Google Cloud Platform Special Interest Group
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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. -
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Annex 2: List of tested and analyzed data sharing tools (non-exhaustive) Below are the specifications of the tools surveyed, as to February 2015, with some updates from April 2016. The tools selected in the context of EU BON are available in the main text of the publication and are described in more details. This list is also available on the EU BON Helpdesk website, where it will be regularly updated as needed. Additional lists are available through the GBIF resources page, the DataONE software tools catalogue, the BioVel BiodiversityCatalogue and the BDTracker A.1 GBIF Integrated Publishing Toolkit (IPT) Main usage, purpose, selected examples The Integrated Publishing Toolkit is a free open source software tool written in Java which is used to publish and share biodiversity data sets and metadata through the GBIF network. Designed for interoperability, it enables the publishing of content in databases or text files using open standards, namely, the Darwin Core and the Ecological Metadata Language. It also provides a 'one-click' service to convert data set metadata into a draft data paper manuscript for submission to a peer-reviewed journal. Currently, the IPT supports three core types of data: checklists, occurrence datasets and sample based data (plus datasets at metadata level only). The IPT is a community-driven tool. Core development happens at the GBIF Secretariat but the coding, documentation, and internationalization are a community effort. New versions incorporate the feedback from the people who actually use the IPT. In this way, users can help get the features they want by becoming involved. The user interface of the IPT has so far been translated into six languages: English, French, Spanish, Traditional Chinese, Brazilian Portuguese, Japanese (Robertson et al, 2014). -
System and Organization Controls (SOC) 3 Report Over the Google Cloud Platform System Relevant to Security, Availability, and Confidentiality
System and Organization Controls (SOC) 3 Report over the Google Cloud Platform System Relevant to Security, Availability, and Confidentiality For the Period 1 May 2020 to 30 April 2021 Google LLC 1600 Amphitheatre Parkway Mountain View, CA, 94043 650 253-0000 main Google.com Management’s Report of Its Assertions on the Effectiveness of Its Controls Over the Google Cloud Platform System Based on the Trust Services Criteria for Security, Availability, and Confidentiality We, as management of Google LLC ("Google" or "the Company") are responsible for: • Identifying the Google Cloud Platform System (System) and describing the boundaries of the System, which are presented in Attachment A • Identifying our service commitments and system requirements • Identifying the risks that would threaten the achievement of its service commitments and system requirements that are the objectives of our System, which are presented in Attachment B • Identifying, designing, implementing, operating, and monitoring effective controls over the Google Cloud Platform System (System) to mitigate risks that threaten the achievement of the service commitments and system requirements • Selecting the trust services categories that are the basis of our assertion We assert that the controls over the System were effective throughout the period 1 May 2020 to 30 April 2021, to provide reasonable assurance that the service commitments and system requirements were achieved based on the criteria relevant to security, availability, and confidentiality set forth in the AICPA’s -
F1 Query: Declarative Querying at Scale
F1 Query: Declarative Querying at Scale Bart Samwel John Cieslewicz Ben Handy Jason Govig Petros Venetis Chanjun Yang Keith Peters Jeff Shute Daniel Tenedorio Himani Apte Felix Weigel David Wilhite Jiacheng Yang Jun Xu Jiexing Li Zhan Yuan Craig Chasseur Qiang Zeng Ian Rae Anurag Biyani Andrew Harn Yang Xia Andrey Gubichev Amr El-Helw Orri Erling Zhepeng Yan Mohan Yang Yiqun Wei Thanh Do Colin Zheng Goetz Graefe Somayeh Sardashti Ahmed M. Aly Divy Agrawal Ashish Gupta Shiv Venkataraman Google LLC [email protected] ABSTRACT 1. INTRODUCTION F1 Query is a stand-alone, federated query processing platform The data processing and analysis use cases in large organiza- that executes SQL queries against data stored in different file- tions like Google exhibit diverse requirements in data sizes, la- based formats as well as different storage systems at Google (e.g., tency, data sources and sinks, freshness, and the need for custom Bigtable, Spanner, Google Spreadsheets, etc.). F1 Query elimi- business logic. As a result, many data processing systems focus on nates the need to maintain the traditional distinction between dif- a particular slice of this requirements space, for instance on either ferent types of data processing workloads by simultaneously sup- transactional-style queries, medium-sized OLAP queries, or huge porting: (i) OLTP-style point queries that affect only a few records; Extract-Transform-Load (ETL) pipelines. Some systems are highly (ii) low-latency OLAP querying of large amounts of data; and (iii) extensible, while others are not. Some systems function mostly as a large ETL pipelines. F1 Query has also significantly reduced the closed silo, while others can easily pull in data from other sources. -
Containers at Google
Build What’s Next A Google Cloud Perspective Thomas Lichtenstein Customer Engineer, Google Cloud [email protected] 7 Cloud products with 1 billion users Google Cloud in DACH HAM BER ● New cloud region Germany Google Cloud Offices FRA Google Cloud Region (> 50% latency reduction) 3 Germany with 3 zones ● Commitment to GDPR MUC VIE compliance ZRH ● Partnership with MUC IoT platform connects nearly Manages “We found that Google Ads has the best system for 50 brands 250M+ precisely targeting customer segments in both the B2B with thousands of smart data sets per week and 3.5M and B2C spaces. It used to be hard to gain the right products searches per month via IoT platform insights to accurately measure our marketing spend and impacts. With Google Analytics, we can better connect the omnichannel customer journey.” Conrad is disrupting online retail with new Aleš Drábek, Chief Digital and Disruption Officer, Conrad Electronic services for mobility and IoT-enabled devices. Solution As Conrad transitions from a B2C retailer to an advanced B2B and Supports B2C platform for electronic products, it is using Google solutions to grow its customer base, develop on a reliable cloud infrastructure, Supports and digitize its workplaces and retail stores. Products Used 5x Mobile-First G Suite, Google Ads, Google Analytics, Google Chrome Enterprise, Google Chromebooks, Google Cloud Translation API, Google Cloud the IoT connections vs. strategy Vision API, Google Home, Apigee competitors Industry: Retail; Region: EMEA Number of Automate Everything running -
Beginning Java Google App Engine
apress.com Kyle Roche, Jeff Douglas Beginning Java Google App Engine A book on the popular Google App Engine that is focused specifically for the huge number of Java developers who are interested in it Kyle Roche is a practicing developer and user of Java technologies and the Google App Engine for building Java-based Cloud applications or Software as a Service (SaaS) Cloud Computing is a hot technology concept and growing marketplace that drives interest in this title as well Google App Engine is one of the key technologies to emerge in recent years to help you build scalable web applications even if you have limited previous experience. If you are a Java 1st ed., 264 p. programmer, this book offers you a Java approach to beginning Google App Engine. You will explore the runtime environment, front-end technologies like Google Web Toolkit, Adobe Flex, Printed book and the datastore behind App Engine. You'll also explore Java support on App Engine from end Softcover to end. The journey begins with a look at the Google Plugin for Eclipse and finishes with a 38,99 € | £35.49 | $44.99 working web application that uses Google Web Toolkit, Google Accounts, and Bigtable. Along [1]41,72 € (D) | 42,89 € (A) | CHF the way, you'll dig deeply into the services that are available to access the datastore with a 52,05 focus on Java Data Objects (JDO), JDOQL, and other aspects of Bigtable. With this solid foundation in place, you'll then be ready to tackle some of the more advanced topics like eBook integration with other cloud platforms such as Salesforce.com and Google Wave. -
Enterprise Procurement with GCP Marketplace Spend Smart, Procure Fast, and Help Your Development Team Succeed
Enterprise Procurement with GCP Marketplace Spend smart, procure fast, and help your development team succeed Be development’s strategic business partner Google Cloud offers a robust, enterprise-tailored, and vetted set of business solutions that will help establish you as a development ally. Spend strategically with options that can draw down your GCP committed spend, and enable your developers to procure directly from GCP Marketplace. Lastly, simplify multi-cloud billing with Orbitera Cloud Billing and Cost Management. Benefits ● Solutions are vetted by Google for security “We use GCP Marketplace to sell our vulnerabilities. Deployment options for industry-leading security solutions and for GCP, on-prem, and multi-cloud. purchasing because they support enterprise procurement with features such as private ● Solutions offer deployment templates so pricing and subscriptions." they launch quickly into the destination environment. Jane Chung VP Public Cloud ● Flexible and consolidated billing models Palo Alto Networks that fit your business needs. What’s new? Partner spotlight Free trial capability for Kubernetes, SaaS, and VM solutions. Subscription and private pricing options for some paid solutions. Anthos applications which can be deployed on-prem and in Google Cloud. For more information visit cloud.google.com/marketplace Features No Separate Billing Relationships Flexible Pricing Get solutions to your team fast by eliminating the Get individualized solution pricing quotes with need for separate billing agreements for partner private pricing. Subscription and usage-based solutions. Purchases from GCP Marketplace billing models fit various business needs. have Google as the seller of record. Retire Committed Spend Integrated Solutions Solutions procured through GCP Marketplace Remove deployment headaches with solutions may count toward GCP committed spend, if you that are tightly integrated with GCP and feature have a GCP spend agreement. -
Migrating Your Databases to Managed Services on Google Cloud Table of Contents
White paper June 2021 Migrating your databases to managed services on Google Cloud Table of Contents Introduction 3 Why choose cloud databases 3 The benefits of Google Cloud’s managed database services 5 Maximum compatibility for your workloads 6 For Oracle workloads: Bare Metal Solution for Oracle 8 For SQL Server workloads: Cloud SQL for SQL Server 10 For MySQL workloads: Cloud SQL for MySQL 12 For PostgreSQL workloads: Cloud SQL for PostgreSQL 14 For Redis and Memcached workloads: Memorystore 16 For Redis: Redis Enterprise Cloud 17 For Apache HBase workloads: Cloud Bigtable 19 For MongoDB workloads: MongoDB Atlas 20 For Apache Cassandra workloads: Datastax Astra 22 For Neo4j workloads: Neo4j Aura 23 For InfluxDB workloads: InfluxDB Cloud 25 Migrations that are simple, reliable, and secure 27 Assessing and planning your migration 27 Google Cloud streamlines your migrations 28 Google Cloud services and tools 28 Self-serve migration resources 28 Database migration technology partners 29 Google Professional Services 29 Systems integrators 29 Get started today 29 3 Introduction This paper is for technology decision makers, developers, architects, and DBAs. It focuses on modernizing database deployments with database services on Google Cloud. These services prioritize compatibility and simplicity of management, and include options for Oracle, SQL Server, MySQL, PostgreSQL, Redis, MongoDB, Cassandra, Neo4j, and other popular databases. To transform your business applications, consider Google Cloud native databases. For strategic applications that don’t go down, need on-demand and unlimited scalability, advanced security, and accelerated application development, Google provides the same cloud native database services that power thousands of applications at Google, including services like Google Search, Gmail, and YouTube with billions of users across the globe. -
A Bridge to the Cloud Damien Contreras ダミアン コントレラ Customer Engineer Specialist, Data Analytics, Google Cloud アジェンダ
A bridge to the Cloud Damien Contreras ダミアン コントレラ Customer Engineer Specialist, Data Analytics, Google Cloud アジェンダ 1 2 4 5 6 はじめに 移行する前の DWHの移行 GCP と連動 データの表示 準備 について はじめに 01 移行する前に| データウェアハウスの欠点 リアルタイムの負担は受 データ増加 けられない コスト データ形式対応外 セルフサービス分析 が難 しい ベンダーロックイン の心 スタースキーマとディメン 配 表ションとファクト表に合わ せる 移行する前に | データレイクの欠点 コスト クラスターのリソースの バージョンアップ バランス 複数のデータレイクが構築 パートナー、人材採用が困 される 難 移行する前に | Google Cloud の価値 コストパフォーマン 弾力性のある構 セキュリティー スが良い サイロはない サーバーレスでNo-ops ANSI SQL-2011 移行をする前に考 えること 02 Partners Cloud plan & cloud deploy 移行する前に | 社内にスキルはない場合 グーグルの支援 パートナーと BigQuery のスター Google リソースが ターパック 協力し合う https://cloud.google.com/partner s/?hl=ja 移行する前に | TCO & ROI アンケートを記入するだけ で 総所有コストのも計算 移行する前に | クラウドで構築 サイロ化に 2 3 なっている 1 データセット データと関連データの Proof of 基盤を構築 発見 Concept 誰でも ML を 使えれるよう 6 5 4 に 機械学習 ソースデータを 周りのシステム 移行 と通信用のツー ルの構築 DWH の移行について03 移行する前に | DWH移行対応 t n r m h o s v b ? Teradata IBM AWS Azure SQL Hadoop Oracle Snowfake Verica SAP BW その他 Netezza Redshif BigQuery t Teradata IBM Netezza から 13 IBM Netezza | アーキテクチャ FPGA CPU メモリー NZSQLコマンド:DML, データダンプ Host FPGA CPU (Linux JDBCコネクター:SQLクエリ メモリー サー バ) FPGA CPU Symmetric Multiprocessing メモリー (SMP)複数のマイクロプロセッサ Disk S-Blade Network Enclosure fabric AMPP Massively Parallel Processing Architecture (MPP) 大量な並行処理 IBM Netezza | データタイプ IBM Netezza の 31 タイプを全部 BigQuery でマッピングが出来ます IBM Netezza BigQuery VARCHAR STRING BOOLEANま BigQuery : TRUE / FALSE BOOL たBOOL Netezza : True / False, 1 / 0, yes / no, on / of TIME / TIMETZ / TIME BigQuery : の TIME でタイムゾーンはない TIME_WITH_TI ME_ZONE ARRAY Netezza : VARCHARのデータタイプに保存 IBM -
Nosql Database Comparison: Bigtable, Cassandra and Mongodb
Running Head: NOSQL DATABASE COMPARISON: BIGTABLE, CASSANDRA AND MONGODB NoSQL Database Comparison: Bigtable, Cassandra and MongoDB CJ Campbell Brigham Young University October 16, 2015 1 NOSQL DATABASE COMPARISON: BIGTABLE, CASSANDRA AND MONGODB INTRODUCTION THE SYSTEMS Google Bigtable History Data model & operations Physical Storage ACID properties Scalability Apache Cassandra History Data model & operations Physical Storage ACID properties Scalability MongoDB History Data model & operations Physical Storage ACID properties Scalability Differences Conclusion References 2 NOSQL DATABASE COMPARISON: BIGTABLE, CASSANDRA AND MONGODB Introduction As distributed systems are adopted and grown to scale, the need for scalable database solutions which meet the application’s exact need has become increasingly important. In the early days of computing, databases were almost entirely relational. Today, new breeds of database have emerged, called NoSQL databases. They are a common element in the grand design for most distributed software platforms. Each database is suited to a slightly different purpose from its peers. This paper discusses the features, similarities, and differences of three NoSQL databases: Google Bigtable, Apache Cassandra, and MongoDB. The Systems In this section, each of the three NoSQL databases are analyzed in-depth, starting with Google Bigtable, then Apache Cassandra, and finally MongoDB. Analysis includes their history, data model, accepted operations, physical storage schema, ACID properties, and scalability. Google Bigtable History. Bigtable was designed within Google to meet their internal data processing needs at scale. It began development in 2004 as part of their effort to handle large amounts of data across applications such as web indexing, Google Earth, Google Finance and more (Google, Inc., 2006). It first went into production use in April 2005. -
Google Cloud Security Whitepapers
1 Google Cloud Security Whitepapers March 2018 Google Cloud Encryption at Rest in Encryption in Transit in Application Layer Infrastructure Security Google Cloud Google Cloud Transport Security Design Overview in Google Cloud 2 Table of Contents Google Cloud Infrastructure Security Design Overview . 3 Encryption at Rest in Google Cloud . 23 Encryption in Transit in Google Cloud . 43 Application Layer Transport Security in Google Cloud . 75 3 A technical whitepaper from Google Cloud 4 Table of Contents Introduction . 7 Secure Low Level Infrastructure . 8 Security of Physical Premises Hardware Design and Provenance Secure Boot Stack and Machine Identity Secure Service Deployment . 9 Service Identity, Integrity, and Isolation Inter-Service Access Management Encryption of Inter-Service Communication Access Management of End User Data Secure Data Storage . 14 Encryption at Rest Deletion of Data Secure Internet Communication . 15 Google Front End Service Denial of Service (DoS) Protection User Authentication Operational Security . 17 Safe Software Development Keeping Employee Devices and Credentials Safe Reducing Insider Risk Intrusion Detection 5 Securing the Google Cloud Platform (GCP) . .. 19 Conclusion . 21 Additional Reading . 22 The content contained herein is correct as of January 2017, and represents the status quo as of the time it was written. Google’s security policies and systems may change going forward, as we continually improve protection for our customers. 6 CIO-level summary • Google has a global scale technical infrastructure designed to provide security through the entire information processing lifecycle at Google. This infrastructure provides secure deployment of services, secure storage of data with end user privacy safeguards, secure communications between services, secure and private communication with customers over the internet, and safe operation by administrators. -
Ray Cromwell
Building Applications with Google APIs Ray Cromwell Monday, June 1, 2009 “There’s an API for that” • code.google.com shows 60+ APIs • full spectrum (client, server, mobile, cloud) • application oriented (android, opensocial) • Does Google have a Platform? Monday, June 1, 2009 Application Ecosystem Client REST/JSON, GWT, Server ProtocolBuffers Earth PHP Java O3D App Services Media Docs Python Ruby Utility Blogger Spreadsheets Maps/Geo JPA/JDO/Other Translate Base Datastore GViz Social MySQL Search OpenSocial Auth FriendConnect $$$ ... GData Contacts AdSense Checkout Monday, June 1, 2009 Timefire • Store and Index large # of time series data • Scalable Charting Engine • Social Collaboration • Story Telling + Video/Audio sync • Like “Google Maps” but for “Time” Monday, June 1, 2009 Android Version 98% Shared Code with Web version Monday, June 1, 2009 Android • Full API stack • Tight integration with WebKit browser • Local database, 2D and 3D APIs • External XML UI/Layout system • Makes separating presentation from logic easier, benefits code sharing Monday, June 1, 2009 How was this done? • Google Web Toolkit is the Foundation • Target GWT JRE as LCD • Use Guice Dependency Injection for platform-specific APIs • Leverage GWT 1.6 event system Monday, June 1, 2009 Example App Code Device/Service JRE interfaces Guice Android Browser Impl Impl Android GWT Specific Specific Monday, June 1, 2009 Shared Widget Events interface HasClickHandler interface HasClickHandler addClickHandler(injectedHandler) addClickHandler(injectedHandler) Gin binds GwtHandlerImpl