logic that are used in data management, e.g., for data quality, transformations,
calculations, integration, and so on.
Azure Purview
Excel

Capability
Maturity
Adapting
1
2
3
Metadata Management
Data Catalog | Data Dictionary | Business Glossary
Data Lineage | Reference Data Management | Business Rules
Rate yourself!

The ongoing maintenance of data to ensure
completeness and accuracy.
Data Quality
What are your
challenges? Post
in EasyRetro!
Marker Definition
DQ Program Management The overall organization of a data quality program with roles and responsibilities.
Issue Management
Processes to determine a possible resolution for a particular data quality issue.
How DQ issues are identified, escalated, tracked, and resolved.
Measurement &
Monitoring
Ensure data quality meet thresholds and targets in production environments. Key
metrics need to be continually measured and monitored to determine DQ
effectiveness.
Systematic Controls
Operational data quality management through data quality rules and exception
resolution. Controls in system of record to ensure data quality, or controls and
checks as data is integrated into a reporting data store.
Azure Purview
Azure Synapse

Capability
Maturity
Adapting
1
2
3
Data Quality
DQ Program Management | Measurement & Monitoring | Issue Management
Systematic Controls
Rate yourself!

Legal Disclaimer
CCG Analytics Solutions & Services (“CCG”) is not a law firm, nor does it represent one. Therefore, neither CCG, nor any of its employees,
consultants, and sub-contractors provide legal advice on data privacy regulations (e.g., CCPA).
CCG expects that any enterprise that engages CCG leverages the enterprise’s Legal and Data Privacy experts, often with outside Counsel, to
interpret the data privacy regulation or law (e.g., CCPA) as they require.
Furthermore, CCG expects that the designated enterprise’s Legal and Data Privacy expert(s) participate throughout any engagement
involving CCG to provide advice, guidance and interpretation (along with advice and/or guidance from designated outside Counsel) of the
impact of the data privacy regulation or law (e.g., CCPA) on the enterprise.
CCG’s role is not to provide this advice and/or guidance, but rather CCG partners with the appropriate enterprise Legal and Data Privacy
experts and other key personnel in Data Governance, IT, Risk, Procurement, etc., to translate the Legal and Data Privacy experts’
interpretation into operationalized practices supporting data privacy compliance.
CCG does not guarantee compliance with any applicable laws and/or regulations (e.g., CCPA) in any jurisdictions (e.g., European Union.) The
expectation is that the enterprise reviews and vets the CCG work products – including, but not limited to - content, deliverables, Readiness
Assessment tools (e.g., CCPA) – essentially all artifacts – with accredited legal experts for final opinions.

The practice of ensuring appropriate controls around data
to ensure only a minimally acceptable amount of risk.
Data Privacy
What are your
challenges? Post in
EasyRetro!
Marker Definition
Compliance &
Ethics
Dealing with regulations that specify what may or may not be done with data, or how data is
to be governed. Ensuring that data is managed and used in ways that are aligned to the values
of the enterprise, irrespective of the existence or non-existence of any relevant regulations or
contracts.
Retention &
Disposition
The processes needed to specify how long data should be kept for, and the processes for
purging or anonymizing data. A retention and disposition policy / schedule is a plan of action
that indicates the period an organization should retain records.
Data
Classification
The grouping of data into sets that have common governance or management needs. The
practice of formally tagging and classifying data in documentation and metadata to serve as
guidance in use of the data. Data classification also helps an organization comply with
relevant industry-specific regulatory mandates such as SOX, HIPAA, PCI DSS, and GDPR.
Consent &
Notification
Interactions with Data Subjects whereby aspects of data privacy are communicated to Data
Subjects, and agreement is obtained from Data Subjects regarding how their personal
information will be processed.
Process Register
An inventory of standard processes that are run against data, usually in the context of data
privacy laws like GDPR.
Licensed Data
Management
Ensuring that contractual terms for data that is acquired are in line with business strategy and
are fully respected.
Azure Purview
Azure Security
Center
Power
Apps
Blueprints

Capability
Maturity
Adapting
1
2
3
Data Privacy
Compliance & Ethics | Data Classification | Retention & Disposition
Process Register | Consent & Notification | Licensed Data Management
Rate yourself!

Increase Revenue
 Improve profitability with better
analytics for improved decision making
 Increase opportunity through
availability of information for business
insights and competitive advantage
Business Drivers & Benefits of Data Governance
Reduce Cost
 Create standardized and high-quality
information through operational
efficiencies
 Lower IT costs by mitigating duplicate
work effort or re-work
Minimize Risk
 Reduce regulatory compliance risk
and improve confidence in operational
and management decisions
 Improve reporting to regulators and
authorities through defined data
processes and data management
What are your drivers & benefits?
Post in EasyRetro!

Using your competency scores, prioritize your action items on your placemat.
Note down your specific findings and ROI!
Action Plan
Self-Service & Advanced Analytics Enablement
Master Data Management
Information Security & Democratization
Information
Architecture
Data Literacy
Clear Communication & Interpretation
Workflow Optimization
Metadata
Management
Cost & Risk Mitigation
Regulatory Compliance
Public Image & Customer Trust
Data
Privacy
Better Business Decisions
Optimal Insight
Trustworthy Data
Data
Quality
Operational Efficiency
Strategic Sponsorship & Support
DG
Program
Management
ROI
Write your findings here
Competency

2
Assess your organizations DG needs using the proven
CCGDG framework
Develop an actionable plan
3
1
Describe what Data Governance is, key drivers, and
benefits
1
Recap on
Learning
Objectives

Q&A
www.ccganalytics.com
Thank you for joining!
Email: sroetman@ccganalytics.com
Visit: www.ccganalytics.com

Azure Purview enables unified data governance
Reimagine
data governance
in the cloud
Set the foundation
for effective
data governance
Maximize business
value of data for
data consumers
Gain insight into
data use
across the estate

Today, BI extends to everyone
Everyone
Analyst to end user
IT to end user
2nd wave
Self-service BI
1st wave
Technical BI
3rd wave
End user BI

Turning data into business insights is challenging
Common BI challenges include…
Multiple data sources Data residing in cloud solutions and on-premise locations
is difficult to access and refresh securely
End-to-end view Data often resides in disparate locations, making it difficult
to see a complete picture of your business
Right data for the right
users at the right time
Different roles have different needs and business users
need the latest operational data

Why
Governance is
Needed
Plan ahead for self-
service BI success
Avoid uncontrolled
proliferation of BI apps
Implement processes
Proper governance
processes
Drive Decisions
Reduce Risks
Increase user adoption

Important
Considerations
If you don’t decide upfront, someone
else will later
Secure data uploaded to the service
Publish data to the entire organisation
Share content to external users
Publish to web
Custom visuals
Audit logs

Power BI
Governance
Considerations
Does BI start top down or bottom up?
Where does change start? Technology or people?
Who should be allowed to see and use business intelligence data?
Fail quickly? What do you mean by that and how does it apply to
business intelligence?
Environment Administration
Tenant Settings
Roles and Responsibilities
Enterprise Gateways
Security standards
Sharing
Environment and Reporting consistency
Published source data and business data models

Power BI Delivery Approaches
Business-Led
Self-Service BI
Bottom-Up Approach
IT-Managed
Self-Service BI
Blended Approach
Corporate BI
Top-Down Approach
Analysis using any type of
data source; emphasis on
data exploration and
freedom to innovate
Ownership:
Business supports all
elements of the solution
Scope of Power BI use
by business users:
Data preparation, data
modeling, report creation
& execution
Governed by:
Business
A “managed” approach
wherein reporting utilizes
only predefined/governed
data sources
Ownership:
IT: data + semantic layer
Business: reports
by business users:
Creation of reports and
dashboards
Governed by:
IT: data + semantic layer
Business: reports
Utilization of reports and
dashboards published by
IT for business users to
consume
Ownership:
IT supports all elements
of the solution
by business users:
Execution of
published reports
Governed by:
IT
Ownership Transfer
Over time, certain self-service solutions deemed as critical to the business may transfer ownership
and maintenance to IT. It’s also possible for business users to adopt a prototype created by IT.

Cloud Adoption Framework | Governance Model
Governance End State that fosters trust and builds confidence

Making Governance Actionable with Native Tools
• Azure Blueprints
• Azure Policy
• Azure Cost
Management
• Azure Advisor
• Azure Portal
• Azure EA Content
Pack
• Azure Policy
• Azure Security Center
• Azure Sentinel
• Subscription Design
• Encryption
• Hybrid Identity
• Azure Networking
• Azure Automation
• Azure Policy
• Azure Monitor
• Azure Advisor
• Resource Manager
Templates
• Resource Graph
• Management Groups
• RBAC
• Azure AD
• Azure AD B2B
• Azure AD B2C
• Directory Federation
• Directory Replication
• Azure Blueprint
• Azure Policy
• Resource Grouping
& Tagging
• Resource Manager
Templates
• Azure Advisor
• Azure DevOps
• Azure Site Recovery
• Azure Backup
• Azure Automation
Azure Monitor

For a complete list of Azure security tools
and services, see Security services and
technologies available on Azure.
The following list of Azure tools can
help mature the policies and
processes that support Security
Baseline.

© Microsoft Corporation Azure
Deployment Acceleration tools in Azure
The following is a list of Azure tools that can help mature the policies and processes that support this
governance discipline.

The following is a list of Azure native tools that can help mature the policies and processes that support this
governance discipline.

Azure Purview Features at Public Preview
Azure Purview Platform
Azure Purview Studio
Azure Purview Catalog (C1)
Automated Scanning & Classification
• Dedicated per customer on shared infra
• Provisioned default capacity with option to add-on capacity
Data Map
• Serverless, pay per use
• Includes connectors, scanning of sources, processing into data assets, lineage capture, classification
• Search, browse, asset details
• Automated metadata and lineage extraction
• Automated classification based on content inspection
• Private Endpoint
• Management center
On-prem & Multi-cloud* Operational, Analytical, SaaS*
Azure Purview Data Insights (D1)
* Power BI, SQL Sever on-prem, Azure Data Services including Synapse, Cosmos DB & Storage, Non-Microsoft systems including SAP ECC, SAP S4 HANA & Teradata, Multi-cloud systems including AWS S3
• Business Glossary templates
• Lineage visualization & workflows
Azure Purview Catalog included with Platform (C0)
• Catalog Insights (Asset, Scan, Glossary)
• Sensitive Information Types & Labeling insights
Data Producers &
Consumers
Data Officers &
Security Officers Power BI
SQL Server on-prem
Azure Synapse
Azure Data Services
M365 Compliance Center
Open APIs
(Apache Atlas 2.0)

CCG At A Glance
We are a team of strategists, technologists and business experts helping
forward-thinking organizations transform into intelligent enterprises guided by
analytics and insights. We empower optimized, real-time data driven
decisions and make data and analytics adoption pervasive so you can respond
quickly and intelligently to both crisis and opportunity alike.
DATA ANALYTICS SOLUTIONS
18
Years of
continued
growth
What we do
CCG helps organizations become more insights-driven, solve
complex challenges and accelerate growth through industry-
specific data and analytics solutions.
Case studies on our website:
https://ccganalytics.com/resources/case-studies

Strategy & Management
• Rapid Data Governance
Solution
• Rapid Analytics Roadmap
Solution
Services
• Health Assessments
• Strategic Roadmaps
• Master Data Management
• Meta Data Management
• Data Governance
Information Management
• Platform Modernization Solution
• Cloud Migration Solution
Services
• Data Integration
• Data Architecture
• Data Warehouses and Lakes
• PowerApps
• Cloud Management
• Cloud Migration
• DR/BC through Azure
• Azure Governance/Security
Analytics
• Leadership Development
• Customer Analytics
Services
• Dashboards and Visualizations
• Operational Reporting
• Self-Service
• Training
• Data Exploration
• Location Intelligence (GIS)
Data Science and AI
• RapidInsight with Machine
Learning Prototype Solution
Services
• Model as a Service
• Data Science as a Service
• Predictive Analytics
• Natural Language Processing
Machine Learning
• Artificial Intelligence
• Machine Learning Ops
CCG Solutions and Services

51
CCG Cloud Management Services
Cloud Migration
Planning to move to the Cloud? Our team specializes in
assessing your current environment, planning out the best
migration path for your company and executing a seamless
migration with minimal downtime.
Cost Optimization
Once resources are in the cloud, they must be proactively
managed to prevent run-away spend. Our team tracks usage
on a daily basis and implements automation for dynamic
scaling and deallocating resources that are not in use
Dedicated Engineering
Our team handles building, monitoring, and managing your
Cloud infrastructure. This includes architecting new buildouts
and ensuring security, networking and automation are all in
place and maintained daily.
Security
Securing the cloud is of the utmost importance. We develop
advance threat detection to receive live updates of any
threats so we can stop and possible breaches before they
begin

Data Governance Workshop

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Data Governance Workshop

Similar to Data Governance Workshop (20)

More from CCG

More from CCG (20)

Recently uploaded

Recently uploaded (20)

Data Governance Workshop