1. Topic Module
Data Governance Part 1 - Introduction

2. Agenda Common concerns about cloud What is cloud Data Governance?
Five step Governance approach
Reimagining what’s possible

3. Common questions about the cloud3 ? 1 ? 4 ? 2 ?
Is my content safe in hosted data centers?
Who has access to my organization’s content in the service?
What visibility do I have into the activity on my content in the service?
Can I encrypt everything so that it’s not possible for you to have access to my content?
[:30] FOR MANY, THE SPEED AND SCALE OF CHANGE SERVES TO HEIGHTEN CONCERNS.
The question is how can you most responsibly and intelligently leverage the cloud to enable your own digital transformation?
JUST AS MANY ONCE HESITATED TO ENTRUST THEIR MONEY TO BANKS – THE DECISION TO TRADE ECONOMIC BENEFIT AND AGILITY FOR OPPORTUNITIES AND GROWTH RESTS ON ASSURANCE AND TRUST OF DEVELOPING SYSTEMS AND SAFEGUARDS.
In the remainder of our time here today, we’ll be helping you to answer these questions yourself – on your own terms, for your own situation – and simply showing you what we’ve learned in our efforts and the efforts of some of our most successful customers. That is, how to strategize, plan and incrementally accelerate you operations and opportunities using Data Governance and Classification as key methods and tools – as supported by the inherent and additional controls and safeguards available to you.

4. Balancing opportunities and risks
Transformation
Modernization
Cost
Agility
Security risks
Privacy breach
Downtime
Malware attacks
Data loss
[:15-:30] THE FUNDAMENTAL ISSUE: BALANCING OPPORTUNITY AND RISK
SECURITY IS THE KEY RISK TO ADDRESS. Security Risk can also include the inability to protect, manage and govern your growing volumes of data in a considered, cohesive, constructive way.
HOWEVER, ANOTHER IMPORTANT RISK TO CONSIDER IS LOST COMPETITIVENESS, EFFECTIVENESS, PRODUCTIVITY AND RELEVANCE.
Governments around the world have been seeking to leverage the many benefits of cloud computing but in recent months have struggled with concerns around highly sensitive government data that could raise national sovereignty issues. These legitimate concerns need not impede government progress in moving to the cloud. With robust data classification and Governance at the government agency or ministry level, governments can both address data sovereignty issues and reap the benefits of cloud computing.
Security strategy

5. Confidentiality How do I define and weigh my need for confidentiality?
Potential impact
Confidentiality
Preserving authorized restrictions on information access and disclosure, including means for protecting personal privacy and proprietary information [44 U.S.C., SEC. 3542]
The unauthorized disclosure of information could be expected to have a limited adverse effect on organizational operations, organizational assets, or individuals
The unauthorized disclosure of information could be expected to have a serious adverse effect on organizational operations, organizational assets, or individuals
The unauthorized disclosure of information could be expected to have a severe or catastrophic adverse effect on organizational operations, organizational assets, or individuals
Security objective
Low
Moderate
High
Personally identifiable information
Highly sensitive personally identifiable information
Financial information
Strategic plans
Mission critical resources
Sovereign data
Intelligence and defense
Can risk be mitigated by:
Obfuscation?
Masking?
Separation/segregation?
Encryption?
Authorization?
Aggregation?
[:30] UNDERSTANDING AND DEFINING CONFIDENTIALITY IS KEY TO STRIKING THE BALANCE
We all understand the what confidentiality is—or at least think we do. This workshop will help you define/confirm you premises in terms of gradations or levels which may help to expand your options and protections.

6. Integrity What data quality and integrity issues should I consider?
Potential impact
Security objective
Low
Moderate
High
Integrity
Guarding against improper information modification or destruction, and includes ensuring information non- repudiation and authenticity [44 U.S.C., SEC. 3542]
The unauthorized modification or destruction of information could be expected to have a limited adverse effect on organizational operations, organizational assets, or individuals
The unauthorized modification or destruction of information could be expected to have a serious adverse effect on organizational operations, organizational assets, or individuals
The unauthorized modification or destruction of information could be expected to have a severe or catastrophic adverse effect on organizational operations, organizational assets, or individuals
[:30] DATA INTEGRITY IS AN IMPORTANT ELEMENT – BUT PERHAPS MORE EASILY ADDRESSED WITHIN THE CONTEXT OF IT PLANNING and EXISTING METHODOLOGIES
Integrity is critical – but we’ll devote less focus to it today given the preponderance of verifiable technical strategies and remedies available to IT.
Validity
Integrity
Completeness
Accuracy
Timeliness
Consistency
Data quality
Dimensions of data quality:
Does the data look like what the business expects and reflect verifiable truth? (Validity and Accuracy)
Is data consistent and unique across business processes and systems? (Consistency)
Are the relations within and between data instances correct? (Integrity)
Is the data available at the time needed? (Timeliness)
Was all necessary data present? (Completeness)
Does the data meet regulatory standards and requirements (Compliance)?

7. Availability What requirements and opportunities must I balance?
Potential impact
Availability
Ensuring timely and reliable access to and use of information
[44 U.S.C., SEC. 3542]
The disruption of access to or use of information or an information system could be expected to have a limited adverse effect on organizational operations, organizational assets, or individuals
The disruption of access to or use of information or an information system could be expected to have a serious adverse effect on organizational operations, organizational assets, or individuals
The disruption of access to or use of information or an information system could be expected to have a severe or catastrophic adverse effect on organizational operations, organizational assets, or individuals
Security objective
Low
Moderate
High
Mission critical operations
Chain of custody
Business continuity/disaster recovery
Hyper scaling on demand
Long term retention
Regulatory compliance
9999s
Is my data essential to:
Multiple ecosystems?
Systemic health monitoring?
Secondary operations?
Analytics and reporting?
Key services?
[:30] AVAILABILITY – A KEY CLOUD VALUE – IS A THIRD IMPORTANT LEG OF YOUR BALANCING ACT.
Availability is a key cloud value/benefit. This is where we could perhaps go on too long in describing the varied “Cloud on your terms’ options available .
One note to strike here is perhaps the flip side of the coin—and that’s the KEY CONSIDERATION in balancing confidentiality. How much of your data’s value is blocked or locked from necessary primary and secondary uses or flow to those who need it to see, act, analyze, invent or apply it to operations, processes services, solutions? When we think about the Digital and Operational Ecosystems, we’ve discussed—are we overly hoarding our gold or enabling proper circulation and currency for shared services and systemic growth.

8. Data Governance: core to your information architecture strategy
Public Sector customers are gravitating to a “hub and spoke” Data Governance approach
Year 5
Year 4
Year 3
Year 2
Year 1 1
Place yourself where you currently are 2
Place yourself where you want to be in a 3 to 5 year time period 3
Build your plan
Where are you today?
Where do you want to be in 3 to 5 years?
Information protection and data quality
Data Governance in dashboards
Data Governance sponsor and steering committee
Infonomics
Enterprise content management and MDM
Data ownership
Basic
Reactive
Defined
Managed
Optimizing

9. Classification is key to effective Data Governance
Financial transactions
Personal sensitive data
Sensitive technology
Your data is not a single, monolithic entity.
Data classification provides a great model for collecting and organizing insightful information about your organization’s systems, workloads and data.
Impact
High impact data
Medium impact data
Low impact data
Value
High value data
Medium value data
Low value data
Controllability
Locally controlled data
Manually controlled data
Automatically controlled data
[:30] UNDERSTANDING YOUR DATA
YOUR PROTECTIONS, SAFGUARDS AND CONTROLS ARISE DIRECTLY FROM YOUR ABILITY TO UNDERSTAND AND DEFINE – CLASSIFY – YOUR DATA.
If you classify everything, everything’s “classified.” The key is to understand, distinguish, differentiate and delineate its characteristics so you can select the right strategy, solutions, safeguards and tools for its specific values, uses and “job.”
Organizationally sensitive data
Personal identifying data
Intellectual property

10. Classification as a key cloud control mechanism
Responsibility
IaaS
PaaS
SaaS
Data classification and accountability
Client and end point protection
Identity and access management
Application level controls
Network controls
Host security
Physical security
Organizational and service provider safeguards
Data classification and accountability
Client endpoint protection
Identity and access management
Application level controls
Network controls
Host security
Physical security
[:30] CLASSIFICATION REPRESENTS A KEY CONTROL MECHANISM WHICH INFORMS AND GUIDES YOUR STRATEGY, POLICIES AND Governance APPROACH.

11. Envision and accelerate your digital future with a Data Governance approach
We can help you to further envision and map your way toward a new, synergetic and self-sustaining public ecosystem—on your terms, tailored to your specific situation, priorities and citizen needs.
Explore vision, opportunities and goals within the context of your current plans
Envision
Confirm business scenarios, processes, approaches, and constraints
Discover
Define technical elements and requirements, specs for existing and future state
Define/design
Receive solution debriefing and review solution sketches to determine next steps
Review and map
For more information about Microsoft Services, contact your Account Manager or go to:

12. Enable modern business applications
What it is
It is a set of processes and controls for managing data by responsibly harnessing the power of the cloud; builds on the Trusted Cloud initiative
Why it is important
Enables business transformation, increases collaboration, reduces costs, delivers new insights, helps organizations meet standards for security, privacy, and compliance
[:30] WHAT IS CLOUD DATA Governance—AND WHAY IS IT IMPORTANT?
Data Governance is the exercise of decision-making and authority for data-related matters. It is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information and under what circumstances, using what methods
All organizations need to be able to make decisions about how to manage data, realize value from it, minimize cost and complexity, manage risk, and ensure compliance with ever-growing legal, regulatory, and other requirements.

13. Balance opportunities and risks
Transformation
Modernization
Cost
Agility
Security Risks
Privacy breach
Downtime
Malware attacks
Data loss
[:30+] BALANCING OPPORTUNITY AND RISK
In addition to the data controls and process management inherent in Cloud Data Governance, CDG is essentially a way of identifying, addressing and balance the “risks and rewards.” It’s both strategic and tactical: it informs and guides policies, procedures, performance measures and has greater intangible benefits – openness, transparency, trust, productivity, innovation – that grow “data culture”
Governments around the world have been seeking to leverage the many benefits of cloud computing but in recent months have struggled with concerns around highly sensitive government data that could raise national sovereignty issues. These legitimate concerns need not impede government progress in moving to the cloud. With robust data classification and Governance at the government agency or ministry level, governments can both address data sovereignty issues and reap the benefits of cloud computing.
Security strategy

14. Governance leads to good policy decisions
Organizational, processes, data protection and IT
Client Corporate Governance
Process Governance (ISO 18091)
Data Governance
Information Technology Governance (ISO 38500)
[:30 ] ASPECTS OF Governance – FOUNDATIONS FOR POLICY AND PLANNING
Data Governance is a key component of general Governance – GRC – and Cloud Data Governance, our focus, is a key element of general data Governance or information Governance. These of course all inter-relate and affect each other as whole system, but it’s good to identify and classify these parts AND KEEP THEM ALL IN MIND.
Collectively, these are the building blocks of institutional and infrastructural planning/management, but also the foundations of our “Data Cultures.”

15. Data Governance leads to a “data culture”
Mature, sustainable stewardship and data-driven operations
Real-time access to reliable data
Data-driven decisions
Self-service access for everybody within the organization
[:30] DATA CULTURE
What do we mean when we talk about data culture? It’s a potential broad and profound conversation which extends and applies to the entire systems and ecosystems on which we operate—not just our organizations.
In practical, organizational terms:
Management and staff need to make good decisions. They need to reach consensus on how to “decide how to decide.” They need to create rules, ensure that the rules are being followed, and to deal with non-compliance, ambiguities, and issues. In short, they need to do more than manage data; they need a Governance system that sets the rules of engagement for management activities.
Organizations with more complex data or compliance environments generally find that they need to step back and agree upon a more formal system of Governance.
With data security, patient privacy, and compliance with regulations among other issues facing business leaders today, many of those leaders in government and healthcare around the world are reconsidering their data management and Governance policies and practices.
Optional Extend/Support:
For example: Healthcare leaders, maintaining patient privacy while improving access to medical care, is of the utmost importance. Behind the scenes, removing information siloes and ensuring the correct labeling and tagging of data can be just as critical.
For government leaders, the ability to effectively wrap their arms around and capitalize on the overwhelming abundance of data they deal with on a regular basis, and using it in a purposeful, efficient and beneficial way for citizens and businesses is a constant battle. Perhaps even more perplexing, what data should be kept on-premises, which can be put in the cloud, and when can there be a mix?
What is Data Governance? -
Data Governance is not:
BI Governance because BI Governance deals with an organizations BI Architecture, standards and prioritization requirements.
Internet Governance because Internet Governance involves the principles, policies and procedures related to the use of the Internet throughout the organization.
Financial Governance because Financial Governance involves the strategic management of core business processes to achieve its financial goals.
I/T Governance because I/T Governance involves establishing the leadership and organizational structures and processes that ensure the organization’s I/T strategies and objectives are in-line with the company’ s business strategies and objectives.
Data Governance is also not:
A Help Desk for generic data questions.
A group for helping to implement process or technology.
Project Governance – yet a topic for another blog.
Involved in developing processes to address data policy decisions.
Involved in addressing immediate data production issues.
So then what exactly is Data Governance? In summary Data Governance is:
A strategic program where data policies are identified, evaluated and data solutions are prioritized.
Where key decisions about Information Management are communicated
A vehicle to ensure compliance and establish accountability around defined data policies and standards.
Involvement of data owners and data stewards with broad understanding of the data required for a set of business processes.
Development, institutionalization and socialization of policy, data standards, and information management processes.
Data Governance Objectives -
Data Governance Objectives
Improve decision-making of the management
Ensure data consistency
Build trust of data among everyone involved in the process
Adhere to compliance requirements
Eliminate risks related to data

16. Data Governance is core to information architecture strategy
Stakeholders and Participants
User Experience
Information Foundation
Citizens and public servants
Business data steward
Information worker and IT pro
Business data manager
Compute, network and storage
Engaging citizens, connecting agencies, and resourcing operations
Platform Foundation
Data Catalog (marketplace)
Find the right data
Reports and analytics
Use the right data
Data catalog (marketplace) Find the right data
Data canvas (semantic layer)
Connect the right data
Data Governance
Enterprise information architecture
Master data management
BI and analytics
Demand
Deliver
Cybersecurity and data loss protection
[:30] THINK OF DATA Governance AS THE FOUNDATION AND CORE OF YOUR STRATEGY -- SPECIFICALLY INFORMATION ARCHITECTURE
Collectively – based on these and other considerations – Data Governance is a core, critical element of any sustainable strategy to maximize your “Data Dividend.”
Optional Extend:
Do’s
“Aim for the middle”
Shared federated accountability
Strategic Business sponsorship
Support adoption, don’t just govern
Show maturity progress in the roadmap
Start Change Management ASAP
Don'ts
Don’t cross the middle line from either side – it becomes a Change Management nightmare
No centralized Overhead in an Ivory Tower just “churning out policies”

17. 5-step Data Governance framework
Executive sponsorship is crucial
Establish roles and responsibilities
Develop data strategy and policy
Set up stewardship model
Classify and catalog data
Develop change control processes
[:30-60] FIVE STEP FRAMEWORK
Here’s a simple, consistent overview of how we view Data Governance as a framework – there are different formulations and flavors, but this is essentially consistent with virtually all best practice models advocated by thought leaders around the world in industry, public sector, education etc.
As you can see, it’s an ongoing, iterative and—ultimately—self sustaining cycle. Today, we’re addressing classification as starting point which enables you to define data – applications, etc. – for further, formal action steps (e.g., team building, validation, strategy/policy, implementation). These steps “turn the Governance wheel” with increasing efficiency and strength.
Optional Recap (followed by specifics):
Start here -> Establish roles and responsibilities by collaborating Business and IT
Develop a strategy of what data should remain on-premises, reside as private information in the cloud or made public in the cloud (data as a service)
Setting up a stewardship model to ensure data ownership and eliminate risks
Create a catalog of data and classify risk through the stewardship model
Create feedback loops and change control processes for governing data

18. Establish roles and responsibilities
5/7/2018 1:57 PM
Establish roles and responsibilities
Involve executives early
Function
Outcomes
Best practices
Recruit executive sponsors
Identify owners for both business and technology—this is a journey that should be taken together
Identify legal council
Identify project management team
Identify citizen involvement
Executive sponsor communicates goals and objectives
Program management team established
Working groups established based on ownership areas
Regular progress meetings established
Organization chart that documents roles and relationships—stakeholder analysis
Roles and responsibilities documented
Recruit executive sponsors early
Engage citizens regarding usage scenarios
Consider policy maker’s interests
Provide monthly visibility
Avoid death by committee
Allow responsibilities to evolve organically
Look for the “outside-in” view or citizen view
[:30] ESTABLISH ROLES AND Responsibilities
If Data Governance is not already established or nascent, this is the first step: providing for holistic approaches, perspectives, responsibilities that support a cohesive, concerted approach on policy, stewardship and other levels. In terms of Classification, this also applies specifically? Who should govern or guide classification? What specialties, knowledge or focus is required to ensure your approach is stable, sensible, shared and sustainable?
Optional Extend:
Subject area owners
An important element of the EDM Governance Model is that each Subject Area is owned by a Business Leader, which in turn is supported by a Technical Leader.
Roles and responsibilities-
There are various roles involved in this process and all of them have to be accountable to ensure data quality. Its vital that the roles are clearly defined upfront. The following are some of the commonly recognized roles:-
Data Governance Council – comprises of an Information Management Head and Data Stewards from various units.
Information Management Head – is the one who is accountable to the Governance Council on all aspects of data quality. This role would typically be fulfilled by the CIO.
Data Stewards - are the unit heads who lay down the rules and policies to be adhered to by rest of the team. This role would usually be fulfilled by a Program Manager.
Data Custodians – are responsible for the safe storage and maintenance of data within the technical environment. DBA’s would normally be the data custodians in a firm.
Business Analysts – are the ones who convey the data quality requirements to the data analysts.
Data Analysts – are those who would reflect the requirements into the model before handing it over to the  development team.
Business Subject Area Owner
Target Members:
General Manager / Sr. Director.
Own or manage a significant business process or area that deals with the data subject.
Responsibilities:
Represent the business view, or identify delegate, for critical decisions around data within a subject area.
Drive EDM adoption in the business and operations teams.
Coordinate and facilitate issue resolution in subject area when multiple business stakeholders are involved.
Nominate and approve data stewards, funding and supporting their efforts, to drive and monitor execution on policies, standards and procedures.
Define priorities and authorize budget and resources for the business team to
Participate in the creation of EDM content.
Carry out corresponding change process for the subject area.
Technical Subject Area Owner
Own or manage IT group supporting significant business process or area that deals with the data subject.
Represent the IT view, or identify delegate, for critical decisions around data within a subject area.
Drive EDM adoption in the systems supporting business and operations teams.
Coordinate and facilitate issue resolution in subject area when multiple IT stakeholders are involved.
Work with Business Subject Area Owners to identify and support data stewards.
Assist in developing funding requests to drive and monitor execution on policies, standards and procedures.
Define priorities and authorize budget and resources for the IT team to
Develop road maps for systems supporting enterprise information.
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19. Develop data strategy Function Outcomes Best practices
5/7/2018 1:57 PM
Develop data strategy
Consider your entire Enterprise Information Management landscape
Function
Outcomes
Best practices
Identify a maturity model like Capability Maturity Model Integration (CMMI) and assess your current maturity and future level
Develop a road map of your three-to five-year plan
Think about maturity level in terms of capabilities, such as policy and stewardship, standardization and sharing, control and measurement, and education and adoption
Define data classification and information security policies
Define data quality policies and measurements
Framework that depicts and describes all the components of your data landscape
Maturity model that shows where you are and where you want to be
Road map with phased outcomes for the overall institution and individual agencies (as appropriate)
Written data classification policy; for example, adherence to ISO ISO/IEC :2014 for PPI data
Scorecards to measure adoption
Choose a maturity model that is right for you
Think “outside-in” and consider citizens and agencies first
Think data sharing rather than data control
Think big, but start small
Map progress on a regular cadence to the plan; learn and revise as needed
Communicate successes
Support adoption, don’t just govern
Show maturity progress in the road map
[:30-60] DEVELOP A STRATEGY
[Talk through]
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20. Set up stewardship model and catalog data
Empower users through stewardship and data culture
Function
Outcomes
Best practices
Assign and/or approve by the area owners
Make data useful to the business
Consistently use data across the business
Promote and achieve high data quality standards
Resolve data integrity issues across stakeholders
Assist in data classification process
Data stewards appointed
Training plan for data stewards to understand their accountabilities and work activities
Data steward roles and responsibilities clearly defined
Set up a community for data stewards so they can share knowledge
Collaboration is key—establish regular cadence and interaction
Place data stewards within organizations instead of in centralized IT
Enable the business to drive business data ownership
[:30-60] SET UP A STEWARDSHIP MODEL
[Talk through]
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21. Classify and catalog data
5/7/2018 1:57 PM
Classify and catalog data
Determine which applications live in the cloud vs. on-premises
Function
Outcomes
Best practices
Establish a data cataloging mechanism for data stewards
Set up a periodic review system to verify standards
Program for moving data to a cloud with proper protections in place
Government workers have a place to go to know what data exists and who can grant access to that data
Citizens have a place to go to know what public data is available
Discover and classify data as part of overall process
Ensure that everyone within the organization understands your data classification levels
Make classification part of your culture
Make data as transparent as possible
Explore ways to certify data as trusted
[:30-60] CLASSIFY AND CATALOG DATA
We’ll be diving into this in detail in the next sessions, but let’s touch briefly on several fundamentals within the context of the framework model.
[Talk through]
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22. Develop change control processes
5/7/2018 1:57 PM
Develop change control processes
Introduce organic change in a structured way
Function
Outcomes
Best practices
Establish a change control process that is consistent across your organization
Determine the results you want to achieve based on your road map
Look for vital behaviors that will achieve your results
Look at personal, social, and structural dimensions for making influential changes
Escalation process for dealing with issues
Routine reviews in place for determining what is going well and what can be improved
Documentation of results you are trying to achieve with concrete measurements
Plan focusing on high-leverage behaviors that will drive results
Consider multiple sources for change, such as personal motivation, personal ability, social motivation, social ability, structural motivation, and structural ability
Look at ways to change the culture through social media, such as Microsoft’s Yammer
Host contests on Power BI story within the organization
Use collaboration software for sharing best practices
[:30] CHANGE CONTROL PROCESSES
Source:
Most organizations have change management – or at least change control – mechanisms for technology. They usually have change management for software applications. They have change management for websites. And yet, many organizations do not practice structured change management for data.
Why is this important? Some types of data – master data and reference data – should have tightly controlled sets of valid values. These values appear in thousands and millions of transactions; without change control, different repositories storing master and reference data get out of sync.
One role of Data Governance is to set the scope of data-related change management and to oversee change management activities.
Optional Extend:
Examples of data-related change management are:
•Changes to allowable values for reference tables
•Changes to physical data stores that impact the ability to access or protect in-scope data
•Changes to data models
•Changes to data definitions
•Changes to data structures
•Changes to data movement
•Changes to the structure of metadata repositories
•Changes to types of metadata included in a metadata repository
•Changes to stewardship responsibilities
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23. Plan an incremental path to the future
Take a maturity-based implementation approach
Governance-focused organizations
Resource investments
Dynamic
People: Formal training and awareness program with compliance metrics
Process: Process transformation and more integrated compliance efforts
Technology: Fully automated and integrated controls
Risk management organizations
Rationalized
People: Formal training and awareness program with compliance metrics
Process: Process and procedure improvement
Technology: Reduced reliance on manual and compensating controls
Compliance-focused organizations
Standardized
People: Formal training and awareness
People: Polices and procedures established and communicated
Technology: Foundational/minimal
Basic
People: Lack of training and awareness
Process: Basic policies and immature procedures
Technology: Ad hoc/limited
[:30] PLAN AN INCREMENTAL, MATURITY BASED PATH
Wherever you are today, plan for tomorrow based on the maturity of your organization. The most perfect plan and system needs to work, now, with the people, processes and platforms you have in place.
Time
Governance, risk management, and compliance

24. How to get started Introduction Workshop Assessment Road map Solutions
Establish a common framework and definition of data Governance, and introduce Microsoft solutions and services
Explore customer requirements and goals, and share Microsoft capabilities
Assess customer goals, challenges, threats, requirements, and technical data Governance maturity
Outline strategic and tactical projects, with business goals and requirements
Implement data Governance solutions based on business goals
[:30} CDG PATH
We’ll take a look at the variety of options and approaches you have at the end of today’s workshop. One point to note is that you truly can—and should—ensure that any journey you undertake is on your terms and based on your individual needs and capabilities.
Microsoft Consulting Services - Security and Identity Offering -

25. Reimagining what’s possible
[:15] NOW ITS TIME TO TALK ABOUT YOU

26. Imagine—and govern—whole new possibilities
Today’s technology trends are sparking opportunity
Mobile
Enterprise social
Big Data
Cloud
Engaging customers and citizens
Connecting agencies, outlets and branches
Resourcing agile, scalable operations
Organizations
People have more information and new ways to connect
[:15] HOW CAN YOU RESPONSBLY AND INTELLIGENTLY PREPARE SIMILAR OPPORTUNITIES?
Data Governance

27. Reimagine the public sector with a data foundation
Improving
city-wide insights
Solving crimes
faster
Enabling doctors with mobile solutions
Empowering students with less cost
Reducing energy
use
City of Barcelona deploys a Big Data business intelligence solution to improve lives and create a “smart city” template for cities around the world
Thai law enforcement agency optimizes investigations with Big Data solution, reducing investigation time from two years to 15 days
AirStrip’s mobile cardiac care solution allows doctors to evaluate a patient’s EKG much faster
Department of Education Western Australia adopts cost- effective solution to provide better collaboration for students and teachers
City of Seattle aims to reduce downtown energy usage by 25 percent with a new “smart buildings” initiative
[:30] PUBLIC SECTOR EXAMPLES
Presenter Guidance: Illustrate that Microsoft understands the complex business issues that today’s enterprise is challenged with through the use of customer stories. Use local, industry-relevant examples where possible. Several examples from around the world and across key industries are also provided in the appendix of this presentation.
Optional Detail:
1) City of Barcelona - Barcelona is recognized as being at the forefront of innovation in city management, having implemented many initiatives that use technology to improve delivery of services to citizens, and increase productivity of employees. Due to their proven scalability and security, cloud services and devices from Microsoft support a number of key initiatives that the Barcelona City Council has implemented—both directly and in collaboration with Microsoft partners, including Big Data and analytics. OpenData BCN, supported by Windows Azure and utilizing business intelligence (BI) analysis tools through partner Bismart, which is also developing a Big Data application for the La Mercè festival using Microsoft SQL Server 2012., MORE DETAIL:
2) Thailand's Ministry of Justice, the Department of Special Investigation (DSI) - To reduce manual investigation processes, DSI wanted better tools for mining large sets of structured and unstructured data from multiple sources. DSI implemented a Microsoft Big Data Solution that uses business intelligence tools in Microsoft SQL Server 2012 with Apache Hadoop technology. The new solution cut investigation time from two years to 15 days
3) AirStrip’s AirStrip ONE® Cardiology app, the Windows Phone and Windows 8.1 mobile device cardiac care solution that allows doctors to evaluate an EKG much faster after a potential heart attack to know if a patient needs surgery, recently became the first FDA-cleared clinician app for the Windows 8.1 platform. See
4) The Department of Education Western Australia manages the learning for 265,000 students across 2.5 Million square kilometers. The Department’s key driver was cost effectiveness, availability and scalability for student collaboration and communication. The Department of Education was looking to replace the current suite for communication between for the students and teachers. Office 365 for Education addresses all student and Department requirements for a more cost-effective and function rich communication and collaboration solution. More detail:
5) City of Seattle - Working with the City of Seattle and its utility Seattle City Light, Microsoft has joined with the Seattle 2030 District, a public-private collaborative of downtown Seattle property owners and managers that has established a 50% energy use reduction goal by The pilot will increase energy efficiency in large commercial buildings across Seattle’s downtown corridor, the initial set of buildings totals approximately 2 million square feet. The intention is to expand the pilot over the next year. The cloud solution will collect data from the myriad systems in those buildings and use data analytics to provide a prescriptive approach to how the building management systems can be tuned to improve energy efficiency. At the center of this pilot is the Accenture Smart Building and Energy Solutions, which identifies and implements energy savings opportunities, alongside Microsoft’s Azure cloud technologyhttp://blogs.msdn.com/b/Microsoft-green/archive/2013/07/09/Microsoft-brings-smart-buildings-to-seattle.aspx

28. Next - Data Governance Part 2 – Data Classification

29. 5/7/2018 1:57 PM
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