Mark logic Industrialize Your Data IOT Berlin Sept 2019
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Data is a big part of the Industry 4.0 conversation but it’s not often a topic in its own right. IOT devices and sensors are creating more data than ever, digital twins need accurate data to impact operations, and the digital thread requires integrated and accessible data. These concepts are all key to industrial organizations being able to improve their products and services, better navigate increasingly complex business environments, and transform for the future. And they all need data to succeed. But getting value from all that data isn’t easy. Many traditional data approaches fall far short of being able to manage the complexity and variability of today’s industrial data and, critically, being able to make that data securely and operationally available. This talk will focus on how leading industrial organizations like Airbus, Eaton, Siemens, Chevron and Boeing are tackling these challenges head on with a new, data-centric approach called the Data Hub. These organizations are “industrializing their data” – investing in data as an asset that’s as essential as the people, processes and materials powering it. With the Data Hub, their projects are creating efficiency, improving quality and safety, and enabling workers today while building a foundation of data across their organizations. Join this session to learn how you too can industrialize your data and hear about the leaders delivering on the vision of Industry 4.0!
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Mark logic Industrialize Your Data IOT Berlin Sept 2019
- 1. 17 September 2019© MARKLOGIC CORPORATION Industrialize Your Data and Deliver Industry 4.0 Matt Turner CSO Manufacturing Matt.turner@marklogic.com @Matt_turner_nyc #MarkLogic
- 2. The Importance of Data
- 3. Isaac Sacolick President, StarCIO 2019 Bad data is like manure … it gets everywhere! Key to Digital Transformation is knowing where data comes from and how you can use it Susan Lauda Director, Global Advanced Technology AGCO Corp 2019
- 4. Isaac Sacolick President, StarCIO 2019 Bad Data is Like Manure … it gets everywhere! Key to Digital Transformation is knowing where data comes from and how you can use it Susan Lauda Director, Global Advanced Technology AGCO Corp
- 5. 2014
- 7. Alan Morrison Senior Research Fellow PWC, 2018 IOT and Digital Twin are Here
- 8. Alan Morrison Senior Research Fellow PWC, 2018
- 9. Alan Morrison Senior Research Fellow PWC
- 10. What Does This Mean For Us?
- 11. Manufacturers Need a 360° View Create better products Navigate complex business Transform for the future 360° view Unified Actionable Real-time Governed
- 12. Impact of Integrating Data Better Products Connected technology will enable innovative new offerings Simplification Business environments are more and more complex Future Ready Digital transformation is just getting started 59activities could be automated 22B# of active IoT devices 2025 2 % MFG 3 INDUSTRY 4. 0 | Interconnectivity, automation, machine learning, and real-time data improved efficiency 30% i4.0 adopters
- 13. Guido Jouret Chief Digital Officer ABB Digital Twins: Two of a Kind Digital Engineering 24/7 7.5billion Potential digital twins
- 14. “An important factor in realizing the value of [digital] twins is an accurate and complete picture of the part, component, product, assembly line and even worker skillset” Matt Turner MarkLogic Digital Twins: Two of a Kind Digital Engineering 24/7 Industry 4.0: How to Navigate Digitization of the Manufacturing Sector McKinsey & Co. April 2015
- 15. What Should We Do?
- 16. The Answer: Michel de Ru MarkLogic, 2018 Industrialize your data!
- 17. Industrialize Your Data Means • Invest in data • Treat data as a first class asset • Make data universally accessible
- 18. Traditional Approach = Fixed Usage Define everything in rows and columns Narrow use to specific purpose Creates complexity for multiple complex types Fix categories into hierarchies Define single view of product or part Result: Inflexible data can’t be used across all parts of the business Part Design Category Source Specs Piston AutoC 542 Power MFG Line 195 64mm|1 8mm|58 Air Sensor CADs HY98f Control Partner 345 5874h/I Caliper ACD404 Braking Archive CF5 Category Control Power Braking Steering Navigation Sensors … Combustion Engine Electric Intake Exhaust Sensors … Battery Rotor Sensors …
- 19. Schema Flexibility and Semantics! Part Name Spec Lineage Production System Source Dates Security <component> Car Model1 <Model> 2018 <production line> braking <system> Car Make <product> Caliper <part> is used in used in used in Is part ofis part of control <system> Used in
- 20. Data Hub Pattern 360 VIEW OF INDUSTRY ____________________________________ INDUSTRIALIZE YOUR DATA Improve Products Navigate Complexity Prepare for the future SUPPLY CHAIN, PARTS, COMPONENTS ASSET MANAGMENT DOCUMENTATION AND RESEARCH ERP, HR, SECURITY AND OTHER ENTERPRISE DATA MANUFACTURING SYSTEMS HARMONIZATION SMART MASTERING GOVERNANCE SECURITY CLOUD READY DOCUMENTATION PORTALS BUSINESS ANALYSIS TOOLS OTHER APPS INDUSTRIAL DATA
- 21. Industrialize Your Data in Action
- 22. Flight Test Data Hub for Analytics and Parts Lineage Greater data efficiency for complex analysis across 600,000 parameters all stored in different silos Agility to address new requirements in hours, not days Faster plane delivery with no compromise on safety
- 23. Graph of Events (temporal patterns) Unstructured text Structured data TEST A/C Flight Crew Report Sensor data Indexing algorithm Test Meta-data + Avionic configuration Text index of Context & Snags Rich Metadata boolean index Storage and processing DEA: Multisource search For Aircraft / test / time zones May 2019 DEA presentation
- 24. Multiple output format Ready to be integrated in an analytic workflow
- 25. Refinery Data Hub for a 360º View of Assets Built app 4x faster than with Oracle Savings of $5M per year Real-time data access for safer, better decisions “Maintenance and inspections involve huge amounts of narrative context. It’s not a traditional transaction and it’s coming from multiple sources. MarkLogic does a really good job analyzing all that data.” IT Manager, Upstream New Capabilities Delivery CHEVRON
- 27. ERP Integration for a 360º View of the Business Integrated 210 ERP systems (Oracle, SAP, NetSuite) 5x faster delivery time compared to Oracle Exadata Single source of truth to make informed decisions “As you figure out your requirements, you can add and adjust your data…you don’t break anything.” Architect EATON
- 28. 12© 2018 Eaton. All rights reserved.. MarkLogic – Technical Advantages Benefits: • Flexible data model • Envelopes: conformed and and local data • Data model versioning Benefit: • Business transform logic all in one spot Benefit: • EL is much simpler than ETL • MarkLogic offers several technical advantages over traditional tools • Deployment Simplicity • Clustered Architecture • MarkLogic capabilities extend the Data Hub’s flexibility • Semantics • Search • Many APIs – or build your own
- 29. Industrialize Your Data! Leading Industrial Organizations Delivering Industry 4.0 COMPLEX MANUFACTURING Discrete, Heavy Industry ENERGY + CHEMICAL Process manufacturing INDUSTRIAL DATA Industry 4.0 Focused Organizations PRASA DHL SOLUTIONS
- 30. Industrialize Your Data @ Booth #13 Industry 4.0 Needs Modern Data Solutions. We’ve built a site to show you how to use data to deliver on the promise of industry 4.0. Check it out! www.marklogic.com/industry4.0 Visit us at Booth 13
- 31. Thank you Matt Turner, MarkLogic CSO Manufacturing Matt.turner@marklogic.com @matt_turner_nyc #MarkLogic
- 32. Resources • Importance of Data • Rich Data, Poor Data, Shelly Palmer: https://www.shellypalmer.com/2016/05/ri ch-data-poor-data-data-rich-data-poor- data-middle-class-not/ • Industrialze your Data:, Michel de Ru: https://www.slideshare.net/MicheldeRu/i ndustrializing-data • Semantic Data Layer • Alan Morrison Keynote - https://www.slideshare.net/AlanMorri son/collapsing-the-it-stack-clearing- a-path-for-ai- adoption?from_action=save • Plus recording of the talk (+18min) -> https://www.facebook.com/fhstp/vide os/308669336596727/ Digital Twins Digital Twins Two of a Kind: https://www.digitalengineering247.co m/article/two-of-a-kind/Digital-Twin McKinsey Industry 4.0: https://www.mckinsey.com/business- functions/operations/our- insights/industry-four-point-o-how- to-navigae-the-digitization-of-the- manufacturing-sector
Notas del editor
- I’m going to start with something that seems obvious … the importance of data But, before I get into this, I do want to remind everyone that going back even 5 years, this was not an obvious topic. We were talking about apps and especially the mobile experience and the new wave of BI … but not about the data itself as a topic
- But there were people having the conversation in their industry Shelly Palmer is a 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 Shelly Palmer is a 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?
- And on this topic, we are just starting to hear from the experts. I hope Alan Morrison as one of these visionaries. He gave a keynote at the Semantic conference in August that was a real call to arms for everyone in THIS room to evangelize that you do need more than just data. He was specifically talking about the vast gap between the vision of a unified IT stack and being able to leverage AI and the reality of the many silos of applications. He specifically is looking at who is out there paying attention to this problem and he put up this slide – the top 10 companies in the world And of them, fully 9 are doing more than just collecting data. They are investing in Linked Data – creating knowledge graphs and connecting their data to realize its value He isn’t alone – Kurt Cagle makes a bold statement about the rise of Ontology will be a critical business advantage. And then there is this paper about the state of AI. Alan also goes into this in his talk – AI without the meaning and connections in the data is just going to fall short. Specifically they make this statement – that nearly every problem comes down to graphs of relationships among entities!
- And on this topic, we are just starting to hear from the experts. I hope Alan Morrison as one of these visionaries. He gave a keynote at the Semantic conference in August that was a real call to arms for everyone in THIS room to evangelize that you do need more than just data. He was specifically talking about the vast gap between the vision of a unified IT stack and being able to leverage AI and the reality of the many silos of applications. He specifically is looking at who is out there paying attention to this problem and he put up this slide – the top 10 companies in the world And of them, fully 9 are doing more than just collecting data. They are investing in Linked Data – creating knowledge graphs and connecting their data to realize its value He isn’t alone – Kurt Cagle makes a bold statement about the rise of Ontology will be a critical business advantage. And then there is this paper about the state of AI. Alan also goes into this in his talk – AI without the meaning and connections in the data is just going to fall short. Specifically they make this statement – that nearly every problem comes down to graphs of relationships among entities!
- And on this topic, we are just starting to hear from the experts. I hope Alan Morrison as one of these visionaries. He gave a keynote at the Semantic conference in August that was a real call to arms for everyone in THIS room to evangelize that you do need more than just data. He was specifically talking about the vast gap between the vision of a unified IT stack and being able to leverage AI and the reality of the many silos of applications. He specifically is looking at who is out there paying attention to this problem and he put up this slide – the top 10 companies in the world And of them, fully 9 are doing more than just collecting data. They are investing in Linked Data – creating knowledge graphs and connecting their data to realize its value He isn’t alone – Kurt Cagle makes a bold statement about the rise of Ontology will be a critical business advantage. And then there is this paper about the state of AI. Alan also goes into this in his talk – AI without the meaning and connections in the data is just going to fall short. Specifically they make this statement – that nearly every problem comes down to graphs of relationships among entities!
- So what’s going on here? Well to get to the heart of this, I want to ask you ONE question. Get ready because I’m going to ask you to raise your hand and take this very seriously
- Data is becoming an important asset for Manufacturers and other industrial organizations. With a better view of the data across their organizations, they can: Create better products Navigate complex business environments Transform for the future
- Across industry there are big changes to nearly every part of the process of designing, sourcing, creating, distributing and servicing their products and output. This has been called Industry 4.0 and is considered to be the 4th Industrial revolution. At the heart of this change, is the rise in the importance of data. These figures speak to the coming challenges and role of data in industry; 1. As part of ‘industry 4.0’ adoption, efficiency can be improved up to 30% https://www.bain.com/insights/industry-4-0-getting-digital-manufacturing-right/?utm_source=twitter&utm_medium=social_organic&utm_content=2613836802 2. But the data deluge is just beginning – there will be 22B IOT devices by 2025. Up from ????? now! 2 - https://iot-analytics.com/state-of-the-iot-update-q1-q2-2018-number-of-iot-devices-now-7b/ 3. And there is plenty of room to improve – 59% of current processes could benefit from further automation https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/where-machines-could-replace-humans-and-where-they-cant-yet
- So what’s going on here? Well to get to the heart of this, I want to ask you ONE question. Get ready because I’m going to ask you to raise your hand and take this very seriously
- How do we address these challenges and deliver the promise of Industry 4.0? Industrialize Your Data! Invest in your data just like you would invest in your equipment, people and assets.
- 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!
- Combined, these two data models are key to creating that data layer and enabling you to actually make data the foundation of your business This is critical – because there is a balance here. In the world of semantics and linked data, there are huge gains to be made in creating ontologies that match the real world and then linking data to those ontologies But there is also a role for just a document – things that belong just to the document like dates, titles and of course the actual –these are perfectly OK in the world of XML. And also in this model the connecting triple is part of the document – also making it a graph that enables you to have data integrity.
- All of these solutions are delivered with the MarkLogic data hub Unique to Manufacturing is the ability to manage and integrate complex data sets. Supply chain data sources include: Siemens PLM, Dassault PLM, Geometrics PLM and multiple MLM (Manufacturing Lifecycle Management) systems Asset Management includes: IBM Maximo and more Documentation sources include customer CMS systems, DITA and other document creation standards and filesystems of content ERP, HR etc include SAP and Oracle business systems Downstream connections include: Dassault 3Ds, PLMs PowerBuilder, ____ and ____ [NEED Field INPUT]
- So what’s going on here? Well to get to the heart of this, I want to ask you ONE question. Get ready because I’m going to ask you to raise your hand and take this very seriously
- Talk Track: Who is the reference? AIRBUS is an international pioneer in the aerospace industry with roughly 180 locations and 12,000 direct suppliers globally. The company is a leader in designing, manufacturing, and delivering civil and military aerospace products, services, and solutions to customers worldwide. In addition to its primary civil aircraft business, the company has two divisions for other products and services: Defense and Space and Helicopters, the latter being the largest in its industry in terms of revenues and turbine helicopter deliveries. AIRBUS has an annual revenue of €67 billion and 134,000 employees across Asia, Europe and the Americas. What is the problem? The AIRBUS Flight test department spends €650 million ($800 million) every year and was looking to reduce costs while ensuring aircraft safety. Each plane certification takes 2,500 hours of flight tests. During test flights, 600,000 parameters are managed, with sensors capturing data (there are some sensors that collect data 32 times in a second). Each hour of operations cost €10,000. The AIRBUS Flight test program uses different data silos: plane configuration criteria, flight data criteria, flight event behaviors, crew reports, and other unstructured content criteria. Why did anyone care? What was impact of not doing anything? AIRBUS needed a search application that would enable them to find a historical test that matched the exact parameters they were looking for. Being able to find a match was extremely hard given the data begin spread across so many silos. But, with MarkLogic, they could find matches with a high level of confidence, which meant they could avoid running new tests. The result isn’t just $80 million in cost savings though. It also results in increased agility to deliver planes more quickly. What was the solution? A quick search app to search through existing flight data to see if a certain flight test has already been completed to reduce duplicating test. What were the competitive differentiators? Why did they pick ML? High cost of repeating tests Ability to handle structured and unstructured flight data Unified platform with advanced search capabilities Agility to respond to new requirements Features leveraged: Geospatial alerting, semantics, bitemporal What were the benefits? Fast – Results in seconds not minutes Advanced – Complex search over massive data sets Agile – Address new requirements in hours not days Future-proof – Adaptability for new source data Success – Will save millions and deliver planes more quickly What’s Next? This first project was to cover the flight test needed for one new Aircraft model. Next steps will be to expand to all the Airbus aircraft models.
- Talk Track: What They Did Ranked #3 on the Fortune 500, Chevron is a US $200 billion revenue company with global operations in exploration, production, transportation, refining and distribution of oil, natural gas and chemical products. Chevron came to MarkLogic because they were struggling to provide over 1,100 field engineers with a quick and easy way to view comprehensive information on assets across refineries. With Chevron, we started working the Downstream and Chemicals Business Unit, responsible for global refining and R&D. Before MarkLogic, they were having trouble integrating data for their many refineries, which was spread across multiple operational systems. If management wanted to understand more about an asset at a refinery, they would have to go into multiple operational systems and also try to glean anything they could from local drives where a lot of the unstructured information ended up. This led to management to make decisions based on partial data, and 1,100 employees spending between 1-2 hours per week trying to find the information they need to do their jobs. With MarkLogic, Chevron was able to quickly integrate their operational data to create an “Asset 360” repository so that they can get a unified view of their refineries. Chevron is able to, for the first time, access structured and unstructured data about their refining assets across the enterprise and different refineries. MarkLogic also provides analytics around assets, in terms of work orders tied to specific parts and vendors, loss investigations, Health/Environment/Safety data, history briefs, and much more. In the future, Chevron expects to also pull in financial data from SAP and Ariba and also incorporate geospatial data. Why MarkLogic MarkLogic’s multi-model database made it possible for the organization to store heterogeneous structured and unstructured data in one platform. Data was indexed as it was ingested, making asset information readily available. MarkLogic’s indexes, in addition to its built-in search engine, allowed field engineers to quickly track safety and compliance, analyze cross-refinery performance, and examine work orders tied to specific vendors, all at sub-second speeds. The application also allowed cross-refinery asset data visibility, permitting new analytical capabilities for executives. MarkLogic’s flexible schema approach will allow the company to quickly accommodate new data sources, models, formats, and queries over time. Results This was a very big, very expensive project and Chevron was given a bid from a relational vendor for over $6 million dollars, with a timeline that stretched over 8 months for implementation. MarkLogic was able to get the initial Phase 1 app built in only 8 weeks rather than 8 months, and at 10% of the price. Chevron field engineers are now using MarkLogic to find information that was never searchable before – and Chevron IT can provide analytics related to work orders, vendor part reliability, HES (health, environment, and safety) information, and more. Chevron expects to recover its investment in three months, to capture $2.5-5M in annual cost savings, and to improve productivity by as much as 5%. Another quote: “We see MarkLogic working in between our system of records and big data platform, providing a high degree of transactional integration between those systems and the real-time analysis and optimization that we need.”
- Who is the reference? Eaton is a large manufacturing company with $20 billion in annual revenue which has grown via acquisition and have accumulated some 210 ERP systems. Eaton has approximately 95,000 employees and sells products to customers in more than 175 countries. What is the problem? They had 210 unique ERP systems, from 12 different vendors—SAP, Oracle, NetSuite—they had at least some instances of almost every major ERP vendor. Many of the ERP systems were running different versions of the same software. They wanted to get a unified view of their business for multiple reasons, but the overarching reason was that they wanted to reduce risk and improve profitability through better analytics and reporting. For example, in their initial project to integrate the first four ERP systems, they were seeking to understand everything they could about a particular area of interest within the business, such as hydraulic mechanical systems. Why did anyone care? What was impact of not doing anything? In order to make informed decisions they need to be able to get one consolidated view of all of the data in their 210 ERP systems. They had been attempting to build this one consolidated view with Oracle Exadata but in 2.5 years they couldn’t even consolidate four ERP systems. At this rate it would take them 100+ man years to deploy! This was a significant problem because as Eaton grows they will continuously have to complete huge integration projects. Eaton wanted to start with a conceptual ERP (CERP) for invoice and orders (1 of 10 subject areas). In addition, due to the inability to integrate all the data sources quickly, Eaton was faced with low user adaption. What was the solution? An Operational Data Hub to create a 360 view of data From 210 ERP Systems. What were the competitive differentiators? Why did they pick ML? Oracle too expensive and time consuming Flexibility to add sources as needed Centralize real-time view of data What were the benefits? Timely – 5x faster time-to-value, 6 months vs 2.5+ years Future-proof – New data sources easily added Cost-effective – Simpler less error-prone architecture Success – Single source of truth to make informed decisions “As you figure out your requirements, you can add and adjust your data…you don’t break anything” - Allen Muller, Architect, Eaton What’s Next? Eaton's experience with MarkLogic has been incredibly positive. They have completed the CERP pilots for Invoices and Orders and Finance and Tax. They are in the processes of go live as of February 2018
- Our customers are just like you – industrial organizations that are levering data to improve their products, navigate complexity and prepare for the future. We have a big concentration in the ‘heavy industry’ bucket, some real leaders in energy and oil and a great group of industrial companies better leveraging data. We also have a growing group of solutions customers leading delivering value to manufacturing by better managing data and content.
- We’ve made it easy for your to get started with some great resources that communicate what our customers are up to and how you can get involved