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DAS Slides: Enterprise Architecture vs. Data Architecture

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Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key inter-relationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall enterprise architecture for enhanced business value and success.

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DAS Slides: Enterprise Architecture vs. Data Architecture

  1. 1. Copyright Global Data Strategy, Ltd. 2019 Master Data Management - Aligning Data, Process, and Governance Donna Burbank Global Data Strategy, Ltd. June 27th, 2019 Follow on Twitter @donnaburbank Twitter Event hashtag: #DAStrategies
  2. 2. Modern Applications Are Fundamentally Different NoSQL Couchbase* Oracle 1K:1 Consumer 1:1 1M:1 IoT TransactionsInteractions Legacy monolithic infrastructure no longer an option to keep up with modern workloads Microservices architecture supports web, mobile and IoT experiences at scale, with performance to match Transactional Analytical Confidential and proprietary. Do not distribute without Couchbase consent. © Couchbase 2019. All rights reserved. Legacy Databases Insufficient *SQL-compatible
  3. 3. Couchbase Behind Today’s Business-Critical Applications Application Customers Infrastructure ManageabilityPerformance at Scale Performance Flight availability, booking, pricing analytics, etc. 7M requests / second <2.5ms response time Real-time crew management, scheduling and resources 41K pilots and crew 148M travelers in 2017 Customer 360 single view, unified notes 210M documents 100K users Developer Agility Caching & session store for single view 2M+ reads/sec. 10M queries/sec. Real-time pricing, product catalog, inventory management 10M+ unique SKUs 35K requests/sec. Security + Availability
  4. 4. Global Data Strategy, Ltd. 2019 Donna Burbank 2 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 Group’s 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 at donna.burbank@globaldatastrategy.com Donna is based in Boulder, Colorado, USA. Follow on Twitter @donnaburbank Twitter Event hashtag: #DAStrategies
  5. 5. Global Data Strategy, Ltd. 2019 DATAVERSITY Data Architecture Strategies • January 24 - on demand Emerging Trends in Data Architecture – What’s the Next Big Thing? • February 18 - on demand Building a Data Strategy - Practical Steps for Aligning with Business Goals • March 28 - on demand Data Modeling at the Environment Agency of England - Case Study • April 25 - on demand Data Governance - Combining Data Management with Organizational Change • May 23 - on demand Master Data Management - Aligning Data, Process, and Governance • June 27 Enterprise Architecture vs. Data Architecture • July 25 Metadata Management: from Technical Architecture & Business Techniques • August 22 Data Quality Best Practices (w/ guest Nigel Turner) • Sept 26 Self Service BI & Analytics: Architecting for Collaboration • October 24 Data Modeling Best Practices: Business and Technical Approaches • December 3 Building a Future-State Data Architecture Plan: Where to Begin? 3 This Year’s Lineup
  6. 6. Global Data Strategy, Ltd. 2019 Today’s Topic Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key inter- relationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Data Architecture is a key component of an overall enterprise architecture for enhanced business value and success. 4
  7. 7. Global Data Strategy, Ltd. 2019 Enterprise Architecture - Definition • Enterprise architecture (EA) is a discipline for proactively and holistically leading enterprise responses to disruptive forces by identifying and analyzing the execution of change toward desired business vision and outcomes. • …by presenting business and IT leaders with signature- ready recommendations for adjusting policies and projects to achieve target business outcomes that capitalize on relevant business disruptions. • EA is used to steer decision making toward the evolution of the future state architecture.1 5 Supporting Business Innovation with a Strong Architectural Foundation 1 Gartner IT Glossary 2013 Innovation Foundation
  8. 8. Global Data Strategy, Ltd. 2019 Enterprise Architecture – Definition for Data Architects • Just as you need to model the data in an organization, you need to model the organization itself: • Motivations & Goals • Business Capabilities • Business Processes • As well as the related technologies that support the organization • Applications • Data • Networks • Etc. 6 Modeling is important on many levels
  9. 9. Global Data Strategy, Ltd. 2019 Data Modeling for Enterprise Architecture • Enterprise Architecture provides a high-level view of the people, processes, applications, and data of an organization • Putting data in business context • How does data link to the rest of my organization? • If I change data, what business processes are affected?
  10. 10. Global Data Strategy, Ltd. 2019 Frameworks for Enterprise Architecture • The Zachman Framework organizes data into the simple categories of: • What • How • Where • Who • When • Why? • Data fits nicely within the “What” column. 8 Zachman Framework https://www.zachman.com
  11. 11. Global Data Strategy, Ltd. 2019 Frameworks for Enterprise Architecture • The TOGAF Architecture Development Method (ADM) developed by the OpenGroup is a step-by- step approach to developing an enterprise architecture. • It provides a detailed framework for building an architecture around Business, Data, Application & Technology. 9 TOGAF EA Framework www.opengroup.org
  12. 12. Global Data Strategy, Ltd. 2019 What EA Model Types are in Use? 10 What Types of Models/Diagrams do you use in your Data/Enterprise Architecture? From Trends in Data Management, a 2019 DATAVERSITY® Report, by Donna Burbank and Michelle Knight – due to be released Sept 2019
  13. 13. Global Data Strategy, Ltd. 2019 Conceptual Data Model • Communication & definition of core data concepts & their definitions • A conceptual data model provides core definitions of key data objects. • It also shows key relationships between data objects. • Even a simple diagram as the one on the right can tell a powerful “story” …. And uncover key business issues and opportunities.
  14. 14. Global Data Strategy, Ltd. 2019 Logical Data Model Place Appear on Contain Belong to Customer customer identifier first name middle initial last name description Product product identifier product name description Order customer identifier (FK) product identifier (FK) order date Product Part Combination product identifier (FK) part identifier (FK) Raw Material material_identifier part identifier (FK) Finished Good finished good identifier part identifier (FK) Subassembly subassembly identifier part identifier (FK) Part part identifier part name description • A logical data model describes key business rules and definitions. • Attributes are typically shown. • Cardinality specifies additional detail regarding relationships. …. The Logical Model defines additional detail regarding data entities, attributes, and their relationships.
  15. 15. Global Data Strategy, Ltd. 2019 Business Capability Models • A business capability model outlines the core functional areas of the organization. • Note: this is not the same as an organizational chart • Capabilities can be overlaid with key data domains to create a “heat map” of cross-functional data usage. 13 Core Business Shared Services Artful Art’s Business Capabilities Etc. – sample subset only Product Development R&D Product Management Product Manufacturing Packaging Marketing Product Messaging Branding Product Launch Campaign Development Lead Generation Pricing Sales Pipeline Management Customer Relationship Quotes & Tenders Research & Development Branding & Go-to-Market Partner Management Sales & Distribution Human Resources Recruitment Employee Training Performance Management Legal Compliance Contract Management Data Domains Customer Product Account Etc.
  16. 16. Global Data Strategy, Ltd. 2019 Data-Driven Merger for Financial Services The combined information assets of both companies is one of our biggest strategic advantages. - CEO • A key driver for a recent merger of two large financial institutions was the integration of data assets • Streamlining the merger of the two organizations by integrating the data assets • Identify ways in which data can be used to strategic advantage • Organizational Structure & Business Capability Alignment were critical • Understanding how data was used across the organization • Identifying efficiencies & opportunities for collaboration Business Capabilities Company A Business Capabilities Company B Common Data Foundation
  17. 17. Global Data Strategy, Ltd. 2019 Process / Workflow Models • Process models are a helpful tool for describing core business processes. • “Swimlanes” outline organizational considerations • Data can be mapped to key business processes to understand creation & usage of information. • They are particularly helpful for areas such as Master Data Management (MDM) where process is critical to data stewardship & integration. 15 Identifying key data dependencies in core business processes
  18. 18. Global Data Strategy, Ltd. 2019 CRUD Matrix Product Development Supply Chain Accounting Marketing Finance Product Assembly Instructions C R Product Components C R Product Price C U R Product Name C U,D Etc. 16 Create, Read, Update, Delete • CRUD Matrices shows where data is Created, Read, Updated or Deleted across the various areas of the organization. • They can be created by department, by system/application, etc. • This can be a helpful tool in data governance & data quality.
  19. 19. Global Data Strategy, Ltd. 2019 Process Models & CRUD Fit Well Together • Business Process Models describe key activities within the organization. • Linking these processes to the data that is Created, Updated, or Deleted (CRUD) is important to understanding data usage. Customer Order Account Invoice Product Receive Customer Order R C C, R Process Customer Order C,R,U R,U R Fill Order R,U R,U R,U Send Invoice R,U R,U C CRUD Matrix Business Process Model
  20. 20. Global Data Strategy, Ltd. 2019 Linking Data with Process for Master Data Management • 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 • BPMN diagrams to identify the flow of information • CRUD Matrixes to understand usage, stewardship & ownership 18 Managing the Data that Runs the Business Product Creation & Testing Menu Display & Marketing Supply Chain Point of Sale & Restaurant Operations
  21. 21. Global Data Strategy, Ltd. 2019 Developers Managers Enterprise Data Management Part of a Data Strategy is Defining Fit for Purpose Solutions Operational Data Reporting & Analytics Master & Reference Data Metadata CRM Customer X orders Product Y at 2pm on Oct 24, 2017 Sales CRM ERP Customer Care IoT Customer X calls Support at 1pm on Nov 1, 2017 Inventory consists of x number of Product X components on Oct 24, 2017 Supply Chain Customer turns on foot warmer at 11pm on Oct 30, 2017 Product Team Customer CRM & other systems DW What were total sales for Product X in 2016 by region? Lake Operational Reporting Enterprise Historical Reporting Analytics & Discovery What variables most influence customer repeat purchases? Limited Personal Use Limited ad hoc analysis for small data sets. Not recommended for enterprise data management. UCM UPM “Golden Record” for Customer, Product, etc. Mary Smith lives on 101 Main ST, Detroit, MI and has been a customer since 2011 Product 720 has a product code of SS720 & a suggested retail price of $11,000 USD. Business & Technical Context & Descriptions ELT How many support calls are currently open? Analytics Team Managers Reference Data Hierarchies The Sales management reporting hierarchy is structured as follows. Valid Return Codes are “X, Y, & Z” State Codes include MA, MD MI … Applications DW Etc DW Etc DW Etc Business Glossary How is Total Sales calculated? What is a Qualified Lead? Business Users Data Models How do we uniquely identify a customer? Can a customer have more than 1 email? Data Dictionary What is this DW table used for? The standard length for customer ID is CHAR(12) Developers Data Lineage How was this field calculated? What will break downstream if I make a change? Developers Developers Business Users Access
  22. 22. Global Data Strategy, Ltd. 2019 System Architecture Diagram • High-level system architecture diagrams can create a “big picture” of how systems and their components fit together. 20 Data Analysis & Discovery – Data Lake Enterprise Systems of Record Data Governance & Collaboration Master & Reference Data Data Warehouse Data MartsOperational Data Security & Privacy Sandbox Lightly Modeled Data Data Exploration Reporting & Analytics Advanced Analytics Self-Service BI Standard BI Reports
  23. 23. Global Data Strategy, Ltd. 2019 Current Platform Use 21 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% Time Series database Other (please specify) Semantic technologies Don’t know Real-time/streaming database IoT data Graph database Open data Social Media Non-relational on-premises database Media files (videos, photos, etc.) Non-relational cloud-based database Big Data platforms (e.g. Hadoop Ecosystem) XML Legacy systems (e.g. Mainframe, COBOL, etc.) JSON Relational cloud-based database Packaged applications (e.g. ERP, CRM, etc.) Spreadsheets Relational on-premises database Which of the following data sources or platforms are you currently using? [Select all that apply] From Trends in Data Management, a 2019 DATAVERSITY® Report, by Donna Burbank and Michelle Knight – due to be released Sept 2019
  24. 24. Global Data Strategy, Ltd. 2019 Future Platform Use 22 0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00% 40.00% 45.00% 50.00% Other (please specify) Time Series database Semantic technologies Open data Non-relational on-premises database Legacy systems (e.g. Mainframe, COBOL, etc.) IoT data Real-time/streaming database Media files (videos, photos, etc.) Graph database Social Media Don’t know XML Non-relational cloud-based database Big Data platforms (e.g. Hadoop Ecosystem) Spreadsheets JSON Packaged applications (e.g. ERP, CRM, etc.) Relational on-premises database Relational cloud-based database From Trends in Data Management, a 2019 DATAVERSITY® Report, by Donna Burbank and Michelle Knight – due to be released Sept 2019
  25. 25. Global Data Strategy, Ltd. 2019 Summary • Enterprise Architecture provides a series of models and diagrams to describe the organization • Data models and data-centric models play a key role in any Enterprise Architecture • While the number and diversity of platforms is increasing it is important to: • Focus on the business need and application • Design fit-for-purpose solutions using a number of interrelated technologies • Adding some enterprise architecture components to your projects can help focus on business value
  26. 26. Global Data Strategy, Ltd. 2019 DATAVERSITY Data Architecture Strategies • January 24 Emerging Trends in Data Architecture – What’s the Next Big Thing? • February 18 Building a Data Strategy - Practical Steps for Aligning with Business Goals • March 28 Data Modeling at the Environment Agency of England - Case Study (w/ guest Becky Russell from the EA) • April 25 Data Governance - Combining Data Management with Organizational Change (w/ guest Nigel Turner) • May 23 Master Data Management - Aligning Data, Process, and Governance • June 27 Enterprise Architecture vs. Data Architecture • July 25 Metadata Management: from Technical Architecture & Business Techniques • August 22 Data Quality Best Practices (w/ guest Nigel Turner) • Sept 26 Self Service BI & Analytics: Architecting for Collaboration • October 24 Data Modeling Best Practices: Business and Technical Approaches • December 3 Building a Future-State Data Architecture Plan: Where to Begin? 24 Join Us Next Month
  27. 27. Global Data Strategy, Ltd. 2019 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 technology solution. • Clear & Relevant: We provide clear explanations using real-world examples. • Customized & Right-Sized: Our implementations are based on the unique needs of your organization’s size, corporate culture, and geography. • High Quality & Technically Precise: We pride ourselves in excellence of execution, with years of technical expertise in the industry. 25 Data-Driven Business Transformation Business Strategy Aligned With Data Strategy Visit www.globaldatastrategy.com for more information
  28. 28. Global Data Strategy, Ltd. 2019 Questions? 26 • Thoughts? Ideas?

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