Data In Action: Business Value of Data
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Lecture on databases for Technology and Operations class at Pepperdine Graziado School of Business. Presented October 2023.
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Data In Action: Business Value of Data
- 1. Technology and Operations Management ISTM 619 Pepperdine Graziadio School of Business Matt Turner, Strategic Advisor mwturner@gmail.com October 16, 2023 Data In Action: Business Impact of Databases
- 2. Agenda • Importance and value of data • The key: putting data into action • Database fundamentals • Data strategy • Types of databases • Use Cases Data and AI • Conclusion *Each person creates 33.67 GB a DAY a day (as of 2022)
- 3. It all starts and ends with the data problem! Roland Busch Deputy CEO, CTO Siemens AG 2019 2018
- 4. 2014
- 5. It’s that easy, right? Just back the data pump over your data and you are all set right?
- 6. Bad data is like manure … it gets everywhere! Susan Lauda Director, Global Advanced Technology AGCO Corp 2019 Lance Stafford Enterprise Architect Chevron Bring consistency to the ‘chaos that exists in the data silos”
- 7. Bad data is like manure … it gets everywhere! Susan Lauda Director, Global Advanced Technology AGCO Corp 2019 Lance Stafford Enterprise Architect Chevron We’re working on opinion, not data
- 8. The Answer • Learn about data! • What data and databases are • How it’s organized and put into action • Fundamental to making good business and technology decisions
- 10. database noun a collection of information that is organized so that it can be easily accessed, managed and updated
- 11. Data in Action Transactional Analytics Video Audio Documents, Messages Reference Data Context* *everything is data 100s / 1000s 10s / 100s
- 12. Relational Approach oRelational Database Management Systems - RDBMS oDefine everything in rows and columns oLists and categories provide context oProven, powerful, simple model for most types of data Title ProductionDate Category AssetType Length Film1 3/1/14 Feature HD Master 2:40 Show1 6/4/13 Series HD720 0:40 Film2 6/4/05 Feature Archive 1:55 Category Feature Series Action Drama Comedy Documentary … Cable Broadcast Drama Comedy … Action Drama Family Documentary …
- 13. But data is … complicated
- 14. Enter NoSQL • Flexible schema • Handle ALL data • Real world has documents, lists, relationships … not all fits into SQL • Pioneered distributed, massive scale out • Flexibility to tune for speed or data consistency • Example: • Digital Twin
- 15. NoSQL Examples digital twin: digital versions of products ? https://www.mongodb.com/blog/post/recap-product-announcements-mongodb-local-london-2023 !
- 16. NoSQL Example: Digital Twin digital twin = digital version of product including all parts and configurations Both! Customers Policies, claims, demographics, products, models …
- 17. NoSQL for ALL your data Type Notes Examples Key-value No schema, simple pairs, Massive scale Redis, DynamoDB Columnar Flexible schema (tablelike), Massive scale Hbase, Cassandra, ScyllaDB Document Schema flexibility, stores ‘as-is’ rich content MongoDB, Couchbase Graph Core data and relationships Neo4J, AllegroGraph Vector Distance! Data behind Large Language Models (LLMs) and ML (Machine Learning) Pinecone, Weaviate Bonus: Hadoop Not a database! Files for processing Spark Cloud + Hybrids Capabilities are merging (document + graph + vector) in cloud systems Snowflake, Databricks, AWS
- 18. Data and AI
- 19. Trusted AI Needs Trusted Data
- 20. Role of data in AI • Train Models • Initial models (ML), training and tuning (LLM) • Trusted, tested, up to date data NOT garbage in, garbage out • Get trusted AI responses • Data sets the context with prompt generation • Tap enterprise data to get the right answers from your LLM • Create new data and queries • Use the answers + interactions to create better data! • AI interactions for insight • What are the most common problems that our customers are seeing? • What are the protein interactions that might lead to new combinations?
- 21. Data and AI Use Cases Customer Inquiry: “I need help with my washer” Lookup customer and ALL product info Interact with customer with that context: “Here is what I can do to help you …” Create a prompt with customer and product context
- 22. Trusted AI Needs Trusted Data
- 23. Key Takeaways
- 24. Key Takeaways • Data is still THE most valuable asset • Your competitive advantage • Trusted AI needs Trusted data • Warning: garbage in, garbage out • Understanding data is key to making good decisions about business and technology
- 25. THANK YOU!
- 26. Resources • Rich Data, Poor Data, Shelly Palmer: https://www.shellypalmer.com/2016/05/rich- data-poor-data-data-rich-data-poor-data- middle-class-not/ • Lance Stafford, Chevron project talk https://www.marklogic.com/resources/chevron- harmonizing-facility-and-equipment-data-on- the-marklogic-data-hub-platform/ • TechTarget definition: https://searchsqlserver.techtarget.com/definitio n/database • NoSQL Design principles from ScyllaDB: https://www.scylladb.com/glossary/nosql- design-principles/ • Bosch Use Case MongoDB https://www.mongodb.com/blog/post/recap- product-announcements-mongodb-local- london-2023 • Generative AI use cases in MetaAcademy GenAI course: https://courses.shellypalmer.com/metacademy- generative-ai • How much data is created each day https://techjury.net/blog/how-much-data-is- created-every-day/
Notes de l'éditeur
- But there were people having the conversation in their industry We do a lot of work with publishers and one of the primary voices for change has been Dr. Sven Fund – then the CEO of DeGruyter a publisher over in Germany. He wrote what I think of as a battle plan for the modern publisher called integrating publishing. It’s a data driven approach to rethinking every part of the business around using data across every part of the business. From planning what content to invest in, to creating it and tailoring it to knowing how it impacts your customers, data can and should play a role … and Sven laid out the plan to get publishers to that point. This was quite a change for an industry still just thinking about content. Shelly Palmer is another voice that was early with a message about data. He worked mostly within Media but his message was to every organization highlighting how the game has changed. He says “Data Rich or Data Poor” that is the ONLY game. Every company is now competing on the battleground of data. Its not your revenue, your number of customers or their engagement. It’s the data you gather that actually matters. What’s more, you aren’t competing against what you think of as your competitors. Its Google, Apple, Facebook … and way above all of them Amazon. Shelly says this to bring people’s attention to the importance of data. And he’s not alone – he is joined by my colleague Michel de Ru. Michel works across a number of industries and at the MarkLogic 360 event last year he issued a call to arms: Industrialize your data! You invest in your processes, your machinery, your people and take care of your capital. And you need to do the same thing your data. Think about how you manage it and, just like your machinery and other assets, industrialize how you deal with it
- And they aren’t alone. Who has heard this phrase Data is the new Oil? Its everywhere … there is even someone saying it’s the not the new oil it the new nuclear. I guess because it keeps delivering value forever? In fact there is so much about this, if you search for Data is the new oil infographic you get 13 million hits! This is my favorite – see the data in the ground – just pump it out and – presto – you get your value! Right? Its that easy, right?
- And they aren’t alone. Who has heard this phrase Data is the new Oil? Its everywhere … there is even someone saying it’s the not the new oil it the new nuclear. I guess because it keeps delivering value forever? In fact there is so much about this, if you search for Data is the new oil infographic you get 13 million hits! This is my favorite – see the data in the ground – just pump it out and – presto – you get your value! Right? Its that easy, right?
- But there were people having the conversation in their industry We do a lot of work with publishers and one of the primary voices for change has been Dr. Sven Fund – then the CEO of DeGruyter a publisher over in Germany. He wrote what I think of as a battle plan for the modern publisher called integrating publishing. It’s a data driven approach to rethinking every part of the business around using data across every part of the business. From planning what content to invest in, to creating it and tailoring it to knowing how it impacts your customers, data can and should play a role … and Sven laid out the plan to get publishers to that point. This was quite a change for an industry still just thinking about content. Shelly Palmer is another voice that was early with a message about data. He worked mostly within Media but his message was to every organization highlighting how the game has changed. He says “Data Rich or Data Poor” that is the ONLY game. Every company is now competing on the battleground of data. Its not your revenue, your number of customers or their engagement. It’s the data you gather that actually matters. What’s more, you aren’t competing against what you think of as your competitors. Its Google, Apple, Facebook … and way above all of them Amazon. Shelly says this to bring people’s attention to the importance of data. And he’s not alone – he is joined by my colleague Michel de Ru. Michel works across a number of industries and at the MarkLogic 360 event last year he issued a call to arms: Industrialize your data! You invest in your processes, your machinery, your people and take care of your capital. And you need to do the same thing your data. Think about how you manage it and, just like your machinery and other assets, industrialize how you deal with it
- But there were people having the conversation in their industry We do a lot of work with publishers and one of the primary voices for change has been Dr. Sven Fund – then the CEO of DeGruyter a publisher over in Germany. He wrote what I think of as a battle plan for the modern publisher called integrating publishing. It’s a data driven approach to rethinking every part of the business around using data across every part of the business. From planning what content to invest in, to creating it and tailoring it to knowing how it impacts your customers, data can and should play a role … and Sven laid out the plan to get publishers to that point. This was quite a change for an industry still just thinking about content. Shelly Palmer is another voice that was early with a message about data. He worked mostly within Media but his message was to every organization highlighting how the game has changed. He says “Data Rich or Data Poor” that is the ONLY game. Every company is now competing on the battleground of data. Its not your revenue, your number of customers or their engagement. It’s the data you gather that actually matters. What’s more, you aren’t competing against what you think of as your competitors. Its Google, Apple, Facebook … and way above all of them Amazon. Shelly says this to bring people’s attention to the importance of data. And he’s not alone – he is joined by my colleague Michel de Ru. Michel works across a number of industries and at the MarkLogic 360 event last year he issued a call to arms: Industrialize your data! You invest in your processes, your machinery, your people and take care of your capital. And you need to do the same thing your data. Think about how you manage it and, just like your machinery and other assets, industrialize how you deal with it
- When you take this to the world of data, and in particular the data layer that can run your business this is what you get – traditional data structures that just fall short You have to define everything up front – all your data and everything your organization does … And then categorize it. In no way will this work – you will end up stripping off context sometimes in layer. You can’t share this data across your organization and so you get what Alan was talking about in terms of the multiple layers of appliations and data One of our customers talks about the result of all this changing of data as operating on opinion, not data!