DOCSLIB.ORG

Kalyan Pamarthy & Dharmesh Patel, Google Cloud Healthcare

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Google Cloud FHIR APIs: Data Ingestion, Management, and Analytics Kalyan Pamarthy & Dharmesh Patel, Google Cloud Healthcare HL7 FHIR DevDays 2020, Virtual Edition, November 17–20, 2020 | @FirelyTeam | #fhirdevdays | www.devdays.com/november-2020 HL7®, FHIR® and the flame Design mark are the registered trademarks of Health Level Seven International and are used with permission. About us Kalyan Pamarthy Dharmesh Patel Product Manager Solutions Manager Google Cloud Healthcare API Google Cloud Healthcare API 2 ● Learn about the Google Cloud Healthcare API & Managed FHIR capabilities ● Preview recently launched features - OSS and Managed APIs ● See Managed FHIR capabilities in action! Cloud Healthcare API ● Let’s Build! Google Cloud FHIR APIs ● Leveraging Synthetic Data to Benchmark Thursday, Nov 19th, 5:15 pm-6:00 pm CET a Cloud-Based FHIR API Onix Friday, Nov 20th, 2:00 pm-2:45 pm ET ● Building FHIR Analytics and AI Applications Thursday, Nov 19th, 5:15 pm-5:35 pm CET ● FHIR Analytics using OHDSI Tools on Cloud Thursday, Nov 19th, 5:40 pm-6:00 pm CET 1. Google Cloud Healthcare - FHIR APIs 5 Accelerate your healthcare solution development ● Primary API surface for healthcare specific data management in the Google Cloud Platform. ● Fully managed, Standards based serverless, REST APIs ○ FHIR (DSTU2, STU3 and R4) ○ HL7v2 ○ DICOM ● Value add capabilities (e.g De-Identification, Data Transformation, NLP) ● Stores PHI data in compliance with regulations (e.g HIPAA) Healthcare API ● Integrated with other Google Cloud applications (e.g BigQuery) ● Integrated with Google Cloud components (e.g Cloud PubSub, Cloud Functions) ● Support for Smart on FHIR Apps with Apigee API Management cloud.google.com/healthcare Generally Available + new features in Preview Supported FHIR ● DSTU2, STU3 & R4 Support Versions ● Import and Export FHIR resources in ndJSON from/to Google Cloud Import & Export Storage ● Export to BigQuery - Streaming and Batch Standard FHIR ● Resource Create/Read/Update/Patch/History/Delete Operations CRUD ● FHIR Search Cloud Healthcare Advanced FHIR ● Patient $Everything Operations FHIR APIs ● Execute Bundle (Batch & Transaction) Notifications ● Pub/Sub notifications on changes to FHIR server De-identification ● Standard and custom configurations to de-identify FHIR resources New IG Support & ● Configure and validate structured definitions Profiles ● Configure and validate IGs such as US Core, CARIN and DaVinci profiles New Bulk Data ● $ export (System Level) with _type and _since Cloud Healthcare Conditional ● Conditionally update and delete FHIR resources that match a search Update/Delete query FHIR APIs Observation ● Retrieves the N most recent Observation resources for a subject Last$n matching search criteria specified as query parameters ● Translates a code from one value set to another using a concept map, Terminology or user provided concept maps to translate any code system to another $translate code 2. Google Cloud Healthcare - Data Transformation 10 New CCD to FHIR ● Transform CCD XML documents to FHIR https://github.com/GoogleCloudPlatform/healthcare-data-harmonization/tree/master/mapping_configs/cda_fhir_r4 New DICOM to FHIR ● Transform DICOM studies to FHIR https://github.com/GoogleCloudPlatform/healthcare-data-harmonization/tree/master/mapping_configs/dicom_fhir_r4 HL7v2 to FHIR ● Transform HL7v2 messages to FHIR Cloud Healthcare https://github.com/GoogleCloudPlatform/healthcare-data-harmonization/tree/master/mapping_configs/hl7v2_fhir_r4 FHIR APIs https://github.com/GoogleCloudPlatform/healthcare-data-harmonization { { "segmentId": "XAD", "use": "Work", "fields": { Transformation "text": "55 Fruit Street Massachusetts General "1": "55 Fruit Street", Hospital Boston MA 02114 USA", "2": "Massachusetts General Hospital", library "line": [ "3": "Boston", "55 Fruit Street" "4": "MA", ], "5": "02114", "city": "Boston", "6": "USA", "district": 100, "7": "Work", "state": "MA", "8": "Other geographic designation", "zipCode": "02114", use: XAD.7 "9": "100" "country": "USA", text: " ", XAD.1, XAD.2, XAD.3, XAD.4, } "type": "physical" XAD.5, XAD.6 => _StrJoin } } line: XAD.1 => _ListOf city: XAD.3 district: XAD.9 state: XAD.4 Sample maps: zipCode: XAD.5 - HL7v2 to FHIR for ADT_A01 country: XAD.6 Supports repeated and nested structures, and ORU_R01 initially type: "physical" terminology mapping, unit harmonization, - FHIR to OMOP clinical entity extraction, user-defined - OMOP to FHIR Whistle mapping config functions - CCD to FHIR Healthcare API Cloud Data Fusion OSS Dataflow FHIR Import API Fully managed, cloud-native data integration Reference Cloud Dataflow (Apache service for building and managing ETL and ELT Beam) pipeline to converting streaming data pipelines. HL7v2 messages to FHIR resources With a graphical interface and a broad open Whistle Cloud Cloud source library of preconfigured connectors Storage config Healthcare and transformations, Cloud Data Fusion shie s https://github.com/GoogleCloudPlatform/healthcare-data-harmonization an organization’s focus away from code and FHIR Export API integration to insights and action. Cloud Whistle BigQuery Healthcare config HL7v2 → FHIR API Cloud Whistle Cloud Healthcare config Healthcare 3. Google Cloud Healthcare - FHIR De-identification 14 Proprietary + Confidential Proprietary + Confidential Raw FHIR Redacted Evaluation Analytics data DelD FHIR data and validation Secure sharing AI/ML training and prediction Proprietary + Confidential Proprietary + Confidential Original (FHIR) record De-identified FHIR record Proprietary + Confidential Leverage the Google Cloud Healthcare Project deployed (from start to API serverless capabilities to receive finish) in 3 weeks ADT, ORU, ORM & MDM messages, transform to FHIR and project into COVID monitoring dashboards BigQuery for analytics at scale (circa available for C-Suite 2M messages per day):- Drill down : Health System > HL7 > FHIR > BigQuery > Looker Hospital > Unit > Patient All components running in Google Cloud, with multiple (5) feeds from HL7 Data latency circa 2-3 minutes interface engines. Processing 1000 messages per minute through the data pipeline. Proprietary + Confidential 1 2 replace sensitive data with a fixed character, ex. “John” > “****” 3 replace input with a category label, ex. “John” > “[NAME]” 4 shie by a random number of days, with the option to maintain chronological order between dates belonging to the same patient or population 5 replace input with a hashed value generated using a (customer-defined) encryption key Demo time! Ingest, Manage and Analyze Healthcare Data using FHIR A. B. D. E. Configure Ingest C. Export Analyze FHIR Server HL7v2 De-identify Data to Data using in Google Data in FHIR Store GCS & BigQuery Cloud FHIR Store BigQuery & Looker 22 Configure FHIR API in Google Cloud A. B. D. E. Configure Ingest C. Export Analyze FHIR Server HL7v2 De-identify Data to Data using in Google Data in FHIR Store GCS & BigQuery Cloud FHIR Store BigQuery & Looker 1 2 3 4 5 Create FHIR Import Enable Ingest FHIR Browse Store Impl. Guide Impl. Guide Data FHIR Data curl -X GET \ -H "Authorization: Bearer $(gcloud auth print-access-token)" \ "https://healthcare.googleapis.com/v1alpha2/projects/ha-portal/locations/us-central1/datas ets/default-dataset/fhirStores/default-fhir-store" 23 Ingest HL7v2 data in FHIR Store A. B. D. E. Configure Ingest C. Export Analyze FHIR Server HL7v2 De-identify Data to Data using in Google Data in FHIR Store GCS & BigQuery Cloud FHIR Store BigQuery & Looker HL7v2 HL7v2 HL7v2 FHIR MLLP Cloud FHIR Simulated EHR 1 HL7v2 Store 2 Adapter Dataflow Store Cloud Pub/Sub 1. https://github.com/GoogleCloudPlatform/mllp 2. https://github.com/GoogleCloudPlatform/healthcare-data-harmonization-dataflow 3. https://github.com/GoogleCloudPlatform/healthcare-data-harmonization/tree/master/mapping_configs/hl7v2_fhir_r4 24 De-identify FHIR Store A. B. D. E. Configure Ingest C. Export Analyze FHIR API in HL7v2 De-identify Data to Data using Google Data in FHIR Store GCS & BigQuery Cloud FHIR Store BigQuery & Looker De-identify FHIR Store FHIR Store (FHIR Data with PII/PHI) (De-identified FHIR Data) 25 Export Data to Cloud Storage & BigQuery A. B. D. E. Configure Ingest C. Export Analyze FHIR API in HL7v2 De-identify Data to Data using Google Data in FHIR Store GCS & BigQuery Cloud FHIR Store BigQuery & Looker :export FHIR Store BigQuery $export Cloud Storage 26 Analyze Data using Looker A. B. E. D. Configure Ingest C. Analyze Stream FHIR API in HL7v2 De-identify Data using Data to Google Data in FHIR Store BigQuery BigQuery Cloud FHIR Store & Looker BigQuery Looker 27 Let’s Build: Google Cloud FHIR APIs Let’s Build! on Thursday Thursday, Nov 19th, 5:15pm - 6pm CET 1. Submit a request for the Google Cloud Sandbox environment (QwikLab) at bit.ly/google-cloud-fhir 2. You will receive instructions to access the Google Cloud Sandbox Environment (QwikLab) 3. During the Let’s Build, we will walk through setting up a Cloud FHIR server and using FHIR APIs with synthetic data 4. Follow along and ask questions! 28 Email us or find us on Zulip to chat about FHIR@Google Kalyan Pamarthy Dharmesh Patel Product Manager Solutions Manager Google Cloud Healthcare API Google Cloud Healthcare API [email protected] [email protected] 29 .
Recommended publications
  • HW&Co. Landscape Industry Reader Template

    HW&Co. Landscape Industry Reader Template

    TECHNOLOGY, MEDIA, & TELECOM QUARTERLY SOFTWARE SECTOR REVIEW │ 3Q 2016 www.harriswilliams.com Investment banking services are provided by Harris Williams LLC, a registered broker-dealer and member of FINRA and SIPC, and Harris Williams & Co. Ltd, which is authorised and regulated by the Financial Conduct Authority. Harris Williams & Co. is a trade name under which Harris Williams LLC and Harris Williams & Co. Ltd conduct business. TECHNOLOGY, MEDIA, & TELECOM QUARTERLY SOFTWARE SECTOR REVIEW │ 3Q 2016 HARRIS WILLIAMS & CO. OVERVIEW HARRIS WILLIAMS & CO. (HW&CO.) GLOBAL ADVISORY PLATFORM CONTENTS . DEAL SPOTLIGHT . M&A TRANSACTIONS – 2Q 2016 KEY FACTS . SOFTWARE M&A ACTIVITY . 25 year history with over 120 . SOFTWARE SECTOR OVERVIEWS closed transactions in the . SOFTWARE PRIVATE PLACEMENTS last 24 months OVERVIEW . SOFTWARE PUBLIC COMPARABLES . Approximately 250 OVERVIEW professionals across seven . TECHNOLOGY IPO OVERVIEW offices in the U.S. and . DEBT MARKET OVERVIEW Europe . APPENDIX: PUBLIC COMPARABLES DETAIL . Strategic relationships in India and China HW&Co. Office TMT CONTACTS Network Office UNITED STATES . 10 industry groups Jeff Bistrong Managing Director HW&CO. TECHNOLOGY, MEDIA & TELECOM (TMT) GROUP FOCUS AREAS [email protected] Sam Hendler SOFTWARE / SAAS INTERNET & DIGITAL MEDIA Managing Director [email protected] . Enterprise Software . IT and Tech-enabled . AdTech and Marketing . Digital Media and Content Services Solutions Mike Wilkins . Data and Analytics . eCommerce Managing Director . Infrastructure and . Data Center and . Consumer Internet . Mobile [email protected] Managed Services Security Software EUROPE Thierry Monjauze TMT VERTICAL FOCUS AREAS Managing Director [email protected] . Education . Fintech . Manufacturing . Public Sector and Non-Profit . Energy, Power, and . Healthcare IT . Professional Services . Supply Chain, Transportation, TO SUBSCRIBE PLEASE EMAIL: Infrastructure and Logistics *[email protected] SELECT RECENT HW&CO.
  • Starburst Enterprise on Google Cloud

    Starburst Enterprise on Google Cloud

    SOLUTION BRIEF Starburst Enterprise on Google Cloud The Starburst Enterprise Difference As organizations scale up, Starburst Enterprise on Google Cloud drives Available on the Google Cloud Marketplace, the better business outcomes, consistency, and reliability, delighting your data Starburst Enterprise platform is a fully supported, engineers and scientists. Teams look to Starburst Enterprise on Google Cloud production-tested, enterprise-grade distribution for expertise & constant fine-tuning that results in overall lower costs & faster of the open source Trino MPP SQL query engine. time-to-insights: Starburst integrates Google’s scalable cloud storage and computing services with a more Performance: stable, secure, efficient, and cost-effective way Includes the latest optimizations; Starburst Cached Views available for to query all your enterprise data, wherever it frequently accessed data; stable code that minimizes failed queries. resides. Leading organizations across multiple industries Connectivity rely on Starburst Enterprise and Google. 40+ supported enterprise connectors; high performance connectors for Oracle, Teradata, Snowflake, IBM DB2, Delta Lake, and many more. Analytics Anywhere Designed for the separation of storage and Security compute, Trino is ideal for querying data residing in multiple systems, from cloud data lakes to Role-based access control (via Apache Ranger); Kerberos, OKTA, LDAP legacy data warehouses. Deployed via Google integration; data encryption & masking; query auditing to see who is doing what. Kubernetes Engine (GKE), Starburst Enterprise on Google Cloud enables the user to run analytic Management queries across Google Cloud data sources and on-prem systems such as Teradata, Oracle, Enhanced tools for configuration, auto scaling, and Starburst Insights and others via Trino clusters. Within a single monitoring dashboards; easy deployment on Google platforms.
  • The Effectiveness of Application Permissions

    The Effectiveness of Application Permissions

    The Effectiveness of Application Permissions Adrienne Porter Felt,∗ Kate Greenwood, David Wagner University of California, Berkeley apf, kate eli, [email protected] Abstract cations’ permission requirements up-front so that users can grant them during installation. Traditional user-based permission systems assign the Traditional user-based permission systems assign the user’s full privileges to all applications. Modern plat- user’s full privileges to all of the user’s applications. In forms are transitioning to a new model, in which each the application permission model, however, each appli- application has a different set of permissions based on cation can have a customized set of permissions based its requirements. Application permissions offer several on its individual privilege requirements. If most applica- advantages over traditional user-based permissions, but tions can be satisfied with less than the user’s full priv- these benefits rely on the assumption that applications ileges, then three advantages of application permissions generally require less than full privileges. We explore over the traditional user-based model are possible: whether that assumption is realistic, which provides in- sight into the value of application permissions. • User Consent: Security-conscious users may be We perform case studies on two platforms with appli- hesitant to grant access to dangerous permissions cation permissions, the Google Chrome extension sys- without justification. For install-time systems, this tem and the Android OS. We collect the permission re- might alert some users to malware at installation; quirements of a large set of Google Chrome extensions for time-of-use systems, this can prevent an in- and Android applications.
  • Appendix 1 - 5 Appendix 1 - Questionnaire for Colleges

    Appendix 1 - 5 Appendix 1 - Questionnaire for Colleges

    Appendix 1 - 5 Appendix 1 - Questionnaire for Colleges Declaration: I, Rajeev Ghode, persuing my Ph.D. in Department of Communication Studies, Pune University. Title of Ph.D. Research is "To study potential and challenges in the use and adoption of ICT in Higher Education"For this research purpose, I want to collect quantitative data from all the professors of colleges which are affiliated to Pune University. I ensure that all the data collected will be used only for the Ph.D. research and secrecy of the data will be maintained. I appreciate you for spending your valuable time to fill this questionnaire. Thanking You <•;. Prof. Rajeev Ghode Questionnaire Name of the College Address/City 1 Arts Science and Commerce College 1 Arts Science and Commerce College with Computer Science Type of College 1 Commerce and BBA Q B.Ed. College 1 1 Law Institutional ICT Infrastructure Sr. ICT Infrastructure Yes No Provision in near No. future 1. Multimedia /Conference Hall 2. Computer Lab 3. Internet Connectivity in Campus 4. Digital Library 5. Website 6. Organization e-mail Server 7. Blog Appendix - I Sr. ICT Infrastructure Yes No Provision in near No. future 8. Presence on SNS 9. Online Admission System 10. Online/Offline Examination Application 11. Biometric Attendance 12. Student Management System 13. Professional membership for online journals Department-wise ICT Infrastructure Sr. ICT Infrastructure Yes No Provision in near No. future 1. Do you have separate Desktops for faculties in every department? 2. Do you have separate Laptops for every department? 3. Does every department have LCD Projector? 4.
  • The Book of Apigee Edge Antipatterns V2.0

    The Book of Apigee Edge Antipatterns V2.0

    The Book of Apigee Edge Antipatterns Avoid common pitfalls, maximize the power of your APIs Version 2.0 Google Cloud ​Privileged and confidential. ​apigee 1 Contents Introduction to Antipatterns 3 What is this book about? 4 Why did we write it? 5 Antipattern Context 5 Target Audience 5 Authors 6 Acknowledgements 6 Edge Antipatterns 1. Policy Antipatterns 8 1.1. Use waitForComplete() in JavaScript code 8 1.2. Set Long Expiration time for OAuth Access and Refresh Token 13 1.3. Use Greedy Quantifiers in RegularExpressionProtection policy​ 16 1.4. Cache Error Responses 19 1.5. Store data greater than 512kb size in Cache ​24 1.6. Log data to third party servers using JavaScript policy 27 1.7. Invoke the MessageLogging policy multiple times in an API proxy​ 29 1.8. Configure a Non Distributed Quota 36 1.9. Re-use a Quota policy 38 1.10. Use the RaiseFault policy under inappropriate conditions​ 44 1.11. Access multi-value HTTP Headers incorrectly in an API proxy​ 49 1.12. Use Service Callout policy to invoke a backend service in a No Target API proxy 54 Google Cloud ​Privileged and confidential. ​apigee 2 2. Performance Antipatterns 58 2.1. Leave unused NodeJS API Proxies deployed 58 3. Generic Antipatterns 60 3.1. Invoke Management API calls from an API proxy 60 3.2. Invoke a Proxy within Proxy using custom code or as a Target 65 3.3. Manage Edge Resources without using Source Control Management 69 3.4. Define multiple virtual hosts with same host alias and port number​ 73 3.5.
  • Apigee X Migration Offering

    Apigee X Migration Offering

    Apigee X Migration Offering Overview Today, enterprises on their digital transformation journeys are striving for “Digital Excellence” to meet new digital demands. To achieve this, they are looking to accelerate their journeys to the cloud and revamp their API strategies. Businesses are looking to build APIs that can operate anywhere to provide new and seamless cus- tomer experiences quickly and securely. In February 2021, Google announced the launch of the new version of the cloud API management platform Apigee called Apigee X. It will provide enterprises with a high performing, reliable, and global digital transformation platform that drives success with digital excellence. Apigee X inte- grates deeply with Google Cloud Platform offerings to provide improved performance, scalability, controls and AI powered automation & security that clients need to provide un-parallel customer experiences. Partnerships Fresh Gravity is an official partner of Google Cloud and has deep experience in implementing GCP products like Apigee/Hybrid, Anthos, GKE, Cloud Run, Cloud CDN, Appsheet, BigQuery, Cloud Armor and others. Apigee X Value Proposition Apigee X provides several benefits to clients for them to consider migrating from their existing Apigee Edge platform, whether on-premise or on the cloud, to better manage their APIs. Enhanced customer experience through global reach, better performance, scalability and predictability • Global reach for multi-region setup, distributed caching, scaling, and peak traffic support • Managed autoscaling for runtime instance ingress as well as environments independently based on API traffic • AI-powered automation and ML capabilities help to autonomously identify anomalies, predict traffic for peak seasons, and ensure APIs adhere to compliance requirements.
  • Manpreet Singh

    Manpreet Singh

    MANPREET SINGH SUMMARY OF EXPERTISE ​ ​ ● 1 Year of Co-op experience at SAP as SLT/HANA Product support Engineer. ● 2+ years of full time experience in US IT firm named Cognizant as Java and ESB Developer. ● Broad understanding of Machine Learning, AI and hands on with latest developments in IoT. ● Experience in Penetration Testing, Intrusion Detection, Digital forensics and Risk Management. ● Sound Knowledge and Experience in Google API Management Platform named Apigee. ● Well acquainted with knowledge related to IT Infrastructure and SOA architecture. ● Good organizational, analytical, problem-solving skills and a great team player. ACADEMIC & PROFESSIONAL DEVELOPMENT Master of Engineering (Sep 2017 - Apr 2019) University of Victoria, Canada ​ Electrical and Computer Engineering Bachelor of Technology (Aug 2011 - May 2015) LPU, Punjab, India Electronics and Communication Engineering TECHNICAL SKILLS Enterprise Tools SAP SLT, Apigee Edge, SAG webMethods, Soap UI, Splunk, SNow Penetration Testing Tools Nessus, Zenmap, Wireshark, Hydra, Burp-suite, Metasploit Programming C++, Java, Python Database MySQL Web Development Wordpress, HTML5, CSS3 Network TCP/IP, OSI Model, WLAN/LAN technologies Operating System Windows, Linux (Kali), Mac OS, iOS, Android Interpersonal Leadership, Teamwork, Time Management, Communication WORK EXPERIENCE Software Dev QA Engineer 1 (August 2019- Present) Fortinet Technologies, Burnaby, BC Canada. ● Work as Software developer for various security interfaces. ● Work as QA engineer for testing the code in production and development. Product Support Engineer (Sept 2018 – August 2019) SAP, Vancouver, Canada SAP Landscape Transformation Replication Server (SLT) Engineer ● Worked as a SLT product support engineer; handling Configurations, Troubleshooting and Incident Handling for top SAP clients. ● Handled (VH) priority issues for real business problems using live troubleshooting sessions for Max Attention Customers like Apple, Porsche, Coca-Cola.
  • Data Warehouse Offload to Google Bigquery

    Data Warehouse Offload to Google Bigquery

    DATA WAREHOUSE OFFLOAD TO GOOGLE BIGQUERY In a world where big data presents both a major opportunity and a considerable challenge, a rigid, highly governed traditional enterprise data warehouse isn’t KEY BENEFITS OF MOVING always the best choice for processing large workloads, or for applications like TO GOOGLE BIGQUERY analytics. Google BigQuery is a lightning-fast cloud-based analytics database that lets you keep up with the growing data volumes you need to derive meaningful • Reduces costs and business value, while controlling costs and optimizing performance. shifts your investment from CAPEX to OPEX Pythian’s Data Warehouse Offload to Google BigQuery service moves your workload from an existing legacy data warehouse to a Google BigQuery data • Scales easily and on demand warehouse using our proven methodology and Google experts–starting with a fixed-cost Proof of Concept stage that will quickly demonstrate success. • Enables self-service analytics and advanced analytics GETTING STARTED The Pythian Data Warehouse Offload to Google BigQuery service follows a proven methodology and delivers a Proof of Concept (POC) that demonstrates viability and value within three to four weeks. The POC phase will follow this workflow: 1. Assess existing data warehouse environment to identify tables and up to two reports that will be offloaded in this phase 2. Provision GCP infrastructure including Cloud storage, Bastion hosts, BigQuery, and Networking 3. Implement full repeatable extract/load process for selected tables 4. Implement selected reports on BigQuery 5. Produce report PYTHIAN DELIVERS By the end of the first stage of our engagement, you can expect to have: • Working prototype on BigQuery • Up to two reports • Demonstrated analysis capabilities using one fact with five associated dimensions www.pythian.com • Report that includes: an assessment of your current setup and support you need to plan and maintain your full (including a cost analysis for BigQuery), performance/ Google BigQuery data warehouse and enterprise analytics usability analysis of POC vs.
  • Google Cloud Whitepaper

    Google Cloud Whitepaper

    1 Table of contents Introduction 3 The compliance landscape for UK health and social care data 4 Legislation governing UK health data 4 Overview of NHS Digital in England 6 Overview of the Use of Public Cloud Guidance 6 Overview of the DSP Toolkit 7 Google Cloud Platform information governance overview 8 Google Cloud Platform’s approach to security and data protection 8 The Shared Responsibility Model 12 How Google Cloud Platform meets NHS Information Governance requirements 13 Data Security Standard 1 13 Data Security Standard 2 20 Data Security Standard 3 22 Data Security Standard 4 22 Data Security Standard 5 25 Data Security Standard 6 26 Data Security Standard 7 29 Data Security Standard 8 31 Data Security Standard 9 32 Data Security Standard 10 33 How Google Cloud Platform helps customers meet their DSP Toolkit requirements 34 Google Cloud Platform products to help with compliance 34 Google Cloud Platform Terms of Service and Conditions 37 Additional Resources to help Google Cloud Platform customers 37 Conclusion 38 2 Disclaimer This document was last updated in O ctober 2020 a nd is for informational purposes only. Google does not intend the information or recommendations in this document to constitute legal advice. Each customer must independently evaluate its own particular use of the services as appropriate to support its legal compliance obligations. Since Google is continually improving security and other features for our customers, some of the policies, procedures, and technologies mentioned in this document may have changed. Please visit cloud.google.com/security/compliance or contact your Google Cloud Account Representative to check for updated information.
  • EN-Google Hacks.Pdf

    EN-Google Hacks.Pdf

    Table of Contents Credits Foreword Preface Chapter 1. Searching Google 1. Setting Preferences 2. Language Tools 3. Anatomy of a Search Result 4. Specialized Vocabularies: Slang and Terminology 5. Getting Around the 10 Word Limit 6. Word Order Matters 7. Repetition Matters 8. Mixing Syntaxes 9. Hacking Google URLs 10. Hacking Google Search Forms 11. Date-Range Searching 12. Understanding and Using Julian Dates 13. Using Full-Word Wildcards 14. inurl: Versus site: 15. Checking Spelling 16. Consulting the Dictionary 17. Consulting the Phonebook 18. Tracking Stocks 19. Google Interface for Translators 20. Searching Article Archives 21. Finding Directories of Information 22. Finding Technical Definitions 23. Finding Weblog Commentary 24. The Google Toolbar 25. The Mozilla Google Toolbar 26. The Quick Search Toolbar 27. GAPIS 28. Googling with Bookmarklets Chapter 2. Google Special Services and Collections 29. Google Directory 30. Google Groups 31. Google Images 32. Google News 33. Google Catalogs 34. Froogle 35. Google Labs Chapter 3. Third-Party Google Services 36. XooMLe: The Google API in Plain Old XML 37. Google by Email 38. Simplifying Google Groups URLs 39. What Does Google Think Of... 40. GooglePeople Chapter 4. Non-API Google Applications 41. Don't Try This at Home 42. Building a Custom Date-Range Search Form 43. Building Google Directory URLs 44. Scraping Google Results 45. Scraping Google AdWords 46. Scraping Google Groups 47. Scraping Google News 48. Scraping Google Catalogs 49. Scraping the Google Phonebook Chapter 5. Introducing the Google Web API 50. Programming the Google Web API with Perl 51. Looping Around the 10-Result Limit 52.
  • Economic and Social Impacts of Google Cloud September 2018 Economic and Social Impacts of Google Cloud |

    Economic and Social Impacts of Google Cloud September 2018 Economic and Social Impacts of Google Cloud |

    Economic and social impacts of Google Cloud September 2018 Economic and social impacts of Google Cloud | Contents Executive Summary 03 Introduction 10 Productivity impacts 15 Social and other impacts 29 Barriers to Cloud adoption and use 38 Policy actions to support Cloud adoption 42 Appendix 1. Country Sections 48 Appendix 2. Methodology 105 This final report (the “Final Report”) has been prepared by Deloitte Financial Advisory, S.L.U. (“Deloitte”) for Google in accordance with the contract with them dated 23rd February 2018 (“the Contract”) and on the basis of the scope and limitations set out below. The Final Report has been prepared solely for the purposes of assessment of the economic and social impacts of Google Cloud as set out in the Contract. It should not be used for any other purposes or in any other context, and Deloitte accepts no responsibility for its use in either regard. The Final Report is provided exclusively for Google’s use under the terms of the Contract. No party other than Google is entitled to rely on the Final Report for any purpose whatsoever and Deloitte accepts no responsibility or liability or duty of care to any party other than Google in respect of the Final Report and any of its contents. As set out in the Contract, the scope of our work has been limited by the time, information and explanations made available to us. The information contained in the Final Report has been obtained from Google and third party sources that are clearly referenced in the appropriate sections of the Final Report.
  • Department of Defense Enterprise Devsecops Initiative

    Department of Defense Enterprise Devsecops Initiative

    Headquarters U.S. Air Force I n t e g r i t y - S e r v i c e - E x c e l l e n c e How did the Department of Defense move to Kubernetes and Istio? Mr. Nicolas Chaillan Chief Software Officer, U.S. Air Force Co-Lead, DoD Enterprise DevSecOps Initiative V2.5 – UNCLASSFIED Must Adapt to Challenges Must Rapidly Adapt To Challenges I n t e g r i t y - S e r v i c e - E x c e l l e n c e 2 Must Adapt to Challenges Work as a Team! Must Adapt To Challenges I n t e g r i t y - S e r v i c e - E x c e l l e n c e 3 Must Adapt to Challenges Work as a Team! A Large Team! Must Adapt To Challenges I n t e g r i t y - S e r v i c e - E x c e l l e n c e 4 Must Adapt to Challenges With Various TechnologiesWork as a Team! A Large Team! Must Adapt To Challenges I n t e g r i t y - S e r v i c e - E x c e l l e n c e 5 Must Adapt to Challenges With Various Technologies Work as a Team! A Large Team! Must AdaptBring To Challenges It With Us! I n t e g r i t y - S e r v i c e - E x c e l l e n c e 6 Must Adapt to Challenges With Various Technologies Work as a Team! Even To Space! A Large Team! Must AdaptBring To Challenges It With Us! I n t e g r i t y - S e r v i c e - E x c e l l e n c e 7 Must Adapt to Challenges With Various Technologies Work as a Team! To Space! A Large Team! MustWith Adapt a FewBring To Sensors! Challenges It With Us! I n t e g r i t y - S e r v i c e - E x c e l l e n c e 8 With Their Help! Must Adapt to Challenges With Various Technologies Work as a Team! To Space! A Large Team! MustWith Adapt a FewBring To Sensors! Challenges It With Us! I n t e g r i t y - S e r v i c e - E x c e l l e n c e 9 What is the DoD Enterprise DevSecOps Initiative? Joint Program with OUSD(A&S), DoD CIO, U.S.