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DAS Slides: Graph Databases — Practical Use Cases

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DAS Slides: Graph Databases — Practical Use Cases

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Graph databases are seeing a spike in popularity as their value in leveraging large data sets for key areas such as fraud detection, marketing, and network optimization become increasingly apparent. With graph databases, it’s been said that ‘the data model and the metadata are the database’. What does this mean in a practical application, and how can this technology be optimized for maximum business value?

Graph databases are seeing a spike in popularity as their value in leveraging large data sets for key areas such as fraud detection, marketing, and network optimization become increasingly apparent. With graph databases, it’s been said that ‘the data model and the metadata are the database’. What does this mean in a practical application, and how can this technology be optimized for maximum business value?

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DAS Slides: Graph Databases — Practical Use Cases

  1. 1. Copyright Global Data Strategy, Ltd. 2020 Graph Databases: Practical Use Cases Donna Burbank Global Data Strategy, Ltd. December 1st, 2020 Follow on Twitter @donnaburbank @GlobalDataStrat Twitter Event hashtag: #DAStrategies
  2. 2. 1December 2020 • Based in Boston • Origins in IBM and Netezza • Featuring enterprise-scale OLAP graph database engine About Cambridge Semantics Scalable knowledge graphs for modern data integration and analytics.
  3. 3. DRUGS@FDA -Approved Single View Of The Drug Product Why Knowledge Graph: FDA’s Data Fabric
  4. 4. Single View Of The Drug Product A Knowledge Graph is a connected graph of data and metadata that richly models real-world entities. Safety Report Patient Drug Reaction Summary Product Exclusivity Patent canonical PRODUCT The canonical product concept connects related data about drugs from siloed sources
  5. 5. DRUGS@FDA -Approved Appl_No Approval_Date Applicant 205613 10/07/2014 Valeant Pharms 212379 10/18/2019 Foamix … … … ApplNo ProductNo DrugName ActiveIngredient 205612 007 ROPIVACAINE HYDROCHLORIDE 205613 001 UCERIS BUDESONIDE … … Orange Book-Products 12.2 Pharmacodynamics Treatment with glucocorticosteroids, including UCERIS rectal foam, is associated with a suppression of endogenous cortisol concentrations and an impairment of the hypothalamic- pituitary-adrenal (HPA) axis function. DailyMedDrugs@FDA-Products 205613 APPLNO Drug CONTAINS BUDESONIDE ACTIVEINGREDIENT UCERIS DRUGNAME Product 2MG/ACTUATION STRENGTH ABOUT Pharmacodynamics glucocorticosteriods endogenous cortisol SUPRRESION TREATMENT 10/07/2014 APPROVAL_DATE Product APPLICANT Valeant Pharms Application 205613 APPL_NO isSponsor Product (Canonical) Knowledge graphs are connected graphs of data and metadata that richly model real-world entities.
  6. 6. ©2020 Cambridge Semantics Inc. All rights Knowledge Graphs Simplify Complexity Simplifies access to complex data to address unanticipated questions Quickly profiles, connects and harmonizes data from multiple sources, including unstructured Presents tailored views, services and experiences to different personas with conceptual models Flexibly accommodates new data sources and use cases on the fly, with minimal impact Scales horizontally to accommodate enterprise data fabric scale - Cloud agnostic
  7. 7. What’s makes AnzoGraph DB powerful BUILT ON STANDARDS • SPARQL/RDF • SPARQL*/RDF* • Cypher/BOLT • RDFS+ DATA CONNECTIVITY • Remote access 200+ data sources • Data Virtualization • ELT, ETL, Streaming FASTEST DATA LOADING • Parallel data loading • 250 GB/hr/32vCPU server HORIZONTAL SCALABILITY • Linear scaling to handle billions or trillions of triples FASTEST QUERY & RICH ANALYTICS • Graph Algorithms • Data Science Algorithms • BI/DW Analytics • Inferencing • Geospatial Algorithms • Build-Your-Own 217x AnzoGraph DB when compared to Neo4j on and industry standard TPC-H benchmark 113x AnzoGraph DB LUBM Benchmark over previous fastest results 10-300x AnzoGraph DB vs SPARK SQL and SPARK GraphFrames Analytical Benchmarks
  8. 8. A scalable, knowledge graph platform for modern data integration and analytics Anzo connects and models related data in a real-world representation of data at scale, surfacing new insights and fueling pervasive analytics. Knowledge Graph Management and Metadata Catalog AnzoGraph MPP OLAP Knowledge Graph Engine Enterprise-grade cloud deployment and security
  9. 9. 8 Thank you
  10. 10. Copyright Global Data Strategy, Ltd. 2020 Graph Databases: Practical Use Cases Donna Burbank Global Data Strategy, Ltd. December 1st, 2020 Follow on Twitter @donnaburbank @GlobalDataStrat Twitter Event hashtag: #DAStrategies
  11. 11. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com 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 awarded the Excellence in Data Management Award from DAMA International. 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 several books 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 @GlobalDataStrat Twitter Event hashtag: #DAStrategies
  12. 12. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com DATAVERSITY Data Architecture Strategies • January 23 Emerging Trends in Data Architecture – What’s the Next Big Thing? • February 27 Building a Data Strategy - Practical Steps for Aligning with Business Goals • March 26 Cloud-Based Data Warehousing – What's New and What Stays the Same • April 23 Master Data Management – Aligning Data, Process, and Governance • May 28 Data Governance and Data Architecture – Alignment and Synergies • June 25 Enterprise Architecture vs. Data Architecture • July 22 Best Practices in Metadata Management • August 27 Data Quality Best Practices • September 24 Data Virtualization – Separating Myth from Reality • October 22 Data Architect vs. Data Engineer vs. Data Modeler • December 1 Graph Databases: Practical Use Cases 3 This Year’s Lineup
  13. 13. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com DATAVERSITY Data Architecture Strategies • January Emerging Trends in Data Architecture – What’s the Next Big Thing? • February Building a Data Strategy - Practical Steps for Aligning with Business Goals • March Data Modeling Case Study – Business Data Modeling at Kiewit • April Master Data Management – Aligning Data, Process, and Governance • May Data Architecture, Solution Architecture, Platform Architecture – What’s the Difference? • June Enterprise Architecture vs. Data Architecture • July Best Practices in Metadata Management • August Data Quality Best Practices (with guest Nigel Turner) • September Data Modeling Techniques • October Data Governance: Aligning Technical & Business Approaches • December Data Architecture for Digital Transformation 4 Next Year’s Lineup - 2021
  14. 14. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com 3 What We’ll Cover Today 5 • Graph databases are seeing a spike in popularity as their value in leveraging large data sets for key areas such as fraud detection, marketing, and network optimization become increasingly apparent. • With graph databases, it’s been said that ‘the data model and the metadata are the database’. • What does this mean in a practical application, and how can this technology be optimized for maximum business value?
  15. 15. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com What is a Graph Database? • A graph database uses a set of nodes, edges, and properties to represent and store data. • With graph databases, the relationships between data points often matter more than the individual points themselves. In order to leverage those data relationships, your organization needs a database technology that stores • These relationships can help you discover new insights from your data. 6
  16. 16. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com Graph Database = Thing Relates to Thing 7
  17. 17. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com Graph Database = Thing Relates to Thing 8 Node Vertice Edge Relationship The more formal way of referring to “thing relates to thing” is “Nodes & Edges”, “Vertices & Relationships”, etc.
  18. 18. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com Graph Databases Mirror the Way We Think 9 Squirrel! I should go visit Mary I wonder how her brother John is doing? Is he still dating Stephanie? …In the mind, as in data, there are always random data points… Do they still have that house at the Lake? Riding their boats on the lake was great. Remember when John crashed the boat? Like my toy as a child. Graph databases can be intuitive to many, since they mirror the way the human brain typically thinks – through Association.
  19. 19. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com “Traditional” way of Looking at the World: Hierarchies • Carolus Linnaeus in 1735 established a hierarchy/taxonomy for organizing and identifying biological systems. Kingdom Phylum Class Order Family Genus Species
  20. 20. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com “New” Way of Looking at the World - Emergence In philosophy, systems theory, science, and art, emergence is the way complex systems and patterns arise out of a multiplicity of relatively simple interactions. - Wikipedia
  21. 21. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com Graph Databases Combine Flexibility w/ Structure & Meaning • In many ways, graph databases provide the “best of both worlds”. 12 Flexibility of the “New World” of Discovery & “Emergence” Structure & Meaning of the “Old World” through Ontologies+
  22. 22. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com It’s All About Relationships • In graph databases, relationships are first class constructs. • Rather ironically, relational databases lack relationships. • In relational databases, relationships are enforced through joins and constraints. • NoSQL (e.g. Key Value) databases are also weak at supporting relationships. 13 “A relational database isn’t about relationships, it’s about constraints.” – Karen Lopez Customer Account Is Owner Of <Customer> <Owner Of> <Account>
  23. 23. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com 14 Use Cases for Graph Databases
  24. 24. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com Social Networks 15 Donna Sad, Lonely Person who doesn’t like data Who are the cool kids? i.e. People linked with Donna
  25. 25. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com X Degrees of Separation – “The Bacon Number” • What’s Audrey Hepburn’s “Bacon Number”? i.e. degrees of separation/relation to actor Kevin Bacon • As always, metadata and data quality are important., i.e Which Audrey Hepburn? 16Courtesy of oracleofbacon.org
  26. 26. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com Fraud Detection in Online Transactions • Online transactions typically have certain identifiers, e.g. User ID, IP address, geo location, tracking cookie, credit card number, etc. • Graph patterns can help detect fraud, e.g. • The more interconnections exist among identifiers, the greater the cause for concern. • Typically they would be 1:1. • Some variations may occur, e.g. Multiple credit cards with one person. Families using same machine, etc. • Large and tightly-knit graphs are very strong indicators that fraud is taking place. • Triggers can be put into place so that these patterns are uncovered before they cause damage. 17 IP1 IP1 IP1 IP1 IP1 IP1 IP1 IP1 IP1 IP1 CC1 CC2 CC3 CC4 CC5 CC6 CC7 CC8 CC9 CC10 CC11 CC12 CC13 CC14 CC15 CC16 CC17 Fraud? FamilyPersonal & Business Card
  27. 27. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com Recommendation Engines • Recommendation Engines are familiar to most of us who do any online shopping. • These engines can be powered by a graph database, e.g. • Capture a customer’s browsing behavior and demographics • Combine those with their buying history to provide relevant recommendations 18
  28. 28. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com Data Quality & Volume Matters • Recommendation engines are based on evaluating data sets. If those data sets are faulty or of poor quality, your results will be flawed. • Especially if the data sets are small 19
  29. 29. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com Master Data Management (MDM) • Master Data Management (MDM) is the practice of identifying, cleansing, storing & governance core data assets of the organization (e.g. customer, product, etc.) • There are many architectural approaches to MDM. Two are the following: 20 Centralized -- Commonly Relational Virtualized/Registry – Commonly Graph MDM Virtualization Layer • Core data stored in a common schema in a centralized “hub”. • Used as a common reference for operational systems, DW, etc. • Data remains in source systems. • Referenced through a common virtualization layer. BOTH require the same core foundation of data quality, parsing & matching, semantic meaning, data governance, etc. in order to be successful… and that’s usually the hardest stuff.
  30. 30. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com 21 When you have a Hammer, everything looks like a nail i.e. Data Warehouses serve a particular purpose for aggregating & summarizing data. Not ideal for graph databases. Graph Databases for Data Warehousing
  31. 31. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com Data Warehousing & Enterprise Knowledge Graph 22 Data Warehouse …Show me Total Sales by Region and by Customer each month in 2017 Enterprise Knowledge Graph Relational & Dimensional data model Graph data model …Who are my most influential customers. (with the most connections)
  32. 32. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com Data Management & Ballroom Dancing “First you dance with yourself, then with your partner, then you dance with the room.” 23
  33. 33. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com An Enterprise Knowledge Graph Provides a Holistic View of the Organization through Relationships 24 “First you dance with yourself, then with your partner, then you dance with the room.” Customer Data Data Quality & Semantics are important for core enterprise data assets. Name: Audrey Hepburn DOB: May 4, 1929 Current Customer: No But the true value is in the interrelationships between data assets. Mother of Name: Luca Dotti DOB: February 8, 1970 Current Customer: Yes Purchased Yacht Insurance Purchased Home Insurance Filed a Claim
  34. 34. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com 3 Who is Using Graph Databases? 25 Graph Databases currently have lower adoption than other platforms, according to a recent DATAVERSITY survey. * Trends in Data Management, a 2020 DATAVERSITY® Report, by Donna Burbank and Michelle Knight
  35. 35. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com 3 Who is Using Graph Databases? 26 For future implementations, there is growing interest in graph databases and technologies 18.5% of respondents are looking to implement graph within the next 1-2 years. * Trends in Data Management, a 2020 DATAVERSITY® Report, by Donna Burbank and Michelle Knight
  36. 36. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com 3 Summary • Graph Databases provide powerful enterprise-wide association using simple constructs • “Thing Relates to Thing” • Relationships are first class constructs • Enterprise use cases are best suited to those that focus on interrelationships between data points • Social Networks • Fraud Detection • Recommendation Engines • Enterprise Knowledge Graph • Graph adoption, while lower than traditional technologies, is has growing interest.
  37. 37. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com 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. 28 Data-Driven Business Transformation Business Strategy Aligned With Data Strategy Visit www.globaldatastrategy.com for more information
  38. 38. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com DATAVERSITY Data Architecture Strategies • January Emerging Trends in Data Architecture – What’s the Next Big Thing? • February Building a Data Strategy - Practical Steps for Aligning with Business Goals • March Data Modeling Case Study – Business Data Modeling at Kiewit • April Master Data Management – Aligning Data, Process, and Governance • May Data Architecture, Solution Architecture, Platform Architecture – What’s the Difference? • June Enterprise Architecture vs. Data Architecture • July Best Practices in Metadata Management • August Data Quality Best Practices (with guest Nigel Turner) • September Data Modeling Techniques • October Data Governance: Aligning Technical & Business Approaches • December Data Architecture for Digital Transformation 29 Next Year’s Lineup - 2021
  39. 39. Global Data Strategy, Ltd. 2020 www.globaldatastrategy.com Questions? 30 • Thoughts? Ideas?

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