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Bridging the Data Governance Chasm Jay Zaidi Data Management Advisory & Execution

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  • Bridging the Data Governance Chasm

    Jay ZaidiData Management Advisory & Execution

  • 2

    Summary...

    1. The modern data ecosystem is very complex. Need to simplify data governance.

    2. Primary governance challenges - Data Security, Data Quality and Process transparency.

    3. A combination of People, Process and Technology is required to bridge the data governance chasm using process framework, agile delivery, standards/policies and automation.

  • The small and big data ecosystems are complex. This impacts every

    organizations MISSION and poses huge risks, if not GOVERNED well.

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    Heres the problem -

  • Dont manage lead change before you have to. Jack Welch

    Data Tsunami Time-to-value Regulatory Compliance Risk Management Customer Satisfaction Security & Privacy

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    Heres what it does to you.

  • GAO took IRS to task for : not implementing security protocols related to systems storing tax payer data, failed to integrate multi-factor authentication; restrict access to servers severely enough; ensure sensitive user authentication data were encrypted; and properly limit access to restricted areas. May 2016

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    This is not just a CISO or CIO issue, it is an IT and Data Governance issue.

    Heres the ramification.

  • Patterns we see within our customers organizations Data Silos (small and big data) Lack of data accountability Complex organizational structures Fragmented data sets Agile delivery Continuous change Too many competing priorities Very complex data eco-system No big picture view

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    Primary challenges based on surveys- data security, data quality and process transparency.

  • ONPREMISE(Small&BigData)

    CLOUD(Small&BigData)

    Data CatalogData LocationSemanticsHandling rulesOwnershipAccountabilityProcessing Rules

    This is the reality..

    Internal ConsumersExternal ConsumersAuditorsRegulators

    Data UnderstandingData PreparationEvaluationTransparencyAccountability

    GAPS

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  • 8

    Generic Data Lake Architecture..

    This architecture supports various data access patterns and governance.

    Source:TheEnterpriseBigDataLakebyAlexGorelik,OReilly

  • Heres a 6-step Data Governance solution a combination of Process, People and Technology..1. Assess: Data Management Maturity Assessment focused on Governance, Quality and

    Master Data Management.

    2. Process: Apply our proprietary SPOCH framework.

    3. Agility: Use Agile Data Governance (DG), Data Quality (DQ) and Master Data

    Management (MDM) processes.

    4. Standards/Policies: Define and monitor compliance.

    5. Alignment: Align DG with IT governance.

    6. Automation: Implement tools to automate DG processes, DQ profiling, Tagging,

    Discovery, etc. 9

  • Assess using DMM - CMMI for Data Management

    Helps teams to align data management strategy with business goals of companies and institutions.

    Create a common terminology for describing data and the framework focuses on data management at strategic as well as planning levels.

    DMM model sets guides for achieving different capability levels based on measured improvements in specific process areas of data management.

    The key to CMMI is a series of levels of process improvements that in turn represent levels of IT maturity. Users work through a process in which they evaluate current data management capabilities, uncover gaps and highlight strengths. The method helps leaders establish priorities and create a roadmap for process improvements.

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  • Process - SPOCH Framework.

    S ScopeP Process automationO Ownership/accountabilityC Cross-functional engagementH Human intelligence

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  • Agility Agile for DG, DQ, and MDM

    Agile sprints. Active user involvement. Team empowered to make decisions. Develop small, incremental releases

    and iterate. Focus on frequent delivery of

    products. Testing is integrated into the

    development cycle.

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  • 13

    Recap...

    1. The modern data ecosystem is very complex. Need to simplify data governance.

    2. Primary governance challenges are in data security, data quality and process transparency.

    3. A combination of People, Process and Technology is required to bridge the data governance chasm combination of DMM Assessment followed by SPOCH process framework, Agile data management, definition of standards and policies, alignment of DG with IT governance and automation.

  • Complete SolutionsAlyData and partners

    Data wrangling for small and big data.

    Smart Data Catalog - Find, understand and govern data in Hadoop Data Lakes.

    Data catalog for Hadoop and relational data stores.

    Data Governance process automation.

    Hadoop platform for big data.

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  • About me.

    Founded AlyData in 2014. Led data management and analytics programs at Fannie Mae for 13 years prior to that. Was a direct report to the Chief Data Officer. Principal at PwC and other firms before that.

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    Thought leadership...

    Succeeding with data isnt just a matter of putting Hadoop in your machine room, or hiring some physicists with crazy math skills. It requires you to develop a data culture that involves people throughout the organization. - DJ Patil, Chief Data Scientist of the U.S.

    MybookonData-DrivenLeadershipwillbelaunchedworldwideonAmazonandKindleinJuly.

    DATA-DRIVENLEADERSALWAYSWIN

    The slogan "Data is the new electricity" is profound! Its not just the data by itself thats important, but being able to generate insights from it. In these times of massive change, leaders have to build a data culture - transform themselves and their organizations to unleash the power of their data assets. Some areas you'll explore: What is Dark Data and why you must manage it better? What is the dark side of Big Data and how it's impacting your organization? What is the "Golden Square" and why every leader needs to learn about it and apply it? What are the opportunities and challenges that Big Data and IoT present? What the 6 ingredients for monetizing data are? What steps you can take to win with data, and How do leaders develop a data culture within their organizations?

    Data is the new currency that will drive business and regulatory compliance strategy. Jay does a great job highlighting the techniques and approaches to solve complex problems and achieve corporate strategies in the age of data. - Ray Vazquez, CEO, Infinitive Insight In Data-Driven Leaders Always Win, Jay Zaidi makes a case for investing in foundational capabilities like a data catalog, master data management, data quality and data governance. The emergence of new self-service data tools and approaches is making it possible for everyone in the enterprise to leverage data, to make better decisions and achieve better business outcomes. - Alex Gorelik, CEO, Waterline Data "In his aptly named book, Jay Zaidi makes the basic argument that being Data-Driven has less to do with having a lot of big data and more to do with understanding and analyzing the context around the data you have. Jay thoughtfully explains that data, like any other form of information, cannot be taken at face value and that being Data-Driven isnt just about cycling data though your organization, its about making sure that people are able to both quickly find the right data and place that data in the appropriate context. - Satyen Sangani, co-founder and CEO Alation

    Jay Zaidi istheFounderandManagingPartnerofAlyData.PriortoAlyData,hewasadirectreporttotheChiefDataOfficerofFannieMaeandledtheDataQuality,MDM,Metadata,andAnalyticsprogramsthere.

    Succeeding with data isnt just a matter of putting

    Hadoop in your machine room, or hiring some physicists with crazy math skills. It requires you to

    develop a data culture that involves people throughout the organization. - DJ Patil, Chief Data Scientist of the

    U.S.

  • Email [email protected] - www.linkedin.com/in/javedzaidiWeb www.alydata.com

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    Were here to help.Advise, Train, & Implement.

    AlyData specializes in Strategic Information Management, Business Insights, and Change Management. We help organizations gain a competitive advantage and achieve their mission, using their most under utilized, yet strategic assets - Data and Information.