mongodb evenings minneapolis: medtronic's mongodb journey

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PRESENTED BY:MATT CHIMENTO: ENGINEERING MANAGERJEFF LEMMERMAN: PRINCIPAL SOFTWARE ENGINEER

MEDTRONIC’S JOURNEY WITH MONGODB

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INTRODUCTION

Jeff Lemmerman B.S. Physics, B.S. Astrophysics

University of Minnesota MS Software Engineering

University of Minnesota Pr. Software Engineer – Medtronic (2006-

Present)

Matt Chimento B.S. Computer Engineering

Kettering University Master of Business Administration (2014)

University of Minnesota Carlson School of Management

Engineering Manager – Medtronic (2006-2014), Target (2014-2015), Medtronic (2015-Present)

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MEDTRONIC ENERGY AND COMPONENT CENTER

MECC est. 1976 Research, Development, and Manufacturing Manufacture components for devices Census – 1200 Employees Plant Size – 190,000 Square Feet

40,000 Manufacturing 15,000 R&D Labs 38,000 Office 97,000 Common, Support, Warehouse

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MEDTRONIC USE CASES

Results API: RESTful API for storing results from automated test equipment

Component Database: Complete 360˚ View of the components we manufacture at MECC

Tests: Storing test information for automated test equipment

Other Medtronic groups are using MongoDB differently

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RESULTS API: PROBLEMVARIETY OF COMPONENTS

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RESULTS API: PROBLEMVARIETY OF DATA INTENSIVE TESTS

Multivariate Analysis

Statistical Process Control

Waveform Measurements

Operational Dashboards

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HOW THE JOURNEY BEGANLEARNING NEW CONCEPTS AND TOOLS: WHAT CAN I BUILD?

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TEST MEASUREMENTS – WAVEFORMRESULTS API

RESTful API

Model Comparison

TESTS: PROBLEM

0.6M unique battery tests

Since 1976

Export as Analysis-Ready Data-Sets

Many thousand test channels for primary and rechargeable batteries

Some tests extending >15 years Each system has very different Test

Information Commercial and Custom Systems

MECC Test Systems Data Management

Rechargeable Battery Test Systems and

Ovens

Batteries on Test Boards in Oven

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TESTS: PROBLEM

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Custom TagsSearching By Tags

Custom PropertiesSearching By Properties

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TEST INFORMATION – RELATIONAL DATABASE

Test Table System Specific Table(s)

Test Table Properties Table

Test Table

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TEST INFORMATION – RELATIONAL DATABASE

Test Table

Key Trade Offs For Flexibility –Joining System Specific TablesQuerying and Processing Key/Value TableQuerying and Processing Structured Text Fields (JSON/XML)

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TEST INFORMATION – MONGODB

RESULTS: VISUALIZE

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Visualize ResultsExport -> CSV

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COMPONENT DATABASE - UPDATE

Full Material Consumption Full Manufacture Step History Summarized Data Scrap Codes

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WHAT HAVE WE LEARNED IN 4 YEARS

MongoDB Training, Support, Documentation have remained excellentStill struggling with standardization vs. flexibilityResponsibility for querying and processing data in MongoDB –

Application vs. MongoDB vs. 3rd Party Tools

Can be difficult to keep up with fast release cycle, new features -C# Driver 2.x – methods, query builders/filters, Async methods

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WRITING CUSTOM SERIALIZATION IS TRICKY

Automapping functionality works in most cases

Can add control over how class properties are serialized

Add serialization information or override Serialize/Deserialize Methods

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NEW FRONTIERS

Data Discovery/VisualizationData Mining

Machine Learning/Pattern Recognition Data Lakes

THANK YOU.QUESTIONS?

HOW IS DATA RETRIEVED?

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LOADING DATA INTO CENTRAL REPOSITORY

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Component Dataset In Excel

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Component Dataset in RDBMS