This document discusses how MongoDB can help enterprises meet modern data and application requirements. It outlines the many new technologies and demands placing pressure on enterprises, including big data, mobile, cloud computing, and more. Traditional databases struggle to meet these new demands due to limitations like rigid schemas and difficulty scaling. MongoDB provides capabilities like dynamic schemas, high performance at scale through horizontal scaling, and low total cost of ownership. The document examines how MongoDB has been successfully used by enterprises for use cases like operational data stores and as an enterprise data service to break down silos.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
How Financial Services Organizations Use MongoDBMongoDB
MongoDB is the alternative that allows you to efficiently create and consume data, rapidly and securely, no matter how it is structured across channels and products, and makes it easy to aggregate data from multiple systems, while lowering TCO and delivering applications faster.
Learn how Financial Services Organizations are Using MongoDB with this presentation.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
How Financial Services Organizations Use MongoDBMongoDB
MongoDB is the alternative that allows you to efficiently create and consume data, rapidly and securely, no matter how it is structured across channels and products, and makes it easy to aggregate data from multiple systems, while lowering TCO and delivering applications faster.
Learn how Financial Services Organizations are Using MongoDB with this presentation.
Slidedeck presented at http://devternity.com/ around MongoDB internals. We review the usage patterns of MongoDB, the different storage engines and persistency models as well has the definition of documents and general data structures.
Webinar: MongoDB Schema Design and Performance ImplicationsMongoDB
In this session, you will learn how to translate one-to-one, one-to-many and many-to-many relationships, and learn how MongoDB's JSON structures, atomic updates and rich indexes can influence your design. We will also explore implications of storage engines, indexing and query patterns, available tools and related new features in MongoDB 3.2.
MongoDB is the most famous and loved NoSQL database. It has many features that are easy to handle when compared to conventional RDBMS. These slides contain the basics of MongoDB.
Presented by Claudius Li, Solutions Architect at MongoDB, at MongoDB Evenings New England 2017.
MongoDB Atlas is the premier database as a service offering. Find out how MongoDB Atlas can help your team to deploy more easily, develop faster and easily manage deployment, maintenance, upgrades and expansions. We will also demonstrate some of the key features and tools that come with MongoDB Atlas.
Find out which is faster, SQL or NoSQL, for traditional reporting tasks. Discover how you can optimise MongoDB aggregation pipelines and how to push complex computation down to the database.
Webinar: An Enterprise Architect’s View of MongoDBMongoDB
In the world of big data, legacy modernization, siloed organizations, empowered customers, and mobile devices, making informed choices about your enterprise infrastructure has become more important than ever. The alternatives are abundant, and the successful Enterprise Architect must constantly discern which new technology is just a shiny object and which will add true business value.
MongoDB is more than just a great application database for developers; it gives Enterprise Architects new capabilities to solve previously difficult architectural requirements much more easily. Take for example the challenge of many siloed systems at MetLife – with MongoDB, the Metlife team was able to successfully provide a single view into those 70 systems, in only 3 months.
In this webinar, we will:
Explore real life challenges enterprises face with case studies of their solutions
Consider how best to introduce MongoDB in the enterprise
Give an overview of how to optimize the use of MongoDB
In the world of big data, legacy modernization, siloed organizations, empowered customers, and mobile devices, making informed choices about your enterprise infrastructure has become more important than ever. The alternatives are abundant, and the successful Enterprise Architect must constantly discern which new technology is just a shiny object and which will add true business value.
Slidedeck presented at http://devternity.com/ around MongoDB internals. We review the usage patterns of MongoDB, the different storage engines and persistency models as well has the definition of documents and general data structures.
Webinar: MongoDB Schema Design and Performance ImplicationsMongoDB
In this session, you will learn how to translate one-to-one, one-to-many and many-to-many relationships, and learn how MongoDB's JSON structures, atomic updates and rich indexes can influence your design. We will also explore implications of storage engines, indexing and query patterns, available tools and related new features in MongoDB 3.2.
MongoDB is the most famous and loved NoSQL database. It has many features that are easy to handle when compared to conventional RDBMS. These slides contain the basics of MongoDB.
Presented by Claudius Li, Solutions Architect at MongoDB, at MongoDB Evenings New England 2017.
MongoDB Atlas is the premier database as a service offering. Find out how MongoDB Atlas can help your team to deploy more easily, develop faster and easily manage deployment, maintenance, upgrades and expansions. We will also demonstrate some of the key features and tools that come with MongoDB Atlas.
Find out which is faster, SQL or NoSQL, for traditional reporting tasks. Discover how you can optimise MongoDB aggregation pipelines and how to push complex computation down to the database.
Webinar: An Enterprise Architect’s View of MongoDBMongoDB
In the world of big data, legacy modernization, siloed organizations, empowered customers, and mobile devices, making informed choices about your enterprise infrastructure has become more important than ever. The alternatives are abundant, and the successful Enterprise Architect must constantly discern which new technology is just a shiny object and which will add true business value.
MongoDB is more than just a great application database for developers; it gives Enterprise Architects new capabilities to solve previously difficult architectural requirements much more easily. Take for example the challenge of many siloed systems at MetLife – with MongoDB, the Metlife team was able to successfully provide a single view into those 70 systems, in only 3 months.
In this webinar, we will:
Explore real life challenges enterprises face with case studies of their solutions
Consider how best to introduce MongoDB in the enterprise
Give an overview of how to optimize the use of MongoDB
In the world of big data, legacy modernization, siloed organizations, empowered customers, and mobile devices, making informed choices about your enterprise infrastructure has become more important than ever. The alternatives are abundant, and the successful Enterprise Architect must constantly discern which new technology is just a shiny object and which will add true business value.
Webinar: How to Drive Business Value in Financial Services with MongoDBMongoDB
Huge upheaval in the finance industry has led to a major strain on existing IT infrastructure and systems. New finance industry regulation has meant increased volume, velocity and variability of data. This coupled with cost pressures from the business has led these institutions to seek alternatives. Top tier institutions like MetLife have turned to MongoDB because of the enormous business value it enables.
In this session, hear how MongoDB enabled these successful real world examples:
Single View of a Customer - 3 months and $2M for a single view of a customer across 50 source systems
Reference Data Management - $40M in cost savings from migrating to MongoDB for reference data management
Private cloud - MongoDB as a PaaS across a tier 1 bank for enabling agility for operations, not just the developer
The use cases are specific to financial services but the patterns of usage - agility, scale, global distribution - will be applicable across many industries.
Webinar: How to Drive Business Value in Financial Services with MongoDBMongoDB
Huge upheaval in the finance industry has led to a major strain on existing IT infrastructure and systems. New finance industry regulation has meant increased volume, velocity and variability of data, so-called Big Data. This coupled with cost pressures from the business has led these institutions to seek alternatives. Top tier institutions like MetLife have turned to MongoDB because of the enormous business value it enables.
In this session, learn where and how you should use MongoDB to get the maximum value including specific case studies such as saving $40M in one project.
The use cases are specific to financial services but the patterns of usage - agility, scale, global distribution - will be applicable across many industries.
Enabling Telco to Build and Run Modern Applications Tugdual Grall
See how new databases like MongoDB enable Telco Enterprises to Build and Run Modern Applications.
This presentations was delivered in Tel Aviv in Jan-2015 during a Telco round table organized by Matrix.
Webinar: How Financial Services Organizations Use MongoDBMongoDB
The finance industry is facing major strain on existing IT infrastructure, systems, and design practices:
New pressures and industry regulation have meant increased volume, consolidation & reconciliation, and variability of data
Mobile and other channels demand significantly more flexible programming and data design environments
Improvements in operational efficiency and cost containment is ever increasing
MongoDB is the alternative that allows you to efficiently create and consume data, rapidly and securely, no matter how it is structured across channels and products and make it easy to aggregate data from multiple systems, while lowering TCO and delivering applications faster.
In this session, we will present on common MongoDB use cases including, but not limited to:
Risk Analytics & Reporting
Tick Data Capture & Analysis
Product Catalogues
Cross-Asset Class Trade Stores
Reference Data Management
Private DBaaS
OPEN'17_4_Postgres: The Centerpiece for Modernising IT InfrastructuresKangaroot
Postgres is the leading open source database management system that is being developed by a very active community for more than 15 years. Gaby Schilders is Sales Engineer at EnterpriseDB, supplier of the EDB Postgres data platform.
Gaby Schilders, Sales Engineer at EnterpriseDB, will be explaining why companies take open source as the centerpiece for modernising their IT infrastructure, thus increasing their scalability and taking full advantage today's technologies offer them.
Transform your DBMS to drive engagement innovation with Big DataAshnikbiz
Erik Baardse and Ajit Gadge from EDB Postgres presented on how to transform your DBMS in order to drive digital business. How Postgres enables you to support a wider range of workloads with your relational database which opens the Big Data doors. They also cover EnterpriseDB’s Strategy around Big Data which focuses on 3 areas and finally last but not the last how to find money in IT with Big Data and digital transformation
What started as a way for web giants to solve problems of serious scale has become the default way all enterprises manage Big Data. Despite having a catchy, if inaccurate title, there really isn't a coherent "NoSQL" category, nor is there a simple future for the range of NoSQL databases. In this presentation, Matt Asay will outline the reasons for NoSQL's existence and persistence, how the different NoSQL technologies help enterprises get control of Big Data, and will identify the trends that point to a bright future for post-relational databases.
Webinar: Expanding Retail Frontiers with MongoDBMongoDB
Twenty-first century retailers are facing an increasingly challenging and competitive environment. Given the rise of ecommerce and pressure on margins, retailers are looking for innovative services as well as ways to improve customer service, loyalty and engagement. Leading organizations in retail are choosing MongoDB because of its ability to help them compete, providing superior customer experience and accelerated time to market. In this webinar, hear how MongoDB enables retailers to develop:
Enriched Product Catalog Management
Distribution and Logistics Management
Solutions Real time Analysis of Customer Behavior
The use cases are specific to retail, but the patterns of usage - agility, scale, and global distribution - will be applicable across many industries.
Webinar: Achieving Customer Centricity and High Margins in Financial Services...MongoDB
It is imperative that Financial Services firms align the organization around providing maximum value to customers across all channels and products with the agility to capitalize on new opportunities. They must do this at the same time as cutting costs, improving operational efficiency, and complying with current and future regulations. This effort is commonly referred to as Industrialization, or streamlining people, process, and technology for maximum customer value, service, and efficiency.
MongoDB can help you in this initiative by allowing you to centralize data management no matter how it is structured across channels and products and make it easy to aggregate data from multiple systems, while lowering TCO and delivering applications faster. MetLife publicly announced that they used MongoDB to enable a single view of the customer in 3 months across 70+ existing systems. We will explore case studies demonstrating these capabilities to help you industrialize your firm.
Key takeaways:
Unique capabilities, brought to you by MongoDB
Concrete use cases that help industrialization
Implementation case studies, to pave the way
According to a recent Harvard Business Review study, there’s only a 43% chance that customers who have a poor experience will stick with you for the next 12 months. Contrast that to the 74% that will remain your customer if they have a great experience. Learn how Macy’s, a leading American department store chain founded in 1858 with over 750 stores in North America, is transforming their customer experience with DataStax Enterprise.
Webinar recording: https://youtu.be/CiUVxh6Ov_E
View current and past DataStax webinars: http://www.datastax.com/resources/webinars
Similar to An Enterprise Architect's View of MongoDB (20)
MongoDB SoCal 2020: Migrate Anything* to MongoDB AtlasMongoDB
During this talk we'll navigate through a customer's journey as they migrate an existing MongoDB deployment to MongoDB Atlas. While the migration itself can be as simple as a few clicks, the prep/post effort requires due diligence to ensure a smooth transfer. We'll cover these steps in detail and provide best practices. In addition, we’ll provide an overview of what to consider when migrating other cloud data stores, traditional databases and MongoDB imitations to MongoDB Atlas.
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
Query performance should be the unsung hero of an application, but without proper configuration, can become a constant headache. When used properly, MongoDB provides extremely powerful querying capabilities. In this session, we'll discuss concepts like equality, sort, range, managing query predicates versus sequential predicates, and best practices to building multikey indexes.
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
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 .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.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
An Enterprise Architect's View of MongoDB
1. An Enterprise Architect’s View of
MongoDB
Matt Kalan
Business Architect
matt.kalan@mongodb.com
@matthewkalan
2. Agenda
• Modern drivers of change on enterprises
• Requirements these create
• How traditional databases are handling changes
• New capabilities needed
• How MongoDB provides these capabilities
• Case studies
• Enterprise adoption
2
4. More Technologies and Requirements
Than Ever
NoSQL
Datawarehouse
Hadoop
Internet of Things
4
Document Data Stores
Big Data
Key-value
JSON
Wide-column
MongoDB
Cloud Computing
Mobile
Gamification
Social networking
Graph
Agile Development
ODS
Analytics
Consumerization
5. More Technologies and Requirements
Than Ever
NoSQL
Datawarehouse
Hadoop
Internet of Things
5
Document Data Stores
Big Data
Key-value
JSON
Wide-column
MongoDB
Cloud Computing
Mobile
Gamification
Social networking
Graph
Agile Development
ODS
Analytics
Consumerization
Opportunity cost
Globalization
Customer 360
Cross-channel
New Revenue Streams
Faster Competition
Emerging markets
Regulation
Data Monetization
More with less
Common Services
Empowered customers
Lowering TCO
6. Questions for Enterprise Architects
• What current and future requirements does all
6
this raise?
• How to prepare my enterprise to handle these?
• Which technologies and products will help me?
• How to bring them into my enterprise
successfully?
• How does old and new technology work together?
• What does the future state architecture look like?
7. Modern Application Requirements
Data Types & OOP
• Object-oriented
• Variably structured
• Unstructured (not tabular)
7
Volume of Data
• Petabytes of data
• Trillions of records
• Millions of queries per
second
Agile Development
• Iterative
• Short development
cycles
• Fast time-to-market
New Architectures
• Horizontal scaling
• Commodity
servers
• Cloud computing
RDBMS
Single Views
• Disparate data
• Intraday
• Cross-channel/silo
• Global
8. Modern Application Requirements
Data Types & OOP
• Object-oriented
• Variably structured
• Unstructured (not tabular)
8
Volume of Data
• Petabytes of data
• Trillions of records
• Millions of queries per
second
Agile Development
• Iterative
• Short development
cycles
• Fast time-to-market
New Architectures
• Horizontal scaling
• Commodity
servers
• Cloud computing
RDBMS
Single Views
• Disparate data
• Intraday
• Cross-channel/silo
• Global
9. Impact of New Requirements Handled
with 40-year old Technology
• Customfield1…100 or separate tables
• Caching & ORMs
• Expensive hardware and storage
• Schema migration project
• One canonical schema
• Application-specific partitioning
• Use files instead of databases
• Schema change takes 6 months
9
10. Impact of New Requirements Handled
with 40-year old Technology
• Customfield1…100 or separate tables
• Caching & ORMs
• Expensive hardware and storage
• Schema migration project
• One canonical schema
• Application-specific partitioning
• Use files instead of databases
• Schema change takes 6 months
10
Slow time-to-market
Agility lost
High cost
Failed projects
Business frustrated
11.
12. How Do I Prepare My Enterprise
for Modern Requirements?
13. What would we need to make it
easier?
13
New capabilities
• Dynamic and variable
schemas
• Richly-structured [object]
data
• Higher performance
• Easy horizontal scaling
• Low TCO
14. What would we need to make it
easier?
• Dynamic and variable
schemas
• Richly-structured [object]
data
14
New capabilities
• Higher performance
• Easy horizontal scaling
• Low TCO
Traditional capabilities
• Rich querying
• Strongly consistently data
• High availability
• Security
15. Documents Support Modern
Requirements
15
Relational Document Data Structure
{ customer_id : 1,
first_name : "Mark",
last_name : "Smith",
city : "San Francisco",
location : [40.74, -73.97],
image : <binary>,
phones: [ {
number : “1-212-777-1212”,
dnc : true,
type : “home”
},
{
number : “1-212-777-1213”,
type : “cell”
}]
}
19. No SQL But Still Flexible Querying
19
MongoDB
Rich Queries
• Find anyone with phone # “212…”
• Check if the person with number
“555…” is on the “do not call” list
Geospatial
• Find the best offer for the customer at
geo coordinates of 42nd St. and 6th Ave
Text Search
• Find all tweets that mention the firm
within the last 2 days
Aggregation
• Count and sort number of customers by
city
Map Reduce
• For customers in each zip code, what
are the top 5 most common products
{ customer_id : 1,
first_name : "Mark",
last_name : "Smith",
city : ”New York",
phones: [ {
number : “1-212-777-1212”,
dnc : true,
type : “home”
},
{
number : “1-212-777-1213”,
type : “cell”
}]
}
20. Security Capabilities
• Kerberos
• LDAP
• x.509 certificates
20
• User-Defined Roles
• Field Level Security
• Admin Actions
• CRUD operations
• Partner support
• SSL support on wire
• Disk encryption
support by partners
21. Global Deployment with Local
Read/Writes
21
Primary:NYC
Primary:LON
Secondary:NYC
Primary:SYD
Secondary:LON
Secondary:NYC
Secondary:SYD
Secondary:LON
Secondary:SYD
22. MongoDB Business Value
22
Faster Time to Market Lower TCO
Enabling New Apps Faster Response Time
& Scalability
26. MongoDB Hadoop Connector
26
Operational
Database
• Low latency
• Rich fast querying
• Flexible indexing
• Aggregations in database
• Known data relationships
• Great for any subset of data
Analytics
• Longer jobs
• Batch analytics
• Highly parallel processing
• Unknown data relationships
• Great for looking at all data
MongoDB-Hadoop
Connector
33. Architecture Patterns
1. Operational Data Store (ODS)
2. Enterprise Data Service
3. Datamart/Cache
4. Master Data Distribution
5. Single Operational View
33
34. Architecture Patterns
1. Operational Data Store (ODS)
2. Enterprise Data Service
3. Datamart/Cache
4. Master Data Distribution
5. Single Operational View
34
System of Record
System of Engagement
38. Criteria for benefitting most from
MongoDB instead of RDBMS
Data
Variably or
unstructured
Hierarchical
Geo-coordinates
Disparate sources
Schema changes
often
38
Querying
Real-time analytics &
aggregations
Location-based
Lowest latency
Performance affects
user experience
Requirements
Agile development &
fastest time-to-market
Data will grow quickly
Best performance for
request/response
Lowest TCO
Multiple sources
aggregated
Challenges today with
RDBMS
39. ADP’s Global Mobile Platform
One of the world's largest providers of payments solutions
constructs a completely reliable and robust mobile
experience
39
Problem Why MongoDB Results
• Needed a signature
mobile app for customers
• Must support millions of
users
• Needed to quickly change
features & functionality
• High availability was
critically important
• Built-in high availability
architecture optimized for
global, multi-data center
distribution
• Dynamic schema & rich
querying – deep
functionality from launch &
new features easily added
• Much lower TCO,
especially with commodity
hardware
• iTunes App Store “Top 15”
business app since 2012
launch
• Over 1 million active users, 17
countries, 23 languages
• Extremely high performance
through predictive caching
• Maintenance much easier =>
simple codebase, less
hardware
• New functionality easy and
quick to add
41. Challenge: Siloed operational
applications
41
Silo 1 Data
Silo 2 Data
…
Silo N Data
Impact
• Views are siloed
• Duplicate management
and data access layer
• Need another layer to
aggregate
Silo 1 systems
Silo 2 Systems
…
Silo N
Systems
Reporting Reporting Reporting
42. Solution: Unified data services
42
…
Benefit
• Each application can still
save its own data
• Data is already aggregated
for cross-silo reporting
• One cluster and data access
layer to manage
Silo 1 Systems
Silo 2 Systems
…
Silo N Systems
Reporting
……
43. Case Study: Global Broker Dealer
Trade Mart for all OTC Trades
Distribute reference data globally in real-time for
fast local accessing and querying
43
Problem Why MongoDB Results
• Each application had its
own persistence and
audit trail
• Wanted one unified
framework and
persistence for all
trades and products
• Needed to handle many
variable structures
across all securities
• Dynamic schema: can
save trade for all products
in one data service
• Easy scaling: can easily
keep trades as long as
required with high
performance
• Rich querying: can query
on any fields each
business requires
• Fast time-to-market using
the persistence framework
• Store any structure of
products/trades without
changing a schema
• One consolidated trade
store for auditing and
reporting
45. Challenge: Response From Data
Warehouse or Other System is Slow
45
Cards
Loans
…
Deposits
Data
Warehouse
Issues
• Data stored normalized
• Reports slow to generate
• Data updated daily but user
response must be fast
Impact
• Lost productivity
• Dissatisfied users and
business
Reporting
Cards
Silo 1
Loans
Silo 2
Deposits
Silo 3
46. Solution: Optimize Data Structure as a
Datamart In-memory or On-disk
Cards
Loans
Deposits
46
…
Data
Warehouse
Solution
• Data stored in optimal
structure for reports
• Optionally in memory
Impact
• Response times is as fast
as possible
• Users and business
satisfied
Fast Reporting
Cards
Silo 1
Loans
Silo 2
Deposits
Silo 3
Datamart/Cache
…
47. Case Study: Global Bank -
Personalized In-memory Datamart
Needed fast reporting for finance on global
banking transaction data (about 2 petabytes)
47
Problem Why MongoDB Results
• Data warehouse was
too slow for reporting
• No visibility into how
long reports took
• Could not generate
multiple ad hoc reports
• Users included
regulators so even
more demanding
• Dynamic schema: store
data in optimal structure
• Performance: storing
report results optimally
• In-memory caching of
results
• Rich querying: can query
on any field
• Easy scaling: results
spread across shards to
generate report in parallel
• Create a personalized in-memory
data mart
• Reports configured and
notified when results ready
• Data all in memory so fast
to manipulate
• Data spread across shards
for ultra-fast reporting
49. Challenge: Master data can be hard
to change and distribute
49
Golden
Copy
Batch
Batch
Batch
Batch
Batch
Batch
Batch
Batch
Common issues
• Hard to change schema
of master data
• Data copied everywhere
and gets out of sync
Impact
• Process breaks from out
of sync data
• Business doesn’t have
data it needs
• Many copies creates
more management
50. Solution: Persistent dynamic cache
replicated globally
50
Real-time
Real-time Real-time
Real-time
Real-time
Real-time
Real-time
Real-time
Solution:
• Load into primary with
any schema
• Replicate to and read
from secondaries
Benefits
• Easy & fast change at
speed of business
• Easy scale out for one
stop shop for data
• Low TCO
51. Case Study: Global bank
Reference Data Distribution
Distribute reference data globally in real-time for
fast local accessing and querying
51
Problem Why MongoDB Results
• Delays up to 36 hours in
distributing data by batch
• Charged multiple times
globally for same data
• Incurring regulatory
penalties from missing
SLAs
• Had to manage 20
distributed systems with
same data
• Dynamic schema: easy to
load initially & over time
• Auto-replication: data
distributed in real-time,
read locally
• Both cache and database:
cache always up-to-date
• Simple data modeling &
analysis: easy changes
and understanding
• Will save about
$40,000,000 in costs and
penalties over 5 years
• Only charged once for data
• Data in sync globally and
read locally
• Capacity to move to one
global shared data service
55. Case Study
Insurance leader generates coveted 360-degree view of
customers in 90 days – “The Wall”
55
Problem Why MongoDB Results
• No single view of
customer
• 145 yrs of policy data,
70+ systems, 15+ apps
• 2 years, $25M in failing
to aggregate in RDBMS
• Poor customer
experience
• Agility – prototype in 5
days; production in 90
days
• Dynamic schema:
Imperative to combine
disparate data
• Rich querying: necessary
for match data across silos
• Hot tech to attract top
talent
• Unified customer view
available to all channels
• Increased call center
productivity
• Better customer
experience, reduced
churn, more upsell opps
• Dozens more projects
on same data platform
56. Single [Operational] View of ….
Cards
Silo 1
Loans
Silo 2
56
Operational
Reporting
Real-time
or Batch
…
Single CSR
Application
Unified
Customer Portal
Operational Data Layer
Cards
Loans
…
Deposits
Deposits
Silo N
Strategic
Reporting
…
• Millisecond latency
• Request/response
• Easily scalable
• Flexible schema
• Low TCO
• Rich querying
• Globally distributed
DW/Analytic Data Layer
• Analytical/Offline processing
• 10s seconds to hours latency
• Also scalable, low TCO, and
flexible
• Pre-defined slices of data
(few indexes)
Analytics/Batch
processing
MongoDB
Hadoop Connector
…
57. Processing + Data Access Paradigm
Processing
model
Data access
model
57
Request/response
Map-reduce
Batch, ETL, etc.
Analytical Jobs
Latency important (e.g.
user waiting)
Milliseconds to seconds
Small to large subsets
of data
Indexes valuable
Multiple seconds to hours
Processing all or large sets
of data
Indexes not used
58. Processing + Data Access Paradigm
Processing
model
Data access
model
58
Request/response
Map-reduce
Batch, ETL, etc.
Analytical Jobs
Latency important (e.g.
user waiting)
Milliseconds to seconds
Small to large subsets
of data
Indexes valuable
Multiple seconds to hours
Processing all or large sets
of data
Indexes not used
Typical MongoDB
Use Case
59. Processing + Data Access Paradigm
Processing
model
Data access
model
59
Request/response
Map-reduce
Batch, ETL, etc.
Analytical Jobs
Latency important (e.g.
user waiting)
Milliseconds to seconds
Small to large subsets
of data
Indexes valuable
Multiple seconds to hours
Processing all or large sets
of data
Indexes not used
Typical MongoDB
Use Case
Typical Hadoop
Use Case
60. Processing + Data Access Paradigm
Processing
model
Data access
model
60
Request/response
Map-reduce
Batch, ETL, etc.
Analytical Jobs
Latency important (e.g.
user waiting)
Milliseconds to seconds
Small to large subsets
of data
Indexes valuable
Multiple seconds to hours
Processing all or large sets
of data
Indexes not used
Typical MongoDB
Use Case
Typical Hadoop
Use Case
61. Processing + Data Access Paradigm
Processing
model
Data access
model
61
Request/response
Map-reduce
Batch, ETL, etc.
Analytical Jobs
Latency important (e.g.
user waiting)
Milliseconds to seconds
Small to large subsets
of data
Indexes valuable
Multiple seconds to hours
Processing all or large sets
of data
Indexes not used
Typical MongoDB
Use Case
Typical Hadoop
Use Case
Data
Discovery
63. Example Adoption Path
Use of MongoDB
63
One Project
MongoDB CoE
A Few Projects
Certified
Widespread
Adoption
Operationally
Supported
Time
Defined
64. Traditional Data Integrity Enforcement
64
RDBMS
• Apps access DB directly
• Data Integrity must be in the RDBMS
• Schema implemented by a DBA
Application 1
Application 2
Application 3
65. Modern Apps (SOA) - Data Access
Layer Should Enforce Data Integrity
Application 1
65
MongoDB Cluster
Application 2
• Data Integrity and validations done in
• Implemented in code
Data
Access
Layer
…
Application N
…
Data Access Layer
REST/API/WS API on TCP/IP
66. Data Governance Benefits
• Greater adoption from natural developer
66
framework on common data models
• Easier for master data or upstream changes to
flow into MongoDB-backed apps
• MongoDB useful for distributing master data
• ETL providers support MongoDB most in NoSQL
68. Factors to Consider in Adoption
• SDLC and data governance for an application
• Enterprise-wide data governance (inter-app)
• Enterprise-wide security
• Roles and responsibilities
• Training requirements
• Operations/production support
• Center of Excellence (COE)
• Process for choosing which DB to use
• How to work with other technologies in-house
68
69. Recommended Center of Excellence
69
Database Engineering & CoE
Operational Database CoE
Datawarehousing CoE
70. Recommended Center of Excellence
70
Database Engineering & CoE
Database
Advisory
Services
Operational Database CoE
Datawarehousing CoE
71. Recommended Center of Excellence
71
RDBMS
Engineering
Database Engineering & CoE
Database
Advisory
Services
Operational Database CoE
Datawarehousing CoE
77. Summary
• Enormous technology and business change today
• Old technologies not suited for many of them
• MongoDB is purpose built for today and future applications
• And can help solve common architectural challenges
• Bring MongoDB, Inc. in to learn how to adopt it more widely
77
when appropriate
• Firms using MongoDB benefit from 50% time-to-market,
70% lower TCO, lower operating costs, and making the
infeasible possible
79. For More Information
79
Resource Location
Resource Location
MongoDB Downloads mongodb.com/download
Free Online Training university.mongodb.com
Webinars and Events mongodb.com/events
White Papers mongodb.com/white-papers
Case Studies mongodb.com/customers
Presentations mongodb.com/presentations
Documentation docs.mongodb.org
Additional Info info@mongodb.com
Editor's Notes
Here’s a relational model for an application. It has hundreds of tables.
If you are the new developer who just joined the team, congratulations!!
Here’s a map of the database, now go figure out how to add your new feature (or fix a bug).
Good luck!
Point out what other NoSQL databases have (not rich querying and strong consistency)
Point out what other NoSQL databases have (not rich querying and strong consistency)
One of the main reasons is the data model.
Documents are just easier.
If my app tracks car collections, I don’t need to know dozens of tables – all the data for an individual and their collection is in one document. (Walk through this example)
Dynamic schema
Single view of a customer
Single view of a customer
Compared to distributed cache - $ and fixed schema
Single view of a customer
Can store all accounts in one table
Have performance capacity and easy scaling to to do real-time, not just batch
Can store all accounts in one table
Have performance capacity and easy scaling to to do real-time, not just batch
Single view of a customer
In terms of reporting, A number of Business Intelligence (BI) vendors have developed connectors to integrate MongoDB as a data source with their suites, alongside traditional relational dbs. This integration provides reporting, visualizations, dash-boarding of MongoDB data