Big Data and Big Data Governance

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1 The First Step in Information Big Data and Big Data Governance Kelle O Neal

2 Table of Contents Big Data Value and Impact Enterprise InformaKon Big Data Big Data Governance AddiKonal Thoughts pg 2

3 The landscape is changing pg 3

4 Big Data Importance When integrated with other enterprise data, organizakons can develop more insightul understanding of their business which can lead to: A stronger compekkve edge Improve business processes Greater product innovakon and improvements Increase in growth and revenue Increased employee produckvity through streamlined business processes Source Big Data: The Next FronKer, McKinsey Global InsKtute pg

5 ImplicaKons of Big Data How will organizakons have to be designed, organized, and managed? What exiskng business models are likely to be disrupted? How will organizakons legacy business models and technology compete? How will business processes change? How will markekng funckons and ackvikes have to evolve? How will organizakons leverage and value their data assets? How will execukves help their organizakons take advantage of the change that is under way? Where do they start and how? Current technologies and data management structures in organiza3ons no longer work in this new era of big data pg 5

6 Enterprise InformaKon pg 6

7 A Comprehensive Framework Enterprise InformaKon GOVERNANCE InformaKon Strategy Business Intelligence and Performance Content Content Delivery Data InformaKon Asset Architecture and Technology Enablement ORGANIZATIONAL ALIGNMENT Provides a holiskc view of data in order to manage data as a corporate asset pg 7

8 How Big Data Fits Enterprise Data Ensure data is available, accurate, complete and secure DATA GOVERNANCE Master Data Reference Data Metadata Big Data Data Quality Data Architecture Data RetenKon/Archiving Privacy/Security Develop and execute architectures, policies and procedures to manage the full data lifecycle pg 8

9 Big Data pg 9

10 FoundaKon to Harness Internal and External Data IT Transformation and Adaptability Flexible Data Architecture Master Data Big Data Integrated Information and Delivery EIM and adaptive architecture to deliver business capabilities and flexibility to future changes BDM is integrakng and managing big data and its relakonship across the enterprise through people, processes and technology. It provides opportunity to find insights in new types of data and content, to make organizakons more agile, and to answer queskons that were previously considered beyond reach MDM is management of foundational data domains that support core business processes, information and insight creation. It provides for flexibility data integration, directly supporting enterprise information architecture vision Architectural Improvements Data Warehousing Data extraction and normalization for operational as well as management reporting and functional analytics. Data integrity and lack of standards have constrained the maturity of analytics in the past Process Automation Transaction Process automation and management of transactions with application specific data within isolated business applications including ERP, CRM, SCM, ecommerce and other systems over the past decade PAST PRESENT FUTURE BDM provides foundational capabilities to integrate and analyze data from non-traditional data sources in order to find insights in new types of data pg 10

11 Big Data Lifecycle Process Listen Capture Process Consume Analyze Integrate Measure Retain Destroy pg 11

12 Types of Data Data Disciplines are expanding. Most types of data are not completely independent. Big Data o7en has a rela9onship to other data types. of these data sets addresses: Data Quality Enrichment /Enhancement Relevance Small Data Privacy and Security Governance Metadata Big Data Master Data Reference Data pg 12

13 Data Types Work Together Big or Small Data (Transactional Data) Reference Data (Statistic non-volatile data) Master Data Enhanced/Enriched Master Data (360 degree View) Examples: Social Media Influence Social Media Account IDs Demographic InformaKon RelaKonships IDs Validated Master Data Examples include: Address validakon through loca9on broadcasts and geo- loca9on data Big Data (Interaction Data) pg 13

14 Big Data Governance pg 1

15 Data Governance DefiniKon Data Governance is the organizing framework for establishing strategy, objeckves and policy for effeckvely managing corporate data. It consists of the processes, policies, organizakon and technologies required to manage and ensure the availability, usability, integrity, consistency, audit ability and security of your data. Data Standards and Modeling CommunicaKon and Metrics Data Policies and Processes Data Strategy A Data Governance Program consists of the inter-workings of strategy, standards, policies and communication. pg 15

16 Data Governance Components Operating Model Arbiters & Escalation points Data Governance Organization Members Roles and Responsibilities Data Ownership & Accountability Vision & Mission Objectives & Goals Alignment with Corporate Objectives Alignment with Business Strategy Guiding Principles Policies & Rules Processes Controls Data Standards & Definitions Metadata, Taxonomy, Cataloging, and Classification Statistics and Analysis Tracking of progress Monitoring of issues Continuous Improvement Score-carding Change Business Impact & Readiness IT Operations & Readiness Training & Awareness Stakeholder & Communication Defining Ownership & Accountability Collaboration & Information Life Cycle Tools Data Mastering & Sharing Data Architecture & Security Data Quality & Stewardship Workflow Metadata Repository Communication Plan Mass Communication Individual Updates Mechanisms Training Strategy pg 16

17 CompeKng PrioriKes Business Insight Security & Control pg 17

18 Strategy Operating Model Arbiters & Escalation points Data Governance Organization Members Roles and Responsibilities Data Ownership & Accountability Vision & Mission Objectives & Goals Alignment with Corporate Objectives Alignment with Business Strategy Guiding Principles Extension of overall Data Governance Strategy and Scope Policies & Rules Statistics and Analysis Processes Tracking of progress Controls Monitoring of issues Data Standards & Definitions Continuous Improvement Metadata, Taxonomy, Business purpose Score-carding and value unique of Big Cataloging, and Classification Collaboration & Information Data Life Cycle Tools Data Mastering & Sharing Data Architecture & Security Understanding of impacted business Data Quality & Stewardship Change Workflow processes and key requirements Metadata Repository IncorporaKon of new risks Business Impact & Readiness IT Operations & Readiness Training & Awareness Stakeholder & Communication Defining Ownership & Accountability Communication Plan Mass Communication Individual Updates Mechanisms Training Strategy pg 18

19 OrganizaKon Operating Model Arbiters & Escalation points Data Governance Organization Members Roles and Responsibilities Data Ownership & Accountability Vision & Mission Objectives & Goals Alignment with Corporate Objectives Alignment with Business Strategy Guiding Principles Policies & Rules Processes Controls Data Standards & Definitions Metadata, Taxonomy, Cataloging, and Classification New Stakeholders Extended parkcipakon at all levels to include Privacy, new Lines of Business Statistics and Analysis Tracking of progress Monitoring of issues Continuous Improvement Score-carding Extended RACI to cover new data types idenkfy new stewards Change Business Impact & Readiness IT Operations & Readiness Training & New Awareness Regions Stakeholder & Communication Defining Ownership & Accountability Collaboration & Information Life Cycle Tools Data Mastering & Sharing Data Architecture & Security Data Quality & Stewardship Workflow Metadata Repository Redefine role and scope of Data Steward; New roles (i.e. Data ScienKsts) Communication Plan Mass Communication Individual Updates Mechanisms Training Strategy pg 19

20 Policies, Processes & Standards Operating Model Arbiters & Escalation points Data Governance Organization Members Roles and Responsibilities Data Ownership & Accountability Vision & Mission Objectives & Goals Alignment with Corporate Objectives Alignment with Business Strategy Guiding Principles Policies & Rules Processes Controls Data Standards & Definitions Metadata, Taxonomy, Cataloging, and Classification Change Statistics and Analysis Tracking of progress Monitoring of issues Continuous Improvement Score-carding Business Impact & Readiness IT Operations & Readiness Training & Awareness Stakeholder & Communication Defining Ownership & Accountability Extension of Security, Privacy Policies Policies around data masking in teskng and/or produckon, and unmasking Understanding of Intellectual Collaboration Property & Information Life Cycle Tools considerakons and Appropriate Use Data Mastering & Sharing Data Architecture & Security Extension of Data RetenKon Data Quality Policy & Stewardship Archiving Storage DisposiKon Policy Enforcement Metadata, ClassificaKon Workflow Metadata Repository New DefiniKons and Terms Communication Plan Mass Communication Individual Updates Mechanisms Training Strategy pg 20

21 Measurement & Monitoring Re- evaluate Data Quality Standards, Thresholds and Metrics Data Availability requirements and Operating Model Arbiters & Escalation points Data Governance Organization Members Roles and Responsibilities Data monitoring Ownership & Accountability Vision & Mission Objectives & Goals Alignment with Corporate Objectives Alignment with Business Strategy Guiding Principles Policies & Rules Processes Controls Data Standards & Definitions Metadata, Taxonomy, Cataloging, and Classification Data Profiling rules & processes Monitoring of data movement and usage Track security, privacy Web metrics Statistics and Analysis Tracking of progress Monitoring of issues Continuous Improvement Score-carding Change Business Impact & Readiness IT Operations & Readiness Training & Awareness Stakeholder & Communication Defining Ownership & Accountability Collaboration & Information Life Cycle Tools Data Mastering & Sharing Data Architecture & Security Data Quality & Stewardship Workflow Metadata Repository Communication Plan Mass Communication Individual Updates Mechanisms Training Strategy pg 21

22 Technology IntegraKng exiskng and Big Data Technologies, i.e. Master Data Operating Model Arbiters & Escalation points Data Governance Organization Members Roles and Responsibilities Data Ownership & Accountability Vision & Mission Objectives & Goals Alignment with Corporate Objectives Alignment with Business Strategy Guiding Principles Policies & Rules Processes Controls Data Standards & Definitions Metadata, Taxonomy, Cataloging, and Classification Big Data Lifecycle Data Compression & Archiving Requirements Statistics and Analysis Tracking of progress Monitoring of issues Continuous Improvement Score-carding Change Regulatory RetenKon Requirements for Big Data Business Impact & Readiness IT Operations & Readiness Training & Awareness Stakeholder & Communication Defining Ownership & Accountability Business RetenKon Requirements Data Volumes & Cost Metadata requirements New Sources Collaboration & Information Life Cycle Tools Data Mastering & Sharing Data Architecture & Security Data Quality & Stewardship Workflow Metadata Repository Communication Plan Mass Communication Individual Updates Mechanisms Training Strategy pg 22

23 CommunicaKon Operating Model Arbiters & Escalation points Data Governance Organization Members Roles and Responsibilities Data Ownership & Accountability Vision & Mission Objectives & Goals Alignment with Corporate Objectives Alignment with Business Strategy Guiding Principles Policies & Rules Processes Controls Data Standards & Definitions Metadata, Taxonomy, Cataloging, and Classification Statistics and Analysis Tracking of progress Monitoring of issues Continuous Improvement Score-carding Change Extended CommunicaKon Plan, Awareness & EducaKon New Stakeholders Business Impact & Readiness IT Operations & Readiness Training & Awareness Stakeholder & Communication Defining Ownership & Accountability Enhanced Goals, PrioriKes, Concerns and ObjecKves Collaboration & Information Life Cycle Tools Data Mastering & Sharing Data Architecture & Security Data Quality & Stewardship Workflow Metadata Repository Communication Plan Mass Communication Individual Updates Mechanisms Training Strategy pg 23

24 AddiKonal Thoughts

25 New Issues and New Deals Shil from Primary to Secondary Use NoKce and Consent doesn t apply The New Deal on Data pg 25

26 Data is the New Oil pg 26

27 Data is the New Money pg 27

28 Thank you! Kelle O Neal pg 28

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