Data Architecture Strategies: Building an Enterprise Data Strategy – Where to Start?

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  • Building an Enterprise Data Strategy Where to Start?

    Donna Burbank, Managing DirectorGlobal Data Strategy, Ltd.

    February 22nd, 2018

    Follow on Twitter @donnaburbankTwitter Event hashtag: #DAStrategies

  • Global Data Strategy, Ltd. 2018

    Donna Burbank

    Donna is a recognised industry expert in information management with over 20 years of experience in data strategy, information management, data modeling, metadata management, and enterprise architecture. Her background is multi-faceted across consulting, product development, product management, brand strategy, marketing, and business leadership.

    She is currently the Managing Director at Global Data Strategy, Ltd., an international information management consulting company that specializes in the alignment of business drivers with data-centric

    technology. In past roles, she has served in key brand strategy and product management roles at CA Technologies and Embarcadero Technologies for several of the leading data management products in the market.

    As an active contributor to the data management community, she is a long time DAMA International member, Past President and Advisor to the DAMA Rocky Mountain chapter, and was recently awarded the Excellence in Data Management Award from DAMA International in 2016.

    Donna is also an analyst at the Boulder BI Train Trust (BBBT) where she provides advice and gains insight on the latest BI and Analytics software in the market. She was on several review committees for the Object Management Groups for key information management and process modeling notations.

    She has worked with dozens of Fortune 500 companies worldwide in the Americas, Europe, Asia, and Africa and speaks regularly at industry conferences. She has co-authored two books: Data Modeling for the Business and Data Modeling Made Simple with ERwin Data Modeler and is a regular contributor to industry publications. She can be reached atdonna.burbank@globaldatastrategy.comDonna is based in Boulder, Colorado, USA.

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    Follow on Twitter @donnaburbankTwitter Event hashtag: #DAStrategies

    mailto:donna.burbank@globaldatastrategy.com

  • Global Data Strategy, Ltd. 2018

    DATAVERSITY Data Architecture Strategies

    January - on demand Panel: Emerging Trends in Data Architecture Whats the Next Big Thing?

    February Building an Enterprise Data Strategy Where to Start?

    March Modern Metadata Strategies

    April The Rise of the Graph Database: Practical Use Cases & Approaches to Benefit your Business

    May Data Architecture Best Practices for Todays Rapidly Changing Data Landscape

    June Artificial Intelligence: Real-World Applications for Your Organization

    July Panel: Data as a Profit Driver Emerging Techniques to Monetize Data as a Strategic Asset

    August Data Lake Architecture Modern Strategies & Approaches

    Sept Master Data Management: Practical Strategies for Integrating into Your Data Architecture

    October Business-Centric Data Modeling: Strategies for Maximizing Business Benefit

    December Panel: Self-Service Reporting and Data Prep Benefits & Risks

    3

    This Years Line Up for 2018

  • Global Data Strategy, Ltd. 2018

    A Word From Our Sponsor

    4

    Datawatch

  • Global Data Strategy, Ltd. 20185

    Data Strategy Across The Organization

    OFF

    ENSE

    DEF

    ENSE

    OPERATIONAL EFFICIENCY ANALYTIC INSIGHT

    HR

    SALESC-LEVEL

    MARKETINGFINANCE

    BI

    IT

  • Global Data Strategy, Ltd. 20186

    Bridge the Gap: Satisfy IT & Data Workers

    Analysts need:Collaboration

    A way to share their work

    A way to ensure their work is based on trusted data

    A means to showcase their contribution of models and analyses

    A way for other analysts and teams to contribute back to their creations

    IT needs:Centralization

    A solution that empowers all users to easily work with data

    Visibility and controls for governance and compliance

    Reduced burden - domain experts manage domain data

    Insight into which data is most valuable so they can focus their efforts

    The organization needs:

    Socialized data access

    Awareness of what data and assets are being created and by whom

    All users working and collaborating in the same place

    Agility and governance in one solution

    Analysis is conducted based on trusted and certified information

    Consistency in models across groups, teams, enterprise

  • Global Data Strategy, Ltd. 20187

    Organizational Analytics Goals

    PROMOTE COOPERATION

    Bring teams together:

    Data scientists

    Analysts

    Data/ETL engineers

    IT

    QA/Governance

    ENHANCE VISIBILITY

    Emphasize:

    Communication

    Automation

    Collaboration

    Integration

    Measurement

    IMPROVE PRODUCTIVITY

    Help analytic teams:

    Rapidly produce insight

    Operationalize that insight

    Continuously improve analytic operations & performance

  • Global Data Strategy, Ltd. 2018

    What Well Cover Today

    The majority of successful organizations in todays economy are data-driven, and innovative companies are looking at new ways to leverage data and information for strategic advantage.

    While the opportunities are vast, and the value has clearly been shown across a number of industries in using data to strategic advantage, the choices in technology can be overwhelming.

    From Big Data to Artificial Intelligence to Data Lakes and Warehouses the industry is continually evolving to provide new and exciting technological solutions.

    This webinar will help make sense of the various data architectures & technologies available, and how to leverage technology for business value and success.

    A practical framework will be provided to generate quick wins for your organization, while at the same time building towards a longer-term sustainable architecture.

    Case studies will also be provided to show how successful organizations have successfully built a data strategies to support their business goals.

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    A Successful Data Strategy links Business Goals with Technology Solutions

    Top-Down alignment with business priorities

    Bottom-Up management & inventory of data sources

    Managing the people, process, policies & culture around data

    Coordinating & integrating disparate data sources

    Leveraging & managing data for strategic advantage

    Copyright 2018 Global Data Strategy, Ltd

    Aligning Business Strategy and Data Strategy

  • Global Data Strategy, Ltd. 2018

    How can we Transform our Business through Data?Business Optimization

    Becoming a Data-Driven Company Making the Business More Efficient

    Better Marketing Campaigns Higher quality customer data, 360 view

    of customer, competitive info, etc. Better Products

    Data-Driven product development, Customer usage monitoring, etc.

    Better Customer Support Linking customer data with support logs,

    network outages, etc. Lower Costs

    More efficient supply chain Reduced redundancies & manual effort

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    Business TransformationBecoming a Data Company

    Changing the Business Model via Data data becomes the product.

    Monetization of Information: examples across multiple industries including:

    Retail: Click-stream data, purchasing patterns

    Social Media: social & family connections, purchasing trends & recommendations, etc.

    Telecom: location information, usage & search data, etc.

    Energy: Sensor data, consumer usage patterns, smart metering, etc.

    How do we do what we do

    better?

    How do we do something different?

  • Global Data Strategy, Ltd. 2018

    Basic Definitions

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    Business & Data Strategies

    A BUSINESS STRATEGY is a medium to long term business plan which details the aims & objectives of a business and how it means to

    achieve them.

    A DATA STRATEGY is a medium to long term plan for the improvement, management & exploitation of data across a business, and how it is

    to be achieved.

  • Global Data Strategy, Ltd. 2018

    Business & Data Strategy the Interdependency

    12

    Business Strategy Data Strategy

    Sets Requirements for

    Informs & Guides

    Business Strategy

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    Getting it Wrong

    13

    What can cause Business and Data Strategies to become Misaligned?

    Lack of a clearly articulated business strategy

    Absence of Business & IT senior leadership in strategy

    formulation & execution

    Business fails to take ownership of the data and

    hence the data strategy

    Data strategy is viewed as a technology roadmap, led by

    IT

    Lack of cross-business / IT collaboration & communication

    Complexity and lack of priority, focus & deliverable

    milestones

    Not showing short-term results & benefits

    Lack of skills and expertise to realize the strategy

  • Global Data Strategy, Ltd. 2018

    Getting it Right

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    The Key Features of an Effective Data Strategy

    ALIGNED Directly Connected to Business Drivers.

    ACTIONABLE with clear activities & milestones

    EVOLUTIONARY to meet changing business needs & new technology

    UNIQUE to the specific organization

  • Global Data Strategy, Ltd. 2018

    Consumer Energy Company

    For the consumer energy sector Big Data and Smart Meters are transforming the ways of doing business and interacting with customers. Moving away from traditional data use cases of metering & billing. Smart meters allow customers to be in control of their energy usage.

    Control over energy usage with connected systems Custom Energy Reports & Usage Smart Billing based on usage times

    As energy usage declines, data is becoming the true business asset for this energy company. While the Big Data Opportunity is crucial, equally important are the traditional data sources

    Data Quality critical for operational and analytic data Data Governance critical for analyzing data in relation to business processes & roles With high volumes of data, critical data elements prioritized

    Business Transformation through Data

  • Global Data Strategy, Ltd. 2018

    Increasing Restaurant Revenue through Menu Data

    An international restaurant chain realized through its digital strategy that: While menus are the core product that drives their business They had little control or visibility over their menu data Menu data was scattered across multiple systems in the organization from supply chain to kitchen prep to marketing,

    restaurant operations, etc. Menu data was consolidated & managed in a central hub:

    Master Data Management created a single view of menu for business efficiency & quality control Data Governance created the workflow & policies around managing menu data

    Process Models & Data Mappings were critical Business Process diagrams to identify the flow of information CRUD Matrixes to understand usage, stewardship & ownership

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    Managing the Data that Runs the Business

    Product Creation & Testing

    Menu Display & Marketing

    Supply Chain Point of Sale & Restaurant Operations

  • Global Data Strategy, Ltd. 2018

    Optimizing Customer Experience through Data

    A major Retail Vendor wanted to become a data-driven company Enhancing the customer experience by mapping the Customer Journey to the Data Lifecycle Using IoT product data to improve product design & customer service Optimizing product supply chain & delivery

    Developing a Tactical Data Strategy determined that Data Architecture was needed to understand the data ecosystem: data flow diagrams, data models, process models, etc Data Governance was required to manage data across organizational siloes: product development, marketing, sales, etc. Master Data Management was needed to manage customer contact data throughout the Customer Journey.

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    Using Data to Build Customer Loyalty & Increase Sales

    Customer SupportCustomer Discovery & Purchase

    Product Delivery & Tracking

    Product Usage Tracking Product Development

  • Global Data Strategy, Ltd. 2018

    UK Environment Agency

    The UK Environment agency worked with Global Data Strategy to develop Data Models & Data Standards in order to support Open Data publication of key environmental measures.

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    Supporting Digital Transformation & Open Data Publication

    Land boundaries Air & Water Quality

    Fish & Wildlife populations Etc.

    Becoming a Data-driven organisation included: Digital Transformation all services online Open Data promoting data sharing with public

    Common Data Models & Standards helped create a common lingua franca across the organization:

    Establishing a standard is a really important step in bringing our information together so we can be better joined up, better integrated

    and work together more efficiently.- National River Basin Operations Manager, Environment Agency

    Saving time & money Supporting Regulation Enhancing public

    reputation

    Improving data quality & consistency

    Increasing collaboration between teams

  • Global Data Strategy, Ltd. 2018

    Managed Care Organization: Telling the Data Story

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    Data Drives Everything We DoCentered around Serving our Members

    Member

    Is Assisted by

    ProviderStaff

    Location

    Credentials

    Community Living

    Visits an Emergency Room at

    Would like to transition to

    Needs an overnight stay in

    Bed

    Has Availability for

    Is Assisted byIs Certified for

    Practices at

    Apply to

    Support & Certify

    Community

    Train & Inform

    Interacts with

  • Global Data Strategy, Ltd. 2018

    The Importance of MotivationFrom Cruise Ship to Life Raft

    With a common motivation, disparate skills, personalities and roles become an asset, not an annoyance

  • Global Data Strategy, Ltd. 2018

    Business Motivation Model

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    Corporate Mission Corporate Vision

    Goals & Objectives

    To provide a full service online retail experience for art supplies and craft products.

    To be the respected source of art products worldwide, creating an online community of art enthusiasts.

    Artful Art Supplies ArtfulArt

    C

    External Drivers

    Digital Self-Service Increasing Regulation Pressures

    Online Community & Social Media

    Customer Demand for Instant Provision

    Internal Drivers

    Cost Reduction

    Targeted Marketing 360 View of Customer

    Brand Reputation Community Building

    Revenue Growth

    C

    Accountability Create a Data Governance

    Framework Define clear roles &

    responsibilities for both business & IT staff

    Publish a corporate information policy

    Document data standards Train all staff in data

    accountability

    C

    Quality Define measures & KPIs for

    key data items Report & monitor on data

    quality improvements Develop repeatable

    processes for data quality improvement

    Implement data quality checks as BAU business activities

    C

    Culture Ensure that all roles

    understand their contribution to data quality

    Promote business benefits of better data quality

    Engage in innovative ways to leverage data for strategic advantage

    Create data-centric communities of interest

    Corporate-level Mission & Vision May already be created or may

    need to create as part of project.

    Project-level, Data-Centric Drivers External Drivers are what youre

    facing in the industry Internal Drivers reflect internal

    corporate initiatives.

    Project-level, Data-Centric Goals & Objectives

    Clear direction for the project Use marketing-style headings

    where possible

  • Global Data Strategy, Ltd. 2018

    The Role of the Data Professional in the Data-Driven Business

    In the current environment of data-driven business, Data Professionals have an opportunity to have a seat at the table

    Finding new opportunities to leverage data for business benefit Creating efficiencies & business process optimization Integrating data from disparate sources for new business insights Supporting organizational change

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  • Global Data Strategy, Ltd. 2018

    Business Executive

    Results-Oriented Optimistic Identifies opportunities Im busy. Whats the business opportunity?

    Data Architect

    Focused on architecture, data, technology Often seen as finding problems, not

    solutions Let me tell you about my data model!

    Data Advisor

    Focused on solutions, business, information Highlights issues & opportunities around

    data Less me show you how data can help your

    business!

    The world is going to end if your model is not in 3rd normal form!!

    If you link your Customer data with your Product usage stats, we can

    increase sales.Whats in it for me?

    Be More Data Advisor and Less Data Architect

  • Global Data Strategy, Ltd. 2018

    Find a Balance in Implementing Data Architecture

    Find the Right Balance Data Architecture projects can have the reputation for being overly academic, long, expensive, etc. No architecture at all can cause chaos. When done correctly, Data Architecture helps improve efficiency and better align with business priorities

    24

    Focus on Business Value

    Business Value

    Too Academic, nothing gets done

    Too Wild West, nothing gets done - chaos

  • Global Data Strategy, Ltd. 2018

    Data Management Maturity Assessment

    Current State Future State

    Strategy 2.8 4.3We have a Data Strategy for maximizing the use of data within our organization 3 5

    Our Data Strategy is aligned to our Business Strategy. 3 5We have executive and/or senior-level business support and sponsorship for our strategy 2 4We have published a plan to achieve our Data Strategy that includes organization support, process, and IT. 4 4We have organizations and budgets in place to support our Data Strategy and Plan. 3 4Our Data Strategy is published and well understood across lines of business and technology groups. 2 4

    Etc

    Data Governance 3.0 5.0We have a standard, auditable process for resolving data governance issues, such as change management, priority management, conflict resolution, etc. 3 5

    We have data stewards who manage key data used across functional groups. They have clearly defined and well understood roles and responsibilities. 4 5We have identified business-critical data elements and define & store them in a commonly-accessible format. 4 5All of our people understand the importance of data to the organization and their personal responsibilities for managing it. 3 5We have a data communications strategy to ensure data policies and standards are reinforced across our organization. 3 5Data related objectives and responsibilities are formally included in job descriptions and/or personal objectives. 1 5Our data governance process has a senior business and IT sponsorship and stakeholder buy-in across the functional leaders. 3 5EtcMaster Data Management 4 5Etc.continue for each capability area 1 4

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    Ask a Detailed Set of Questions for Each Functional AreaShow Current State and desired Future State. You dont have to be a 5 in everything!

  • Global Data Strategy, Ltd. 2018

    Visualizing Current vs. Target Maturity

    A Radar Chart (Spider Chart) can be a helpful way to visualize the relative strengths & weaknesses in various capability areas.

    26

    Determine Relative Strengths

    Significant Gap in Data Governance

    Metadata Management meets Target Maturity

    Were overdoing it for Data Architecture

  • Global Data Strategy, Ltd. 2018

    Master Data Management

    Data Governance

    Strategy

    Mapping Business Drivers to Data Management Capabilities

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    Business-Driven PrioritizationStakeholder Challenges

    Lack of Business Alignment Data spend not aligned to Business Plans Business users not involved with data

    1

    360 View of Customer Needed Aligning data from many sources Geographic distribution across regions

    2

    Data Warehousing

    Business Intelligence

    Big Data Analytics

    Data Quality

    Data Architecture & Modeling

    Data Asset Planning & Inventory

    Data Integration

    Metadata Mgt

    Business Drivers

    Digital Self ServiceIncreasing Regulation

    Pressures

    Online Community & Social Media

    Customer Demand for Instant Provision

    Internal Drivers

    External Drivers

    Targeted Marketing

    360 View of Customer

    Revenue Growth

    Brand Reputation

    Community Building

    Cost Reduction

    Integrating Data Siloed systems Time-to-Solution Historical data

    3

    Data Quality Bad customer info causing Brand damage Completeness & Accuracy Needed

    4

    Cost of Data Management Manual entry increases costs Data Quality rework Software License duplication

    5

    No Audit Trails No lineage of changes Fines had been levied in past for lack of

    compliance

    6

    New Data Sources Exploiting Unstructured Data Access to External & Social Data

    7

    1 7

    1 2 3 4 5 6

    71 2 3 4 5 6

    1 72 3

    1 72 3

    1 2 6

    72 3

    53 4

    1 2 3 4

    63 5

    2 3 5 7

    Shows Heat Map of Priorities

  • Global Data Strategy, Ltd. 2018

    Speak with a Wide Variety of Stakeholders

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    Its important to speak with a wide range of roles across the organization.

    Business & IT Cross-functional teams (Marketing,

    Finance, Analytics, etc, etc.)

    Understand key opportunities & challenges.

    Recruit allies & volunteers (and identify those you still need to convince. )

  • Global Data Strategy, Ltd. 2018

    Stakeholder Matrix

    29

    Create a simple stakeholder matrix outlining the key stakeholders, their roles, involvement, influence, impact, etc.

    Keeping track of whos who: Create a simple stakeholder matrix outlining the key stakeholders, their roles, involvement, influence, impact, etc.

    RACI *:R: ResponsibleA: AccountableC: ConsultedI: Informed

  • Global Data Strategy, Ltd. 2018

    Data Source Inventory Document key data sources across the organization as well as who is using them (i.e. key departments & stakeholders) Data models & other architecture tools can help document the technical structures & metadata

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    Data Sources Leadership Sales Finance Marketing Support R&D HR Legal Compliance

    Relational DatabasesMySQL XOracle X X X X X X X XSQL Server X XSybase XEtc.

    BI ToolsTableau X X X X X XQlik X X XEtc.

    Open DataData.gov agricultural data X X X

    Etc.

  • Global Data Strategy, Ltd. 2018

    Industry Trends: Data Platforms are Currently in Use?

    A wide range of technologies are currently in use: Relational databases most common

    o Both Cloud & On-Premises Spreadsheets ubiquitous

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    Which of the following data sources or platforms are you currently using? [Select all that apply]

    Relational Databases are still clearly the

    leader.

    Spreadsheets are ubiquitous

    More Legacy platforms (44.6%)

    than Big Data (42.2%)

    From Emerging Trends in Data Architecture, DATAVERSITY, by Donna Burbank & Charles Roe, October 2017

  • Global Data Strategy, Ltd. 2018

    Industry Trends: Emerging Technologies

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    Which of the following do you plan to use in the future that you are not using currently? [Select all that Apply]

    Many looking to Big Data Platforms

    Movement to the Cloud is popular

    Uncertainty is common.

    For those looking at new technologies, there is a wide range of responses.

    Big Data Platforms a leader Move to Cloud RDMBS Graph Database Real-time Streaming Internet of Things (IoT)

    Many are still uncertain, indicating the vast rate of change and wide array of choices available.

    From Emerging Trends in Data Architecture, DATAVERSITY, by Donna Burbank & Charles Roe, October 2017

  • Global Data Strategy, Ltd. 2018

    Implement Just Enough Data Governance Each type of data has its own type of governance model & sharing paradigm As a general rule, the more the data is shared across & beyond the organization, the more formal governance needs to be

    33

    Core Enterprise Data

    Functional & OperationalData

    Exploratory Data

    Reference & Master Data

    Core Enterprise Data Common data elements used by multiple

    stakeholders across Bus, LOBs, functional areas, applications, etc.

    Highly governed Highly published & shared

    Functional & Operational Data Lightly modeled & prepared data for

    limited sharing & reuse Collaboration-based governance May be future candidates for core data

    Exploratory Data Raw or lightly prepped data for

    exploratory analysis Mainly ad hoc, one-off analysis Light touch governance

    Examples Operational Reporting Non-productionized analytical model data Ad hoc reporting & discovery

    Examples Raw data sets for exploratory analytics External & Open data sources

    Examples Common Financial Metrics: for Financial & Regulatory Reporting Common Attributes: Core attributes reused across multiple areas

    (e.g. Customer name, Account ID, Address)

    Master & Reference Data Common data elements used by multiple stakeholders

    across functional areas, applications, etc. Highly governed Highly published & shared

    Examples Reference Data: Procedure codes, Country Codes, etc Master Data: Location, Customer, Product

  • Global Data Strategy, Ltd. 2018

    Identify What Data Needs to Be Governed

    34

    And What to Leave Alone

    Launch of New Product Marketing Campaign requires better customer information

    Customer Product

    RegionVendor

    Partner

    Identify Key Business Driver

    Filter Data Elements Aligned with Business

    Driver

    Focus Governance Efforts on Key Data

    What?Why? How?

    Structured Warehouse for Financial Reporting

    Exploratory Analytics & Discovery

    Lightly governed

    Social Media Sentiment Analysis

    Financial Reporting

    Highly governed

  • Global Data Strategy, Ltd. 2018

    Crowdsourcing Governance & Metadata Definitions Many data governance projects (& vendors) are embracing the concept of crowdsourcing. i.e. The

    Wikipedia vs. Encyclopedia approach Open editing Popularity & Usage Rankings Dynamically changing

    35

    Encyclopedia Wikipedia Created by a few, then published as read-only Single source of vetted truth Static

    Created by a by many, edited by many Eventual consistency with multiple inputs Dynamic

    For Standardized, Enterprise Data Sets For Self-Service Data Prep & Analytics

  • Global Data Strategy, Ltd. 2018

    Finding the Right Balance

    36

    When implementing successful data governance in todays rapidly-changing, self-service data landscape, it is important to find a balance between:

    Standards-based Governance

    The two methods work well together, using the right approached depending on the data usage.

    Collaboration-based Governance

    Well-suited for enterprise-wide data standards Well-suited for self-service data

    preparation & analytics

  • Global Data Strategy, Ltd. 2018

    Applying a Structured Data Governance Framework

    Organization & People

    Process & Workflows

    Data Management & Measures

    Culture & Communication

    Vision & Strategy

    Tools & Technology

    Business Goals & Objectives

    Data Issues & Challenges

  • Global Data Strategy, Ltd. 2018

    Building the Data Governance Framework

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    Vision & Strategy Organization & PeopleProcesses & Workflows

    Data Management & Measures

    Culture & Communications Tools & Technology

    Is there a clear understanding of the strategic goals of your organization & the need for enterprise data governance?

    Who are the key data stakeholders within and outside your organization?

    Do business process design and operations management take data needs into account?

    Has key data been identified, defined and analyzed?

    Has the importance of data been communicated across the organization? Is there a data communications plan?

    Is there a coherent data architecture in place to define and guide how data is captured, processed, stored and used?

    How does your organization rely on data now and in the future?

    Who are the primary data producers, consumers & modifiers?

    Are there any specific data management / improvement processes in place?

    Have data models been built conceptual / logical / physical?

    Is the value of good data management understood and championed by senior managers?

    What primary IT systems and platforms are used to store and process key data?

    What impact are data problems currently having on your organization?

    Are individuals formally accountable for data ownership?

    Are there issue and workflow management processes to address data problems?

    Has the relationship between business processes and data been mapped?

    Do all employees and third parties receive data awareness and improvement education and training?

    Do design gateways exist to ensure data needs are taken into account in new & modified platforms?

    Do you have a data governance policy?

    Are employees trained in good data management practices?

    Has there been any analysis of the efficiency and effectiveness of how data is managed within operational business processes?

    Are data shortcomings known, measured & recorded?

    Are there communication channels for communicating best practice in data management?

    What specialist data management tools are currently in use?

    What are the overall expected benefits of better data governance?

    Are there any channels through which data shortcomings can be highlighted and investigated?

    How does the business and IT interact to manage data improvement?

    Are there are formal standards & rules specifying how data should be managed and improved?

    Are there internal success stories that could be used to promote better data management across the organization?

    What metadata is captured and stored?

  • Global Data Strategy, Ltd. 2018

    Measuring Data Improvements

    KPIs & Measures aligned with concrete business drivers Helps prioritize efforts Assists with the Why do I Care? issue Basis for showing benefits and results

    39

    Align Data Quality Metrics to Business Improvements

    KPI Current Target Status Business Benefits TypeNumber of duplicate customer records

    2,000,000 1,000 Correct # of customers for sales estimations Better single view of customer for integrated social media campaign

    Reduce cost of physical mailing by $20K

    Cost savings Brand Reputation Marketing Innovation

    Incorrect Salutation (Mr,Ms, etc.)

    5,000 1,000 Customer satisfaction & Brand reputation harmed by incorrect salutation.

    Targeted marketing campaigns by gender.

    Brand Reputation Campaign Effectiveness

    Incorrect address/location 10,000 500 Lower return rate on physical mailings Better targeted marketing by region.

    Cost Savings Campaign Effectiveness

    Missing Sales Rep Assigned 500 100 Ability for Sales to execute on customer leads Revenue growth

    Sales Effectiveness

    Etc.

    Business Driver: Improving Customer Data for Marketing Launch Campaign

  • Global Data Strategy, Ltd. 2018

    Look for Business Value Levers

    Identify areas that will derive the highest business value by addressing.

    Is this supporting the new marketing campaign for a high visibility product launch?

    Or are you re-arranging the deck chairs on the Titanic i.e. focusing valuable time and effort no low-value activities

    As with any areas of the business that have value, it is helpful to build a model or architectural design around the key areas of business value.

    Identify Quick WinsLoadEffort

    Fulcrum

    Identify areas where data can be the fulcrum.

  • Global Data Strategy, Ltd. 2018

    Defining an Actionable Roadmap

    Develop a detailed roadmap that is both actionable and realistic Show quick-wins, while building to a longer-term goal Balance Business Priorities with Data Management Maturity Focus on projects that benefit multiple stakeholders Mix core architecture with new shiny things

    41

    Maximize the Benefit to the Organization

    Initiatives H1 '17 H2 '17 H2 '18 H2 '18

    Strategy Development

    Governance Lineage for Privacy RulesBusiness Glossary Population & Publication

    Data Warehouse Metadata

    Customer Analytics Pilot Social Media integration

    Open Data Publication

    IoT Integration

    Ongoing Communication & Collaboration

    Customer Product Location

    Integrated Customer View

    Marketing

    Sales

    Customer Support

    Executive Team

  • Global Data Strategy, Ltd. 2018 42

    Key Steps to Creating a Data Program

    The following steps should be included when creating a data program. The order is less important than ensuring that they are completed.

    Steps to Success

    Secure Senior Executive Support

    Identify a Data Champion among senior leadership.

    Define Vision, Drivers & Motivations

    Define business-driven vision for the program.

    Build the Business Case

    Outline key benefits of data program & risks of not doing so

    Deliver Quick Wins

    Short, iterative, business-driven projects deliver short-term value, building towards long-term gain.

    Identify Business-Critical Data

    Focus on the data that has the highest impact on the business.

    Identify & Interview Stakeholders

    Elicit feedback from key stakeholders listen & communicate.

    Create Organization

    Define an organizational structure that aligns with your way of working.

    Communicate

    Build a communication plan from initial feedback phase throughout all phases of the program.

    Assess IT Maturity

    Assess the maturity of the IT organization across all aspects of data management.

    Map Business Priorities to IT Capabilities

    Create a realistic heat map aligning business goals with data management capabilities.

  • Global Data Strategy, Ltd. 2018

    Summary

    Aligning Data Strategy & Data Architecture with business drivers & goals is key to success Adapt your data architecture for both innovative & legacy technologies Orchestrate the people, process, technology, & culture required to support your data

    architecture through a robust Data Governance program Design data quality and metadata into your data architecture from the outset, and how to

    design core KPIs and metrics to track success Build quick wins into your roadmap to provide business value through every stage of your

    architecture development

    Where to Start? - With Business Drivers

  • Global Data Strategy, Ltd. 2018

    About Global Data Strategy, Ltd.

    Global Data Strategy is an international information management consulting company that specializes in the alignment of business drivers with data-centric technology.

    Our passion is data, and helping organizations enrich their business opportunities through data and information.

    Our core values center around providing solutions that are: Business-Driven: We put the needs of your business first, before we look at any technological solution. Clear & Relevant: We provide clear explanations using real-world examples, not technical jargon. Customized & Right-Sized: Our implementations are based on the unique needs of your organizations

    size, corporate culture, and geography. High Quality & Technically Precise: We pride ourselves in excellence of execution, and we attract high-

    quality professionals with years of technical expertise in the industry.

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    Data-Driven Business Transformation

    Business StrategyAligned With

    Data Strategy

    www.globaldatastrategy.com

    http://www.globaldatastrategy.com/

  • Global Data Strategy, Ltd. 2018

    Related Article

    Related article on DATAVERSITY, Sept 2017: Data Management vs. Data Strategy: A

    Framework for Business Success

    45

    To Read More

    http://www.dataversity.net/data-management-vs-data-strategy-a-framework-for-business-success/

  • Global Data Strategy, Ltd. 2018

    DATAVERSITY Data Architecture Strategies

    January Panel: Emerging Trends in Data Architecture Whats the Next Big Thing?

    February Building an Enterprise Data Strategy Where to Start?

    March Modern Metadata Strategies

    April The Rise of the Graph Database: Practical Use Cases & Approaches to Benefit your Business

    May Data Architecture Best Practices for Todays Rapidly Changing Data Landscape

    June Artificial Intelligence: Real-World Applications for Your Organization

    July Panel: Data as a Profit Driver Emerging Techniques to Monetize Data as a Strategic Asset

    August Data Lake Architecture Modern Strategies & Approaches

    Sept Master Data Management: Practical Strategies for Integrating into Your Data Architecture

    October Business-Centric Data Modeling: Strategies for Maximizing Business Benefit

    December Panel: Self-Service Reporting and Data Prep Benefits & Risks

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    This Years Line Up for 2018 Join Us Next Month

  • Global Data Strategy, Ltd. 2018

    Questions?

    47

    Thoughts? Ideas?

    Building an Enterprise Data Strategy Where to Start?Donna BurbankDATAVERSITY Data Architecture StrategiesA Word From Our SponsorData Strategy Across The OrganizationSlide Number 6Slide Number 7What Well Cover TodayAligning Business Strategy and Data StrategyHow can we Transform our Business through Data?Basic Definitions Business & Data Strategy the InterdependencyGetting it WrongGetting it Right Consumer Energy CompanyIncreasing Restaurant Revenue through Menu DataOptimizing Customer Experience through DataUK Environment AgencyManaged Care Organization: Telling the Data StoryThe Importance of MotivationBusiness Motivation ModelThe Role of the Data Professional in the Data-Driven BusinessBe More Data Advisor and Less Data ArchitectFind a Balance in Implementing Data ArchitectureData Management Maturity AssessmentVisualizing Current vs. Target MaturityMapping Business Drivers to Data Management CapabilitiesSpeak with a Wide Variety of StakeholdersStakeholder MatrixData Source InventoryIndustry Trends: Data Platforms are Currently in Use?Industry Trends: Emerging TechnologiesImplement Just Enough Data GovernanceIdentify What Data Needs to Be GovernedCrowdsourcing Governance & Metadata DefinitionsFinding the Right BalanceApplying a Structured Data Governance Framework Building the Data Governance FrameworkMeasuring Data ImprovementsLook for Business Value LeversDefining an Actionable RoadmapKey Steps to Creating a Data ProgramSummaryAbout Global Data Strategy, Ltd.Related ArticleDATAVERSITY Data Architecture StrategiesQuestions?

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