This document discusses how to call JavaScript, JQuery, and Angular $scope functions from the browser console. It provides an example Angular application with different functions and demonstrates calling each from the console. To call a JavaScript function, enter its name directly. To call a JQuery function, use $().functionName(). To call an Angular $scope function, use angular.element(element).scope().functionName(), where element is the DOM element with the ng-controller.
NoSQL, No Worries: Vecchi Problemi, Nuove SoluzioniSteve Maraspin
Slide del talk sulle basi di dati non relazionali (NoSQL) al Codemotion di Venezia del 17/11/2012. Presentato un caso di studio di architettura basata su CouchDB, MongoDB, Redis e OrientDB, oltre che diversi concetti relativi ai datastore NoSQL.
Data Analytics and Distribution with Power BIdesertislesql
Learn how to apply predictive data forecasting, natural language Q&A, and distribute updated reports to tablets and phones with Power BI. By exploring the components provided outside of Excel, including modeling, dissemination and data availability, report distribution and the data refresh capabilities which make this all possible, you will get a better understanding of what capabilities exist to provide better access and analytics to your data with Power BI.
Take a look at the real-time streaming datasets in Power BI. Covering what is the streaming API, how to push data to it and then display that in dashboards and reports. A look at sample data that is well suited to real-time display.
SQL Server is really the brain of SharePoint; in this session, Serge Luca (SharePoint MVP) and Isabelle Van Campenhoudt (SQL Server MVP) will give you an overview of what any SharePoint consultant and DBA need to know regarding business continuity in SharePoint 2013 & 2016. Of course SQL Server plays a major role in this story; the sessions will be animated with real & live demos.
Topics covered:
Concepts of business continuity
SharePoint and Business continuity
Patterns and anti-patterns
SharePoint and SQL Server Always on Availability groups : what works, what doesn’t work (demos)
Lessons learned from real projects
SharePoint 2016 Min Role and Business continuity
This document discusses how to call JavaScript, JQuery, and Angular $scope functions from the browser console. It provides an example Angular application with different functions and demonstrates calling each from the console. To call a JavaScript function, enter its name directly. To call a JQuery function, use $().functionName(). To call an Angular $scope function, use angular.element(element).scope().functionName(), where element is the DOM element with the ng-controller.
NoSQL, No Worries: Vecchi Problemi, Nuove SoluzioniSteve Maraspin
Slide del talk sulle basi di dati non relazionali (NoSQL) al Codemotion di Venezia del 17/11/2012. Presentato un caso di studio di architettura basata su CouchDB, MongoDB, Redis e OrientDB, oltre che diversi concetti relativi ai datastore NoSQL.
Data Analytics and Distribution with Power BIdesertislesql
Learn how to apply predictive data forecasting, natural language Q&A, and distribute updated reports to tablets and phones with Power BI. By exploring the components provided outside of Excel, including modeling, dissemination and data availability, report distribution and the data refresh capabilities which make this all possible, you will get a better understanding of what capabilities exist to provide better access and analytics to your data with Power BI.
Take a look at the real-time streaming datasets in Power BI. Covering what is the streaming API, how to push data to it and then display that in dashboards and reports. A look at sample data that is well suited to real-time display.
SQL Server is really the brain of SharePoint; in this session, Serge Luca (SharePoint MVP) and Isabelle Van Campenhoudt (SQL Server MVP) will give you an overview of what any SharePoint consultant and DBA need to know regarding business continuity in SharePoint 2013 & 2016. Of course SQL Server plays a major role in this story; the sessions will be animated with real & live demos.
Topics covered:
Concepts of business continuity
SharePoint and Business continuity
Patterns and anti-patterns
SharePoint and SQL Server Always on Availability groups : what works, what doesn’t work (demos)
Lessons learned from real projects
SharePoint 2016 Min Role and Business continuity
Microsoft PowerPivot & Power View in Excel 2013Mark Ginnebaugh
PowerPivot is an add-in for Excel that empowers business users to create their own tabular data models. Power View is also available in the Excel 2013 client. It was first released as a server-based report authoring tool with SQL Server 2012 and is available in SharePoint Server 2010 Enterprise.
You'll learn:
* How to work with the add-in in the Excel 2013 client
* How compelling interactive reports can be created quickly and easily
* The new PowerPivot features - including pie charts, maps, KPIs, hierarchies, drill down/drill up, and report styles
Peter Myers specializes in Microsoft Business Intelligence, and provides mentoring, technical training and course content authoring for SQL Server and Office. Peter has current SQL Server and MCT certifications, and has been a Microsoft MVP (Most Valued Professional) since 2007.
This slide deck explains in a comprehensive way what Power BI is, how the Power BI architecture looks like and what the usage scenarios are for using Power BI and related tools
BI: new of the buzz words that everyone is talking about but what is it? How can it be used to make a impact in my organization? How do I get started? In this session, we will talk about it and show you a live example in Office 365's SharePoint Online.
Objectives/Outcomes: In this session, participants will learn:
1. What is BI
2. What is Microsoft's Power BI
3. Case Studies
4. How can I get it
Power BI Create lightning fast dashboard with power bi & Its Components Vishal Pawar
Every data has meaning, but we had limitation to use data through big long running process Extraction, Transformation and Representation, but now Power BI solves your problem to kick start having Data extraction in Power Query, Data Modelling and Transformation in Power Pivot and reach data representation using power view and power map on demand any nearby device on your fingertips, You will learn all latest and greatest features of Power BI.
Technology is designed for humans, by humans. See how the era of human technology will transform both business and society in trend 4 of the Tech Vision 2017.
Presented to The Ottawa IT Community Meetup Group (Ottawa SQL - PASS Chapter) on Thursday September 19
Powerful Self-Service BI in Excel 2013 - Data search and discovery with Power Query (formerly "Data Explorer"), analyzing and modeling with Power Pivot, visualizing and exploring with Power View and Power Map (formerly codename "GeoFlow")
In the ecosystem-driven digital economy, the rules are still waiting to be written. Leaders must work to shape the digital markets of tomorrow. Grab your guidebook in trend 5 of the 2017 Technology Vision.
Learn Power BI with Power Pivot, Power Query, Power View, Power Map and Q&AVishal Pawar
The document appears to be a slide deck presentation about Microsoft Power BI. It includes slides on Power Query, Power Pivot, Power View and Power Map. The presentation provides overviews of these tools, describes their capabilities and functionality, and includes demos of how to use them. It discusses how Power BI allows users to discover, visualize and share insights from data.
Power BI is a self-service business intelligence tool that allows users to analyze data and create reports and visualizations. It includes components for data discovery, analysis, and visualization both on-premises using Excel and in the cloud using the Power BI service. The tool integrates with Office 365 and allows users to discover, visualize, and share insights from data.
In 2016, cloud technologies went mainstream. But with maturity came the realization that moving to the cloud doesn’t happen overnight. CIOs are prioritizing hosted computing and cloud data storage. But they’re approaching the shift as a gradual, multi-year journey.
Many startups and small businesses will continue to go all-in on cloud. But enterprises will find success in a slow but steady move from on-prem. Hybrid ecosystems—of data, software, and infrastructure—will be the reality for most established organizations.
As this shift to cloud progresses where are things are headed? This paper highlights the top cloud trends for 2017.
Building your role in digital ecosystems is the key to unlocking future growth. Digital platforms are the gateway to new digital ecosystems. See how will you can use them to grow in trend 2 of Tech Vision 2017.
Power BI is a cloud-based business analytics service that allows users to bring their data together and gain insights. It provides a single view of critical business data through live dashboards and rich interactive reports. Gartner has positioned Microsoft as a leader in business intelligence and analytics platforms for nine consecutive years based on its vision. The demo showcases how to create a Power BI account, import and transform different data sources to build a data model, create reports and columns/measures, and publish reports to the web.
Uno sguardo agli strumenti informatici per il settore commerciale. Con una particolare attenzione al Web, al Cloud, al CRM e alle nuove tecnologie Mobile.
Power Platform: AI Builder la democratizzazione di AIAlessio Biasiutti
L'utilizzo dell'intelligenza artificiale fa crescere molto di più i fatturati delle aziende che la utilizzano rispetto a quelle che non lo stanno facendo. La mancanza di competenze in azienda è quindi un freno alla crescita. AI Builder è la risposta code-less alla creazione di modelli di AI
I Graph Database: analisi del comportamento degli utentiThinkOpen
Roberto Grandi, esperto di Data Analytics & Business Intelligence, presenta il workshop “I Graph Database: analisi del comportamento degli utenti”.
Nell’incontro Roberto esplora il mondo dei graph database, strumenti poco conosciuti ma molto intuitivi e potenti per rappresentare le relazioni online in modo del tutto naturale.
Nella presentazione viene illustrato come è cambiato il concetto di relazione applicandolo ad uno use case specifico: l'analisi del comportamento dell'utente e dei suoi gusti. Saper riconoscere la propensione e determinare con accuratezza la prossima mossa dell’user è fondamentale per allocare le risorse corrette dal punto di vista del business.
Durante una sessione pratica vengono mostrati i costrutti base del linguaggio Cypher con Neo4J e alcuni algoritmi utili a caratterizzare il comportamento del cliente.
Le basi della SEO | Quando il posizionamento ha un'animaMichele Franzese
Le slide del corso SEO di Seogarden.net riportano tutti gli aspetti che vengono trattati nelle 5 lezioni da 3 ore ciascuna in cui il corso è suddiviso.
Si parte dagli elementi di base dell'ottimizzazione seo, per poi analizzare tutti gli strumenti di monitoraggio e le tecniche avanzate di link building, fino all'analisi delle strategie di posizionamento di siti web diversi per tipologia e obiettivi.
Ho cercato di rappresentare tutti gli aspetti della SEO, per giungere ad una conclusione, siccome oggi più che mai la SERP non è più solo frutto di un lavoro ben fatto dal punto di vista tecnico, al professionista della SEO vengono richieste nuove competenze, dalla semantica al copywriting, fino alla capacità di relazionarsi con gruppi eterogenei di stakeholder.
Microsoft PowerPivot & Power View in Excel 2013Mark Ginnebaugh
PowerPivot is an add-in for Excel that empowers business users to create their own tabular data models. Power View is also available in the Excel 2013 client. It was first released as a server-based report authoring tool with SQL Server 2012 and is available in SharePoint Server 2010 Enterprise.
You'll learn:
* How to work with the add-in in the Excel 2013 client
* How compelling interactive reports can be created quickly and easily
* The new PowerPivot features - including pie charts, maps, KPIs, hierarchies, drill down/drill up, and report styles
Peter Myers specializes in Microsoft Business Intelligence, and provides mentoring, technical training and course content authoring for SQL Server and Office. Peter has current SQL Server and MCT certifications, and has been a Microsoft MVP (Most Valued Professional) since 2007.
This slide deck explains in a comprehensive way what Power BI is, how the Power BI architecture looks like and what the usage scenarios are for using Power BI and related tools
BI: new of the buzz words that everyone is talking about but what is it? How can it be used to make a impact in my organization? How do I get started? In this session, we will talk about it and show you a live example in Office 365's SharePoint Online.
Objectives/Outcomes: In this session, participants will learn:
1. What is BI
2. What is Microsoft's Power BI
3. Case Studies
4. How can I get it
Power BI Create lightning fast dashboard with power bi & Its Components Vishal Pawar
Every data has meaning, but we had limitation to use data through big long running process Extraction, Transformation and Representation, but now Power BI solves your problem to kick start having Data extraction in Power Query, Data Modelling and Transformation in Power Pivot and reach data representation using power view and power map on demand any nearby device on your fingertips, You will learn all latest and greatest features of Power BI.
Technology is designed for humans, by humans. See how the era of human technology will transform both business and society in trend 4 of the Tech Vision 2017.
Presented to The Ottawa IT Community Meetup Group (Ottawa SQL - PASS Chapter) on Thursday September 19
Powerful Self-Service BI in Excel 2013 - Data search and discovery with Power Query (formerly "Data Explorer"), analyzing and modeling with Power Pivot, visualizing and exploring with Power View and Power Map (formerly codename "GeoFlow")
In the ecosystem-driven digital economy, the rules are still waiting to be written. Leaders must work to shape the digital markets of tomorrow. Grab your guidebook in trend 5 of the 2017 Technology Vision.
Learn Power BI with Power Pivot, Power Query, Power View, Power Map and Q&AVishal Pawar
The document appears to be a slide deck presentation about Microsoft Power BI. It includes slides on Power Query, Power Pivot, Power View and Power Map. The presentation provides overviews of these tools, describes their capabilities and functionality, and includes demos of how to use them. It discusses how Power BI allows users to discover, visualize and share insights from data.
Power BI is a self-service business intelligence tool that allows users to analyze data and create reports and visualizations. It includes components for data discovery, analysis, and visualization both on-premises using Excel and in the cloud using the Power BI service. The tool integrates with Office 365 and allows users to discover, visualize, and share insights from data.
In 2016, cloud technologies went mainstream. But with maturity came the realization that moving to the cloud doesn’t happen overnight. CIOs are prioritizing hosted computing and cloud data storage. But they’re approaching the shift as a gradual, multi-year journey.
Many startups and small businesses will continue to go all-in on cloud. But enterprises will find success in a slow but steady move from on-prem. Hybrid ecosystems—of data, software, and infrastructure—will be the reality for most established organizations.
As this shift to cloud progresses where are things are headed? This paper highlights the top cloud trends for 2017.
Building your role in digital ecosystems is the key to unlocking future growth. Digital platforms are the gateway to new digital ecosystems. See how will you can use them to grow in trend 2 of Tech Vision 2017.
Power BI is a cloud-based business analytics service that allows users to bring their data together and gain insights. It provides a single view of critical business data through live dashboards and rich interactive reports. Gartner has positioned Microsoft as a leader in business intelligence and analytics platforms for nine consecutive years based on its vision. The demo showcases how to create a Power BI account, import and transform different data sources to build a data model, create reports and columns/measures, and publish reports to the web.
Uno sguardo agli strumenti informatici per il settore commerciale. Con una particolare attenzione al Web, al Cloud, al CRM e alle nuove tecnologie Mobile.
Power Platform: AI Builder la democratizzazione di AIAlessio Biasiutti
L'utilizzo dell'intelligenza artificiale fa crescere molto di più i fatturati delle aziende che la utilizzano rispetto a quelle che non lo stanno facendo. La mancanza di competenze in azienda è quindi un freno alla crescita. AI Builder è la risposta code-less alla creazione di modelli di AI
I Graph Database: analisi del comportamento degli utentiThinkOpen
Roberto Grandi, esperto di Data Analytics & Business Intelligence, presenta il workshop “I Graph Database: analisi del comportamento degli utenti”.
Nell’incontro Roberto esplora il mondo dei graph database, strumenti poco conosciuti ma molto intuitivi e potenti per rappresentare le relazioni online in modo del tutto naturale.
Nella presentazione viene illustrato come è cambiato il concetto di relazione applicandolo ad uno use case specifico: l'analisi del comportamento dell'utente e dei suoi gusti. Saper riconoscere la propensione e determinare con accuratezza la prossima mossa dell’user è fondamentale per allocare le risorse corrette dal punto di vista del business.
Durante una sessione pratica vengono mostrati i costrutti base del linguaggio Cypher con Neo4J e alcuni algoritmi utili a caratterizzare il comportamento del cliente.
Le basi della SEO | Quando il posizionamento ha un'animaMichele Franzese
Le slide del corso SEO di Seogarden.net riportano tutti gli aspetti che vengono trattati nelle 5 lezioni da 3 ore ciascuna in cui il corso è suddiviso.
Si parte dagli elementi di base dell'ottimizzazione seo, per poi analizzare tutti gli strumenti di monitoraggio e le tecniche avanzate di link building, fino all'analisi delle strategie di posizionamento di siti web diversi per tipologia e obiettivi.
Ho cercato di rappresentare tutti gli aspetti della SEO, per giungere ad una conclusione, siccome oggi più che mai la SERP non è più solo frutto di un lavoro ben fatto dal punto di vista tecnico, al professionista della SEO vengono richieste nuove competenze, dalla semantica al copywriting, fino alla capacità di relazionarsi con gruppi eterogenei di stakeholder.
OpenData with Android Google Services by Pietro Alberto RossiCodemotion
The purpose of this talk is to introduce the main concepts of OpenData and propose possible development solutions in Android with Google Services API.
Will be introduced regulations of OpenData and the current situation regarding the mobile environment.
Will discuss the future of OpenData in Italy and the investment opportunities.
Big Data e Business Intelligence. Intervento del Prof. Pozzan nell'ambito dell'open day organizzato dalla Fondazione ITS Kennedy di Pordenone, evento del 13 settembre 2014 in cui sono stati presentati i temi per i corsi in partenza a novembre 2014.
Polyglot Persistence e Big Data: tra innovazione e difficoltà su casi reali -...Data Driven Innovation
Oggi il tema non è più SI o NO ai sistemi NoSQL. Il problema sta nella capacità di essere “poliglotti” nell’uso di tecnologie per la gestione di dati e informazioni. Le strategie di innovazione sui Big Data nelle aziende non può prescindere dalla Polyglot Persistence, ma le difficoltà sono tante, specie in ambienti complessi ed enterprise. Ma la necessità di fare innovazione non è forte solo nelle startup, anzi…
Gartner prevede che oltre il 70 % delle implementazioni di Hadoop non soddisferà gli obiettivi di generazione di business e di riduzione dei costi a causa della mancanza di competenze sul mercato oltre che alle difficoltà d’integrazione.
Costruire un Recommendation Engine con Cosmos DBLaura Villa
In un mondo sommerso da contenuti e prodotti, i sistemi di raccomandazione offrono un aiuto agli utenti e rappresentano una opportunità per le aziende in molti settori. In questa sessione vedremo le basi per attraversare un grafo alla ricerca di spunti per i nostri utenti, in modo da creare un semplice Recommendation Engine da integrare nelle nostre applicazioni. Il tutto utilizzando le Gremlin API di Cosmos DB, con un occhio di riguardo ai costi.
Sono passati decine di anni dai primi siti web composti solo da testo, immagini e link. Ora gli utenti pretendono di più volendo fare di meno. Desiderano che il tuo sito web capisca i loro gusti, fornisca approfondimenti, si modifichi in base alle loro esigenze. Durante questo intervento verranno forniti consigli su quali tecniche e servizi di text analysis, collective intelligence e semantic web possono rendere il nostro sito web intelligente.
Analizzare il valore dei link, scegliere le metriche con cui misurarli e adattare le proprie strategie di acquisizione al fine di generare traffico organico di valore per il proprio sito.
MongoDB SoCal 2020: Migrate Anything* to MongoDB AtlasMongoDB
This presentation discusses migrating data from other data stores to MongoDB Atlas. It begins by explaining why MongoDB and Atlas are good choices for data management. Several preparation steps are covered, including sizing the target Atlas cluster, increasing the source oplog, and testing connectivity. Live migration, mongomirror, and dump/restore options are presented for migrating between replicasets or sharded clusters. Post-migration steps like monitoring and backups are also discussed. Finally, migrating from other data stores like AWS DocumentDB, Azure CosmosDB, DynamoDB, and relational databases are briefly covered.
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!MongoDB
These days, everyone is expected to be a data analyst. But with so much data available, how can you make sense of it and be sure you're making the best decisions? One great approach is to use data visualizations. In this session, we take a complex dataset and show how the breadth of capabilities in MongoDB Charts can help you turn bits and bytes into insights.
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...MongoDB
MongoDB Kubernetes operator and MongoDB Open Service Broker are ready for production operations. Learn about how MongoDB can be used with the most popular container orchestration platform, Kubernetes, and bring self-service, persistent storage to your containerized applications. A demo will show you how easy it is to enable MongoDB clusters as an External Service using the Open Service Broker API for MongoDB
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDBMongoDB
Are you new to schema design for MongoDB, or are you looking for a more complete or agile process than what you are following currently? In this talk, we will guide you through the phases of a flexible methodology that you can apply to projects ranging from small to large with very demanding requirements.
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...MongoDB
Humana, like many companies, is tackling the challenge of creating real-time insights from data that is diverse and rapidly changing. This is our journey of how we used MongoDB to combined traditional batch approaches with streaming technologies to provide continues alerting capabilities from real-time data streams.
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series DataMongoDB
Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe.
This talk covers:
Common components of an IoT solution
The challenges involved with managing time-series data in IoT applications
Different schema designs, and how these affect memory and disk utilization – two critical factors in application performance.
How to query, analyze and present IoT time-series data using MongoDB Compass and MongoDB Charts
At the end of the session, you will have a better understanding of key best practices in managing IoT time-series data with MongoDB.
Join this talk and test session with a MongoDB Developer Advocate where you'll go over the setup, configuration, and deployment of an Atlas environment. Create a service that you can take back in a production-ready state and prepare to unleash your inner genius.
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]MongoDB
Our clients have unique use cases and data patterns that mandate the choice of a particular strategy. To implement these strategies, it is mandatory that we unlearn a lot of relational concepts while designing and rapidly developing efficient applications on NoSQL. In this session, we will talk about some of our client use cases, the strategies we have adopted, and the features of MongoDB that assisted in implementing these strategies.
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB
Encryption is not a new concept to MongoDB. Encryption may occur in-transit (with TLS) and at-rest (with the encrypted storage engine). But MongoDB 4.2 introduces support for Client Side Encryption, ensuring the most sensitive data is encrypted before ever leaving the client application. Even full access to your MongoDB servers is not enough to decrypt this data. And better yet, Client Side Encryption can be enabled at the "flick of a switch".
This session covers using Client Side Encryption in your applications. This includes the necessary setup, how to encrypt data without sacrificing queryability, and what trade-offs to expect.
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...MongoDB
MongoDB Kubernetes operator is ready for prime-time. Learn about how MongoDB can be used with most popular orchestration platform, Kubernetes, and bring self-service, persistent storage to your containerized applications.
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!MongoDB
These days, everyone is expected to be a data analyst. But with so much data available, how can you make sense of it and be sure you're making the best decisions? One great approach is to use data visualizations. In this session, we take a complex dataset and show how the breadth of capabilities in MongoDB Charts can help you turn bits and bytes into insights.
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your MindsetMongoDB
When you need to model data, is your first instinct to start breaking it down into rows and columns? Mine used to be too. When you want to develop apps in a modern, agile way, NoSQL databases can be the best option. Come to this talk to learn how to take advantage of all that NoSQL databases have to offer and discover the benefits of changing your mindset from the legacy, tabular way of modeling data. We’ll compare and contrast the terms and concepts in SQL databases and MongoDB, explain the benefits of using MongoDB compared to SQL databases, and walk through data modeling basics so you feel confident as you begin using MongoDB.
MongoDB .local San Francisco 2020: MongoDB Atlas JumpstartMongoDB
Join this talk and test session with a MongoDB Developer Advocate where you'll go over the setup, configuration, and deployment of an Atlas environment. Create a service that you can take back in a production-ready state and prepare to unleash your inner genius.
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...MongoDB
The document discusses guidelines for ordering fields in compound indexes to optimize query performance. It recommends the E-S-R approach: placing equality fields first, followed by sort fields, and range fields last. This allows indexes to leverage equality matches, provide non-blocking sorts, and minimize scanning. Examples show how indexes ordered by these guidelines can support queries more efficiently by narrowing the search bounds.
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++MongoDB
Aggregation pipeline has been able to power your analysis of data since version 2.2. In 4.2 we added more power and now you can use it for more powerful queries, updates, and outputting your data to existing collections. Come hear how you can do everything with the pipeline, including single-view, ETL, data roll-ups and materialized views.
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...MongoDB
The document describes a methodology for data modeling with MongoDB. It begins by recognizing the differences between document and tabular databases, then outlines a three step methodology: 1) describe the workload by listing queries, 2) identify and model relationships between entities, and 3) apply relevant patterns when modeling for MongoDB. The document uses examples around modeling a coffee shop franchise to illustrate modeling approaches and techniques.
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep DiveMongoDB
MongoDB Atlas Data Lake is a new service offered by MongoDB Atlas. Many organizations store long term, archival data in cost-effective storage like S3, GCP, and Azure Blobs. However, many of them do not have robust systems or tools to effectively utilize large amounts of data to inform decision making. MongoDB Atlas Data Lake is a service allowing organizations to analyze their long-term data to discover a wealth of information about their business.
This session will take a deep dive into the features that are currently available in MongoDB Atlas Data Lake and how they are implemented. In addition, we'll discuss future plans and opportunities and offer ample Q&A time with the engineers on the project.
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & GolangMongoDB
Virtual assistants are becoming the new norm when it comes to daily life, with Amazon’s Alexa being the leader in the space. As a developer, not only do you need to make web and mobile compliant applications, but you need to be able to support virtual assistants like Alexa. However, the process isn’t quite the same between the platforms.
How do you handle requests? Where do you store your data and work with it to create meaningful responses with little delay? How much of your code needs to change between platforms?
In this session we’ll see how to design and develop applications known as Skills for Amazon Alexa powered devices using the Go programming language and MongoDB.
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...MongoDB
aux Core Data, appréciée par des centaines de milliers de développeurs. Apprenez ce qui rend Realm spécial et comment il peut être utilisé pour créer de meilleures applications plus rapidement.
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...MongoDB
Il n’a jamais été aussi facile de commander en ligne et de se faire livrer en moins de 48h très souvent gratuitement. Cette simplicité d’usage cache un marché complexe de plus de 8000 milliards de $.
La data est bien connu du monde de la Supply Chain (itinéraires, informations sur les marchandises, douanes,…), mais la valeur de ces données opérationnelles reste peu exploitée. En alliant expertise métier et Data Science, Upply redéfinit les fondamentaux de la Supply Chain en proposant à chacun des acteurs de surmonter la volatilité et l’inefficacité du marché.
2. Chi sono?
• Solutions Architect/Evangelist in MongoDB Inc.
• 24 anni di esperienza nel mondo dei database e dello
sviluppo software
• Ex dipendente di MySQL
• In precedenza: web,web,web
3. Agenda
• Che cos’è un Record?
• Concetti chiave
• Che cos’è un’Entità?
• Associazione tra Entità
• Suggerimenti generali
7. Chiave → Valore
• Storage mono-dimensionale
• Il singolo valore e’un blob
• Le query sono solo per chiave
• Nessuno schema
• I valore non può essere aggiornato ma solamente
sovrascritto
Key Blob
8. Relazionale
• Storage bi-dimensionale (tuple)
• Ogni campo contiene solo un valore
• Query sono su ogni campo
• Schema molto strutturato (tabelle)
• Update sul posto
• Il processo di normalizzazione richiede molte tabelle,
indici e con una pessima localizzazione dei dati.
Primary
Key
9. Documento
• Storage N-dimensionale
• Ogni campo può contenere 0,1,
tanti o valori incapsulati
• Query su tutti i campi e livelli
• Schema dinamico
• Update in linea
• Incapsulare i dati migliora la localizzazione dei dati,
richiede meno indici e ha migliori performance
_id
17. E come si sviluppava il software?
pio, il LISP (LISt Processing language) [24].
A quel tempo, i problemi significativi non ri-
denti con interfacce chiare e componibili. Si
diffusero concetti quali la programmazione
1
ei
gi
Processo Bisogno Linguaggio
1950
1960
1970
1980
1990
2000
Primi tentativi di “ordine”
nello sviluppo
Comprensibilità e portabilità del codice,
per sostenere la sua evoluzione
Organizzazione “industriale”
dello sviluppo dei sistemi software
Impossibilità di definire in modo
preciso il sistema da sviluppare
Sviluppo e distribuzione molto
rapidi e orientati ai sistemi
di comunicazione
Waterfall, a “V”, ...
Incrementale, Spirale, ...
Metodologie agili
Linguaggi assemblativi
Linguaggi di alto livello
Linguaggi strutturati
Linguaggi orientati agli oggetti
Linguaggi per lo sviluppo
dinamico
18. RDBMS Rende lo Sviluppo Difficile
Relational
Database
Object Relational
Mapping
Application
Code XML Config DB Schema
19. E Ancora Più Difficile Evolverlo…
New
Table
New
Table
New
Column
Name Pet Phone Email
New
Column
3 months later…
20. RDBMS
Dalla Complessità alla Semplicità..
MongoDB
{
_id : ObjectId("4c4ba5e5e8aabf3"),
employee_name: "Dunham, Justin",
department : "Marketing",
title : "Product Manager, Web",
report_up: "Neray, Graham",
pay_band: “C",
benefits : [
{ type : "Health",
plan : "PPO Plus" },
{ type : "Dental",
plan : "Standard" }
]
}
24. I 3 Elementi fondamentali dello
Schema Design Documentale
25. 1 – Flessibilità
• Scelte per lo schema design
• Ogni documento può avere campi differenti
• I nomi di campi sono consistenti per la
programmazione
• La struttura può essere forzata dall’applicazione
• Facile da evolvere secondo necessità
26. 2 – Arrays – Valori Multipli per Campo
• Ogni campi può essere:
– Assente
– Settato a null
– Settato a un valore singolo
– Settato a un array con molteplici valori
• Query per ogni valore:
– Può essere indicizzato e ogni valore dell’array è nell’indice
27. 3 – Documenti Incapsulati (embedded)
• Un valore accettato è un documento
• I documenti nidificati creano la struttura
• Query di ogni campo ad ogni livello
– Possono essere indicizzati
29. Un’Entità
• Un Oggetto del vostro modello
• Ci sono Associazioni con altre entità
Referencing (Relazionale) Embedding (Documentale)
has_one embeds_one
belongs_to embedded_in
has_many embeds_many
has_and_belongs_to_many
MongoDB ha sia il referencing sia l’embedding per un uso generale
35. Contatti
• nome
• azienda
• adress
• Street
• City
• State
• Zip
• titolo
• telefono
• indirizzi
• strada
• città
• stato
• cap
Schema Documentale
36. In cosa differiscono? E Perché?
Contact
• name
• company
• title
• phone
Address
• street
• city
• state
• zip_code
Contact
• name
• company
• adress
• Street
• City
• State
• Zip
• title
• phone
• address
• street
• city
• state
• zip_code
41. Tipico ERD di una Rubrica
Contacts
• name
• company
• title
Addresses
• type
• street
• city
• state
• zip_code
Phones
• type
• number
Emails
• type
• address
Thumbnails
• mime_type
• data
Portraits
• mime_type
• data
Groups
• name
N
1
N
1
N
N
N
1
1
1
11
Twitters
• name
• location
• web
• bio
1
1
43. 1-a-1
Contacts
• name
• company
• title
Addresses
• type
• street
• city
• state
• zip_code
Phones
• type
• number
Emails
• type
• address
Thumbnails
• mime_type
• data
Portraits
• mime_type
• data
Groups
• name
N
1
N
1
N
N
N
1
1
1
11
Twitters
• name
• location
• web
• bio
1
1
44. 1-a-1
Scelte di Schema Design
contact
• twitter_id
twitter1 1
contact twitter
• contact_id1 1
E’ ridondante tenere entrambe le relazioni
• Entrambe devono essere aggiornate per consistenza
• Posso risparmiare una lettura?
Contact
• twitter
twitter 1
45. 1-a-1
Consigli Generali
• Tutto il contatto in un sol colpo
– Il contatto embedda twitter
• Relazione padre-figlio
– “contiene”
• Nessuna duplicazioni dei dati
• Possibilie eseguire query o indicizzare il campo
incapsulato
– Ad es.,“twitter.nome”
– Eccezioni…
• L’immagine del ritratto potrebbe essere troppo
grande
Contact
• twitter
twitter 1
46. 1-a-molti
Contacts
• name
• company
• title
Addresses
• type
• street
• city
• state
• zip_code
Phones
• type
• number
Emails
• type
• address
Thumbnails
• mime_type
• data
Portraits
• mime_type
• data
Groups
• name
N
1
N
1
N
N
N
1
1
1
11
Twitters
• name
• location
• web
• bio
1
1
47. 1-a-molti
Scelte di Schema Design
contact
• phone_ids: [ ]
phone1 N
contact phone
• contact_id1 N
E’ ridondante tenere entrambe le relazioni
• Entrambe devono essere aggiornate per consistenza
• Non possibile in un DB relazionale
• E’ possibile risparmiare letture?
Contact
• phones
phone N
48. 1-a-molti
Consigli Generali
• Tutto il contatto in un sol colpo
– Il contatto incapsula molteplici telefoni
• Relazione Padre-Figlio
– “contiene”
• Nessuna duplicazione di dati
• Si possono eseguire query o indicizzare ogni campo
– e.g., { “phones.type”: “mobile” }
– Eccezioni…
• Dimensioni: la grandezza massima di un
documento è 16MB
Contact
• phones
phone N
49. molti-a-molti
Contacts
• name
• company
• title
Addresses
• type
• street
• city
• state
• zip_code
Phones
• type
• number
Emails
• type
• address
Thumbnails
• mime_type
• data
Portraits
• mime_type
• data
Groups
• name
N
1
N
1
N
N
N
1
1
1
11
Twitters
• name
• location
• web
• bio
1
1
50. Molti-a-molti
Associazione del mondo relazionale
Join table
Contacts
• name
• company
• title
• phone
Groups
• name
GroupContacts
• group_id
• contact_id
nei documenti si usano gli arrays
X
51. Molti-a-molti
Scelte di Schema Design
group
• contact_ids: [ ]
contactN N
group contact
• group_ids: [ ]N N
Redundant to track
relationship on both sides
• Both references must be
updated for consistency
Redundant to track
relationship on both sides
• Duplicated data must be
updated for consistency
group
• contacts
contact
N
contact
• groups
group
N
52. Molti-a-Molti
Consigli Generali
• Dipende dai casi
1. Rubrica semplice
• I contatti referenziano i gruppi
2. Gruppi di email corporate
• I gruppi incapsulano i contatti per performance
• Eccezioni
– Scalabilità: dimensione massima documenti16MB
– Scalabilità: può avere impatti sulle performance and sulle
dimensioni del working set
group contact
• group_ids: [ ]N N
53. Contacts
• name
• company
• title
addresses
• type
• street
• city
• state
• zip_code
phones
• type
• number
emails
• type
• address
thumbnail
• mime_type
• data
Portraits
• mime_type
• data
Groups
• name
N
1
N
1
twitter
• name
• location
• web
• bio
N
N
N
1
1
Modello del documento – Rappresentazione efficiente
54. Esempio di documento di un contatto
{
“name” : “Gary J. Murakami, Ph.D.”,
“company” : “MongoDB, Inc.”,
“title” : “Lead Engineer”,
“twitter” : {
“name” : “Gary Murakami”, “location” : “New Providence, NJ”,
“web” : “http://www.nobell.org”
},
“portrait_id” : 1,
“addresses” :
,
“phones” :
,
“emails” :
}
55. Working Set
Per ridurre le dimensioni del working set,considera
• Referenzia i data grandi,e.g.,portrait
• Referenzia i dati usati poco invece di embeddarli
– Estraili in un documento figlio referenziato
57. Migrazione da schemi legacy
1. Copiate lo schema esistente e qualche dato su
mongoDB
2. Iterate lo sviluppo dello schema design
1. Prima le associazioni one to one
2. Poi le associazioni one to many
3. Ed infine le associazioni many to many
3. Migrate l’intero dataset al nuovo schema
L’applicazione è nuova? Embeddate di default
58. Embedding contro Referencing
• Embedding è come fare un pre-join dei dati
– Le operazioni su documenti BSON (Binary JSON) sono facili
per il server
• Embed (90/10 regola del pollo)
– Quando l’uno a molti sono oggetti visti nello stesso
contesto del padre
– Per performance
– Per atomicità
• Reference
– Quando avete bisogno di scalare maggiormente
– Per consistenza nel molti-a-molti evitando di ripetere tanti
dati.
59. E’ Tutto nella Vostra Applicazione
• Programmi + Database = Applicazioni Big Data
• Programmi×MongoDB = Grandi applicazioni Big Data
62. High Volume Data Feeds
• More machine forms, sensors & data
• Variably structured
Machine
Generated Data
• High frequency trading
• Daily closing priceSecurities Data
• Multiple data sources
• Each changes their format consistently
• Student Scores, ISP logs
Social Media /
General Public
63. Operational Intelligence
• Large volume of users
• Very strict latency requirements
• Sentiment Analysis
Ad Targeting
• Expose data to millions of customers
• Reports on large volumes of data
• Reports that update in real time
Real time
dashboards
• Join the conversation
• Catered Games
• Customized Surveys
Social Media
Monitoring
64. Metadata
• Diverse product portfolio
• Complex querying and filtering
• Multi-faceted product attributes
Product
Catalogue
• Data mining
• Call records
• Insurance Claims
Data analysis
• Retina Scans
• FingerprintsBiometric
65. Content Management
• Comments and user generated content
• Personalization of content and layoutNews Site
• Generate layout on the fly
• No need to cache static pages
Multi-device
rendering
• Store large objects
• Simpler modeling of metadataSharing