Beyond the Basics 3: Introduction to the MongoDB BI ConnectorMongoDB
Watch this presentation to learn how the MongoDB BI Connector lets you use MongoDB as a data source for your SQL-based BI and analytics platforms.
Learn how to seamlessly create the visualizations and dashboards that will help you extract the insights and hidden value in your multi-structured data.
MongoDB is one of the most popular NoSQL databases written in C++. In 2015, MongoDB was found as the fourth most popular database management system. It was developed by the company 10gen which is now named as MongoDB Inc.
MongoDB is a document-oriented database that stores data in JSON-like documents that can vary in structure. It implies that you can store your records without bothering about the data structure such as the number of fields or types of fields to store values. MongoDB documents are related to JSON objects.
Beyond the Basics 3: Introduction to the MongoDB BI ConnectorMongoDB
Watch this presentation to learn how the MongoDB BI Connector lets you use MongoDB as a data source for your SQL-based BI and analytics platforms.
Learn how to seamlessly create the visualizations and dashboards that will help you extract the insights and hidden value in your multi-structured data.
MongoDB is one of the most popular NoSQL databases written in C++. In 2015, MongoDB was found as the fourth most popular database management system. It was developed by the company 10gen which is now named as MongoDB Inc.
MongoDB is a document-oriented database that stores data in JSON-like documents that can vary in structure. It implies that you can store your records without bothering about the data structure such as the number of fields or types of fields to store values. MongoDB documents are related to JSON objects.
Build robust streaming data pipelines with MongoDB and Kafka P2Ashnikbiz
Kafka is an event streaming solution designed for boundless streams of data that sequentially write events into commit logs, allowing real-time data movement between your services. The MongoDB database is built for handling massive volumes of heterogeneous data. Together MongoDB and Kafka make up the heart of many modern data architectures today.
Database plays a critical role in event-driven architectures. While events flow through Kafka in an append-only stream, MongoDB helps the consumer to proactively make streams of data from the source systems available in real time.
The MongoDB Connector for Kafka simplifies building a robust, streaming event pipeline.
Business Jumpstart: The Right (and Wrong) Use Cases for MongoDBMongoDB
New to MongoDB? This talk will cover when to use MongoDB and how to evaluate if MongoDB is a fit for your project. You will see how MongoDB's flexible document model is solving business problems in ways that were not previously possible, and how MongoDB's built-in features allow running at scale. No prior knowledge of MongoDB is assumed.
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.
Introductory talk to how can MongoDB enable new age software taking into account the expected growth rates, the constant availability of services and new business models that appear on a daily basis.
Real World MongoDB: Use Cases from Financial Services by Daniel RobertsMongoDB
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. In this session learn how FS companies are using MongoDB to solve their problems. The use cases are specific to FS but the patterns of usage - agility, scale, global distribution - will be applicable across many industries.
Using semi-structured data in modern applicationsMariaDB plc
JSON is the de facto standard for consuming and producing data from web, mobile and IoT apps, but relational databases are required for reliability – enforcing data integrity and providing durability with transactions. They're not mutually exclusive. MariaDB TX introduced SQL functions for validating, indexing and querying JSON documents – and for returning relational data as JSON documents, or JSON documents as relational data. In this session you will learn how to read, write, index and query semi-structured/non-traditional data with hands-on examples.
Webinar: How Banks Use MongoDB as a Tick DatabaseMongoDB
Learn why MongoDB is spreading like wildfire across capital markets (and really every industry) and then focus in particular on how financial firms are enjoying the developer productivity, low TCO, and unlimited scale of MongoDB as a tick database for capturing, analyzing, and taking advantage of opportunities in tick data. This webinar illustrates how MongoDB can easily and quickly store variable data formats, like top and depth of book, multiple asset classes, and even news and social networking feeds. It will explore aggregating and analyzing tick data in real-time for automated trading or in batch for research and analysis and how auto-sharding enables MongoDB to scale with commodity hardware to satisfy unlimited storage and performance requirements.
Build robust streaming data pipelines with MongoDB and Kafka P2Ashnikbiz
Kafka is an event streaming solution designed for boundless streams of data that sequentially write events into commit logs, allowing real-time data movement between your services. The MongoDB database is built for handling massive volumes of heterogeneous data. Together MongoDB and Kafka make up the heart of many modern data architectures today.
Database plays a critical role in event-driven architectures. While events flow through Kafka in an append-only stream, MongoDB helps the consumer to proactively make streams of data from the source systems available in real time.
The MongoDB Connector for Kafka simplifies building a robust, streaming event pipeline.
Business Jumpstart: The Right (and Wrong) Use Cases for MongoDBMongoDB
New to MongoDB? This talk will cover when to use MongoDB and how to evaluate if MongoDB is a fit for your project. You will see how MongoDB's flexible document model is solving business problems in ways that were not previously possible, and how MongoDB's built-in features allow running at scale. No prior knowledge of MongoDB is assumed.
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.
Introductory talk to how can MongoDB enable new age software taking into account the expected growth rates, the constant availability of services and new business models that appear on a daily basis.
Real World MongoDB: Use Cases from Financial Services by Daniel RobertsMongoDB
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. In this session learn how FS companies are using MongoDB to solve their problems. The use cases are specific to FS but the patterns of usage - agility, scale, global distribution - will be applicable across many industries.
Using semi-structured data in modern applicationsMariaDB plc
JSON is the de facto standard for consuming and producing data from web, mobile and IoT apps, but relational databases are required for reliability – enforcing data integrity and providing durability with transactions. They're not mutually exclusive. MariaDB TX introduced SQL functions for validating, indexing and querying JSON documents – and for returning relational data as JSON documents, or JSON documents as relational data. In this session you will learn how to read, write, index and query semi-structured/non-traditional data with hands-on examples.
Webinar: How Banks Use MongoDB as a Tick DatabaseMongoDB
Learn why MongoDB is spreading like wildfire across capital markets (and really every industry) and then focus in particular on how financial firms are enjoying the developer productivity, low TCO, and unlimited scale of MongoDB as a tick database for capturing, analyzing, and taking advantage of opportunities in tick data. This webinar illustrates how MongoDB can easily and quickly store variable data formats, like top and depth of book, multiple asset classes, and even news and social networking feeds. It will explore aggregating and analyzing tick data in real-time for automated trading or in batch for research and analysis and how auto-sharding enables MongoDB to scale with commodity hardware to satisfy unlimited storage and performance requirements.
Hola Amigos , Este documento porta la información acerca de como se utiliza la criptografía -Gestión de seguridad para redes .
Realizado por : Abel Duque
Note de cadrage juridique : les enjeux de la sécurisation du foncier irrigué
Communication de Moussa Djire, expert foncier, consultant ROPPA et GWI, lors de l'atelier régional « Sécurisation foncière des exploitations familiales dans les grands périmètres irrigués d'Afrique de l'Ouest - Apprendre des expériences du Burkina Faso, Mali et Niger », qui s'est tenu à Ouagadougou du 17 au 19 juin 2016.
L'atelier était co-organisé par le Réseau des organisations paysannes et de producteurs de l’Afrique de l’Ouest (ROPPA) et la Global Water Initiative (GWI) en Afrique de l’Ouest – mise en œuvre par le consortium formé par l’Union internationale pour la conservation de la nature (UICN) et l’Institut international pour l’environnement et le développement (IIED), et financée par la Fondation Howard G. Buffett.
Communication sur les avantages et inconvénients rencontrés dans les démarches de sécurisation foncière dans la vallée du Sourou
Communication de Césaire Tiama, président de l'Union des producteurs de riz de la vallée du Sourou (UPRVS), lors de l'atelier régional « Sécurisation foncière des exploitations familiales dans les grands périmètres irrigués d'Afrique de l'Ouest - Apprendre des expériences du Burkina Faso, Mali et Niger », qui s'est tenu à Ouagadougou du 17 au 19 juin 2016.
L'atelier était co-organisé par le Réseau des organisations paysannes et de producteurs de l’Afrique de l’Ouest (ROPPA) et la Global Water Initiative (GWI) en Afrique de l’Ouest – mise en œuvre par le consortium formé par l’Union internationale pour la conservation de la nature (UICN) et l’Institut international pour l’environnement et le développement (IIED), et financée par la Fondation Howard G. Buffett.
Learn MongoDB online at Easylearning.guru. We offer instructor led online training and Life Time LMS (Learning Management System) Access. Join Our Free Live Demo Classes of MongoDB.
Jumpstart your day with an introduction to MongoDB by building a simple web app with React, Atlas, and Stitch. First, we will cover the foundations of schema design, security, queries and indexing. Then we'll partially refactor an application using the MERN stack to a serverless application using MongoDB Stitch.
Everything You Need to Know About MongoDB Development.pptx75waytechnologies
Today, organizations from different verticals want to harness the power of data to grab new business opportunities and touch new heights of success. Such an urge leads them to follow unique ways to use and handle data effectively. After all, the right use of data boosts the ability to make business decisions faster. But at the same time, working with data is not as easy as a walk in the garden. It sometimes turns out to be a long-standing problem for businesses that also affects their overall functioning.
Companies expect fast phase development and better data management in every scenario. Modern web-based applications development demands a quality working system that can be deployed faster, and the application is able to scale in the future as per the constantly changing environment.
Earlier, relational databases were used as a primary data store for web application development. But today, developers show a high interest in adopting alternative data stores for modern applications such as NoSQL (Not Only Structured Query Language) because of its incredible benefits. And if you ask us, one of the technologies that can do wonders in modern web-based application development is MongoDB.
MongoDB is the first name strike in our heads when developing scalable applications with evolving data schemas. Because MongoDB is a document database, it makes it easier for developers to store both structured and unstructured data. Stores and handles large amounts of data quickly, MongoDB is undoubtedly the smart move toward building scalable and data-driven applications. If you’re wondering what MongoDB is and how it can help your digital success, this blog is surely for you.
This paper trying to focus on main features, advantages and applications of non-relational database namely Mongo DB and thus justifying why MongoDB is more suitable than relational databases in big data applications. The database used here for comparison with MongoDB is MySQL. The main features of MongoDB are flexibility, scalability, auto sharding and replication. MongoDB is used in big data and real time web applications since it is a leading database technology.
Basic of Mongodb With the description of NoSQl database and its features about colleactions and documents.Its advantages and disadvantages.Why to use MongoDB.Difference between RDBMS and MongoDB.Installation process of MongoDB.Varoius BSON Types.Keypoints Of MongoDB.
Keywords:NOSQL,BSON Types,Replication,Sharding,Aggregations,ObjectId and various others.
1> Why Choose NoSQL
2> MongoDB -NoSQL Database
3> MongoDB BioGraphy
4> RDBMS VS MongoDB
5> Query Language in MYSQL Vs MongoDB
6> Key Features
7> MongoDB Basics
8> MongoDB Collections
9> MongoDB Aggregations
10> Aggregation Pipeline
11> Single Purpose Aggregation Operations
12> MongoDB Replication
13> Sharding in MongoDB
14> Pros / Cons Of MongoDB
15> Why should use MongoDB
17> Where should use MongoDB?
Conclusion:MongoDB database is used to store big data.It gives high performance and scalability features which makes advanced in terms of SQL database
MongoDB is a document – Oriented , No Sequel (NoSQL) Database.
MongoDB is a document database with the Scalability and Flexibility.
It is a distributed database built for Modern Application Developers.
It store data in BSON.
NOSQL WHY?
It’s a non-relational, document-oriented database management system and works on document-based database.
MongoDB stores data in form of documents.
MongoDB uses BSON to Query database.
What is BSON :
Bson Stands for binary JSON.
It containing a field name , type ,and value.
The BSON type format is lightweight, highly traversable and fast in nature.
Characteristics:
Replication
Sharding
Schema less
MongoDB.local Sydney: An Introduction to Document Databases with MongoDBMongoDB
This presentation will describe MongoDB's document database and what advantages it has over traditional databases. The presentation will explore MongoDB's server, query language, ecosystem and various tools. Brett will demonstrate using various MongoDB tools to assist in developing a Python application that utilises MongoDB as the database.
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.
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/
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.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
7. Document Database
A record in MongoDB is a document which is a data structure composed of field and
value pairs.
MongoDB documents are similar to JSON objects.
MongoDB internally stores the data as BSON (binary JSON)
The values of fields may include other documents, arrays, and arrays of documents.
8. What is JSON?
JSON stands for JavaScript Object Notation
Characteristics:
Lightweight data-interchange format
Easy for humans to read and write
Easy for machines to parse and generate
11. Document model benefits
Agility and flexibility:
Data model supports business change
Rapidly iterate to meet new requirements
Dynamic schema supports fluent polymorphism.
12. Document model benefits
Intuitive, natural data representation
Eliminate ORM layer
Developers are more productives
Documents (i.e. objects) correspond to native data types in many
programming languages.
13. Document model benefits
Reduces the need for joins, disk seeks
Embedded documents and arrays reduce need for expensive joins.
Programming is simpler
No foreign keys