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Data Governance for Enterprises
The document outlines the importance of data governance for enterprises, emphasizing the transformation of data into a vital company asset and the need for a solid framework to manage it. It details the components of a data governance strategy, including identification, storage, provisioning, processing, and governance, and highlights the benefits such as operational efficiency, data cleanliness, and enhanced collaboration. Additionally, it discusses the roles of data governance councils, trustees, and stewards in ensuring compliance and the effective use of data within organizations.
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Data Governance for Enterprises
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- 2. DataLumin WHAT ISDATA GOVERNANCE • Definition of a company’s assets has changed over the years • Transformed from physical buildings to virtual assets like data & intellectual property • Increased sharing of company data necessitates companies to develop solid framework of regulations to regulate how data is handled, managed, and processed
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- 4. DataLumin DATA GOVERNANCESTRATEGY Defines how data is named, stored, processed, and shared. Instead of data being a by-product of your applications, it becomes a vital company asset. The strategy defines how data will be used efficiently in an organization. Eliminates duplication of resources while enabling access to vital data by those who need it in an organization Effective data governance strategy can tell you where data originates from, where it is stored, and who can access it Precedes & boosts regulatory compliance
- 5. DataLumin COMPONENTS OFDATA GOVERNANCE STRATEGY STORAGE IDENTIFICATION PROVISIONING PROCESSING GOVERNANCE
- 6. DataLumin COMPONENTS OFDATA GOVERNANCE STRATEGY IDENTIFICATION • Identify the origin of the data • Proceed to cleaning, manipulation and storage • Just like you identify residential houses through postal addresses, your data has to be well catalogued • In this regards, the data will have a name, a value, defined format, and source
- 7. DataLumin COMPONENTS OFDATA GOVERNANCE STRATEGY STORAGE • More than physical storage but encompasses the ease to share various data streams across the organization • Understand and document the overlap as to who gets to use the raw data • Allocate storage space depending on the type of data being processed – analytical systems, transactional processing applications or general purpose files • Plan how this data will be moved between the various organizational systems • Efficient storage strategy will help users access data without the need of copying it
- 8. DataLumin COMPONENTS OFDATA GOVERNANCE STRATEGY PROVISIONING • Data reuse and sharing has become the norm in the modern world • This necessitates data strategy provisions to decode this data so that it can be used by another part of the organization • Instead of data being decoded to serve specific applications it should be done with the user in mind • Sharing of data helps the company to increase their productivity will boosting operational efficiencies
- 9. DataLumin COMPONENTS OFDATA GOVERNANCE STRATEGY PROCESSING • For Data to be useful, it has to go through a process of preparations and transformation so that it conforms to a wide range sources within the organization • Developers will be responsible for the task of standardizing and transforming this data for use by various end-users • Aim of process is to ensure that data can be reused and shared
- 10. DataLumin COMPONENTS OFDATA GOVERNANCE STRATEGY GOVERNANCE • Need to have a set of regulations to govern how data is handled by applications and staff members • Once policies are in place, they will lay out what to do during data naming, sharing and manipulation • While developing a governance structure you should ensure that it is not rigorous and complex • When data is able to flow to all the organizations constituents, it has the added benefit of boosting productivity
- 11. DataLumin BENEFITS OFDATA GOVERNANCE Operational Efficiency We live in a data driven world and companies are finally coming to terms that their data is part of the company’s asset. Instead of data being held by one party, data governance strategies enable the efficient sharing of data Boosts Collaboration When data is open to everyone needs it in the organization, it boosts transparency and collaboration between teams in the organization Keeps Data clean Many organizations spend a lot of time accumulating data. Having a data governance strategy, ensures that the data you are storing is clean. The data will need to be updated or deleted for it to be relevant
- 12. DataLumin BUILDING ADATA GOVERNANCE FRAMEWORK Policies & Standards Information Quality Privacy, Compliance & Security Architecture Integration Establish Decision Rights Stewardship Access Risk & Define Controls Consistent Data Definitions Technology & People Data Literacy Data-Driven Improvements ChangeManagement
- 13. DataLumin BUILDING USERSTEWARDSHIP WITHIN GOVERNANCE FRAMEWORK DATA GOVERNANCE COUNCIL DATA TRUSTEE1 DATA STEWARD1 DATA STEWARD2 DATA STEWARD3 DATA TRUSTEE2 DATA STEWARD4 DATA STEWARD5 DATA TRUSTEE3 DATA STEWARD6 DATA STEWARD7 Data Governance Council Primary function of the Data Governance Council is to provide ongoing management and oversight. Council manages • Data governance initiatives • Issues, and escalations to improve and promote • Data Quality and Integrity • Appropriate and ethical use of data • Compliance • Data Literacy and Awareness Data Trustees Those with authority over source Data systems. Data Trustees are accountable for managing, protecting, and ensuring the integrity and usefulness of Data and for upholding policies, system policies, state and union law. Each Data Trustee appoints one or more Data Stewards for the Data Trustee’s specific Data Domain Data Stewards Data Stewards help define, implement, and enforce data management policies and procedures within their specific Data Domain. A Data Trustee may delegate to the Data Steward the authority to represent the Data Trustee in data-related policy discussions
- 14. DataLumin KEY RESPONSIBILITIESOF DATA STEWARDS Data Stewards Data Stewards are the first line of defence and core implementers of policies. Their major responsibilities include • Identifying major data systems where data under the Data Steward’s responsibility resides • Classifying & cataloging data systems according to Data Classification policy, working with security, privacy officers, and review classifications at least annually • Building relevant reports, analyses and dashboards for the functional areas that they are responsible for • Classifying reports and dashboards that deliver or expose data for which the Data Steward is responsible • Reviewing and approving requests for access to Data Sample framework Data Domain Applications Data Trustee Data Steward Steward Area(s) Major Data Systems Marketing Campaign Effectiveness Krishna Bhavna BTL ATL Hubspot Marketo Sales Sales 360 Aasma Abhijeet Sales SFDC Ops Interlock Aasma Pravin Sales Ops SFDC ServiceNow Information Technology Asset Management Sudhir Mary IT & Cybersecurity ServiceNow Splunk
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- 16. DataLumin DataLumin. ATeam that workedin Big 4 Consulting Organizations andWorld-Class Software Companies coming together to provide customers with the best Data experience
- 17. DataLumin WHAT WE SPECIALIZEIN CREATING RIGHT PLATFORMS BUILDING RIGHT MODELS ENGINEERING RIGHT DATA STRUCTURES FORUMULATING RIGHT DATA STRATEGY
- 18. DataLumin WHAT WESPECIALIZE IN INSIGHT SCIENCE DATA SCIENCE DATA ENGINEERING ADVISORY DATA INTEGRATION BIG DATA MANAGEMENT DW & DL AUTOMATION DATA MIGRATION DATAVISUALIZATION CONVERSATIONALAI DATA LITERACY MACHINE LEARNING TEXTANALYTICS & NLP ANALYTICS BLUEPRINT DEPLOYMENT FRAMEWORK ADOPTION SERVICES INDUSTRY SOLUTION DESIGN COE DESIGN
- 19. DataLumin TECH DATA INTEGRATION DW& DL AUTOMATION DATA SCIENCE DATAVIZ/ CONVERSATIONAL AI ENTERPRISE SECURITY
- 20. DataLumin DATA & ANALYTICSCHANGING HOW COMPANIES COMPETE 70% of all Executives report that data and analytics have caused at least moderate changes in their industries’ competitive landscapes in recent years 8% 26% 36% 21% 7% 2% Fundamental Change Significant Change Moderate Change Minimal Change No Change Don’t Know New entrants launch data-and-analytics businesses that undermine traditional competitors’ value propositions Traditional competitors gain an edge by improving core business through data and analytics Companies extract new insights from data that were traditionally unrelated or in different systems Traditional competitors are launching new products, including analytics services Companies are forming data-related partnerships along value chain Traditional competitors are launching new data-and-analytics-related businesses Traditional competitors are pooling their data into a shared utility 50 36 36 27 21 18 7McKinsey CxO Survey
- 21. DataLumin 5 KEY PILLARSTO UNLOCK VALUE & STAY AHEAD Aligned Analytics & Strategy Have a clearly articulated vision and strategy that aligns capabilities with business needs and promotes transparency across functions Flexible Organization & Operating Model Reconfigure an organizational and operating model to best support demand for analytics Empowered Analytics & Governance Design a holistic governance model that establishes clear ownership and accountability for data Innovative Talent Strategies Develop innovative processes and partnerships to recruit, retain and grow in-house talent Modern Technology Platforms Invest wisely in new technology to enable self-service analytics across the business
- 22. DataLumin DATALUMINADDRESSESTHESEAREAS To ensure yourinformation workers a. Get Trusted Data b. Explore freely & make sense of the data c. Derive insights, collaborate and multiply that effect To help you cut through clutter, work with best-in- classTech and get maximum value for the investment
- 23. DataLumin ONE WAYTO MOVE FORWARD 01 TO BE STATE: Study of Objectives at • Organizational Level • Department Level 03 Derive theGaps that need to be addressed to get to theTO- BE state 05 Re-assemble and choose the right path where can start the work 02 AS-IS study of current Data Processes 04 Offer multiple paths to get to theTO-BE state with cost- benefit analysis of each path
- 24. DataLumin Placing Data atthe center of DigitalTransformation
Editor's Notes
- #13 Policies and Standards: The program will determine who has the authority to make decisions regarding access, priorities, and data usage standards, and under what conditions those decisions can be made. Information Quality: Formal and professional data stewardship is an essential part of any data governance program. Those responsible for data stewardship are accountable for the integrity and quality of our data. Privacy, Compliance, and Security: How we institutionally deal with the inherent risk that comes along with curating data is an essential part of the program. The program will develop the risk management strategies and identify ways to operationalize those strategies. Additionally, the program should align with and coordinate with records management custodians to ensure compliance with applicable requirements. Architecture and Integration: Ensuring that there are common data definitions and that those definitions are made available across platforms is essential to enabling informed data-driven decision-making. The program will make decisions on what those definitions are and how we technically support the requirements of those definitions. Guiding Principles Transparency: It should be clear how and when decisions are made and processes are created. Metrics-Driven: We should measure and report on how we are doing against our goals. Consistency: All decisions should be applied consistently. Stewardship: While there will be formal stewardship roles defined, it is everyone’s responsibility to protect the privacy, security, and confidentiality of our data as required. Accountability: Decisions and processes should be audited. Agility: All processes should be able to adapt when appropriate. Change Management: New processes will require a concerted effort in managing change
- #17 DataLumin exists for a reason. We solve the fundamental data problems. To provide the best experience in the data world to ensure customers harness the power behind utilizing the data they possess and need to transform their organization. When people place data at the center of digital transformation, they invariable are at a leap’s distance from competition. That is our Motto - to give customers the best data Experience!
- #18 As DataLumin, we solve all the data problems after you have collected it. We help formulate the right data strategy for you. We help in engineering the right structures that hold your data for easy consumption. We work with ML & AI tech to build the models that uncover the insights. We create the right platforms for you not just to visualize but converse with your data and get the hidden insights that can potentially change how you look at data. We also help your organization become data literate to maximize the time investment people make in working with data day-in and day-out
- #19 And that problem-solving ability is what you can see in what we specialize in. There are 4 pillars we work on. The advisory piece - to create an Analytics Blueprint, a strategy document that talks about what kind of a journey you will need to take given your landscape (both tech and people). A detailed deployment framework that talks about what deployment strategy to undertake and what does it take to create those governance mechanisms to ensure a smooth and successful deployment. Adoption services that create a short, medium and long-term plan that will ensure that the organizations becomes data-driven. Industry specific solution design that gets you the right metrics across different functions from our ever-updated industry repository. And Finally, building a Center of Excellence and this is of particular importance when you are a multi-geo organization and when you have to create an Ops center that will scale with the data needs of your organization.
- #24 There are many ways! But the first step is what we call a Phase Zero. In this, we take the following steps