The document discusses alternatives to limited scale in data solutions. It describes how IBM has been a leader in big data for years and shows examples of C# integration with Hadoop and Hive. It also demonstrates provisioning, executing, and deprovisioning frameworks and tools for connecting to MongoDB from .NET projects using official wrappers or alternative tools. The document contains code examples and asserts the results of queries.
Design Patterns in Micro-services architectures & GilmourPiyush Verma
Gilmour is a framework for writing micro-services that exchange data over non-http transports. Talk looks at Design Patterns of a service oriented architecture, like Request-Response, Signal-Slots, Service Discovery, Load Balancing, Error detection and how Gilmour addresses those.
MongoDB - Back to Basics - La tua prima ApplicazioneMassimo Brignoli
Eccoci alla seconda puntata della serie Back to Basics edizione 2017. Vedremo come sviluppare un'applicazione con MongoDB studiando come interagire con la base dati. Vedremo come fare le query, creare un indice e studiarne il piano di esecuzione
This presentation is showing how to use the Aggregation Framework, the powerful aggregation language of MongoDB. Using some real data coming from the USA Census, we will discover the most important operations.
Just a few years ago all software systems were designed to be monoliths running on a single big and powerful machine. But nowadays most companies desire to scale out instead of scaling up, because it is much easier to buy or rent a large cluster of commodity hardware then to get a single machine that is powerful enough. In the database area scaling out is realized by utilizing a combination of polyglot persistence and sharding of data. On the application level scaling out is realized by microservices. In this talk I will briefly introduce the concepts and ideas of microservices and discuss their benefits and drawbacks. Afterwards I will focus on the point of intersection of a microservice based application talking to one or many NoSQL databases. We will try and find answers to these questions: Are the differences to a monolithic application? How to scale the whole system properly? What about polyglot persistence? Is there a data-centric way to split microservices?
MongoDB Europe 2016 - Advanced MongoDB Aggregation PipelinesMongoDB
We will do a deep dive into the powerful query capabilities of MongoDB's Aggregation Framework, and show you how you can use MongoDB's built-in features to inspect the execution and tune the performance of your queries. And, last but not least, we will also give you a brief outlook into MongoDB 3.4's awesome new Aggregation Framework additions.
MongoDB .local Munich 2019: Best Practices for Working with IoT and Time-seri...MongoDB
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.
Design Patterns in Micro-services architectures & GilmourPiyush Verma
Gilmour is a framework for writing micro-services that exchange data over non-http transports. Talk looks at Design Patterns of a service oriented architecture, like Request-Response, Signal-Slots, Service Discovery, Load Balancing, Error detection and how Gilmour addresses those.
MongoDB - Back to Basics - La tua prima ApplicazioneMassimo Brignoli
Eccoci alla seconda puntata della serie Back to Basics edizione 2017. Vedremo come sviluppare un'applicazione con MongoDB studiando come interagire con la base dati. Vedremo come fare le query, creare un indice e studiarne il piano di esecuzione
This presentation is showing how to use the Aggregation Framework, the powerful aggregation language of MongoDB. Using some real data coming from the USA Census, we will discover the most important operations.
Just a few years ago all software systems were designed to be monoliths running on a single big and powerful machine. But nowadays most companies desire to scale out instead of scaling up, because it is much easier to buy or rent a large cluster of commodity hardware then to get a single machine that is powerful enough. In the database area scaling out is realized by utilizing a combination of polyglot persistence and sharding of data. On the application level scaling out is realized by microservices. In this talk I will briefly introduce the concepts and ideas of microservices and discuss their benefits and drawbacks. Afterwards I will focus on the point of intersection of a microservice based application talking to one or many NoSQL databases. We will try and find answers to these questions: Are the differences to a monolithic application? How to scale the whole system properly? What about polyglot persistence? Is there a data-centric way to split microservices?
MongoDB Europe 2016 - Advanced MongoDB Aggregation PipelinesMongoDB
We will do a deep dive into the powerful query capabilities of MongoDB's Aggregation Framework, and show you how you can use MongoDB's built-in features to inspect the execution and tune the performance of your queries. And, last but not least, we will also give you a brief outlook into MongoDB 3.4's awesome new Aggregation Framework additions.
MongoDB .local Munich 2019: Best Practices for Working with IoT and Time-seri...MongoDB
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.
Big Data otimizado: Arquiteturas eficientes para construção de Pipelines MapR...Tail Target
Limpar, agregar, analisar, transformar: aplicações de data science no mundo real em geral envolvem a execução de diversas etapas de processamento, cada uma adicionando mais valor aos seus dados. Arquitetar e orquestrar estes pipelines de forma eficiente é uma tarefa que exige uma boa dose de conhecimento sobre o funcionamento interno de algoritmos de MapReduce e alguns truques que você só aprende depois de processar vários terabytes. Esta palestra irá mostrar como arquitetar MapReduce Pipelines eficientes usando o framework Apache Crunch, como integrar seus pipelines com fontes de dados externas como Redis, MongoDB ou mesmo bancos de dados relacionais, qual a melhor granularidade para seus jobs e quando investir em uma arquitetura de MapReduce realmente faz sentido.
Palestra apresentada por Fabiane Bizinella Nardon no QConSP 2013.
MongoDB natively supports geospatial indexing and querying, and it integrates easily with open source visualization tools. In this webinar, learn high-performance techniques for querying and retrieving geospatial data, and how to create a rich visual representation of global weather data using Python, Monary, and Matplotlib.
The weather is everywhere and always. That makes for a lot of data. This talk will walk you through how you can use MongoDB to store and analyze worldwide weather data from the entire 20th century in a graphical application. We’ll discuss loading and indexing terabytes of data in a sharded cluster, and optimizing the schema design for interactive exploration. MongoDB also natively supports geospatial indexing and querying, and it integrates easily with open source visualization tools. You'll earn high-performance techniques for querying and retrieving geospatial data, and how to create a rich visual representation of global weather data using Python, Monary, and Matplotlib.
The Weather of the Century Part 3: VisualizationMongoDB
MongoDB natively supports geospatial indexing and querying, and it integrates easily with open source visualization tools. In this presentation, learn high-performance techniques for querying and retrieving geospatial data, and how to create a rich visual representation of global weather data using Python, Monary, and Matplotlib.
Back to Basics Webinar 5: Introduction to the Aggregation FrameworkMongoDB
This is the fifth webinar of a Back to Basics series that will introduce you to the MongoDB database. This webinar will introduce you to the aggregation framework.
MongoDB Europe 2016 - Debugging MongoDB PerformanceMongoDB
Asya is back, and so is Sherlock Holmes and his techniques to gather and analyze data from your poorly performing MongoDB clusters. In this advanced talk we take a deep look at all the diagnostic data that lives inside MongoDB - how to interrogate and interpret it to help you solve those frustrating performance bottlenecks that we all face occasionally.
MongoDB World 2019: Using Client Side Encryption in MongoDB 4.2 LinkMongoDB
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.
Engineers often ask "how do I know if I should build my application on MongoDB?" IT executives ask a similar question, "which applications in my application portfolio should I migrate to MongoDB?" This presentation will present a framework for answering these questions.
We will cover two sets of criteria: (1) how to determine when to migrate a legacy application to MongoDB and (2) when should MongoDB be used for new applications? The presentation will also include a brief introduction to MongoDB to provide enough MongoDB technical background for analyzing when to use MongoDB?
Learning Objectives:
The basics of MongoDB document model, query capabilities, and architecture required for analyzing when to use MongoDB?
Criteria for determining when to use MongoDB to re-platform legacy applications
Criteria for determining when to use MongoDB for new applications
This talk will demonstrate the Internet of Things with Windows Azure. Using embedded devices that interact with Windows Azure cloud technologies, the Internet of Things ideology is enabled with scalable and resilient cloud systems that imbue the resource constrained devices with elastic, on-demand additional computing power that allows any network connected device to achieve amazing computational feats. The talk features three main device/cloud interactions: persisting unbounded data from sensors, communicating through resilient channels and interacting directly with the Windows Azure cloud to provision and control cloud based infrastructure.
Big Data otimizado: Arquiteturas eficientes para construção de Pipelines MapR...Tail Target
Limpar, agregar, analisar, transformar: aplicações de data science no mundo real em geral envolvem a execução de diversas etapas de processamento, cada uma adicionando mais valor aos seus dados. Arquitetar e orquestrar estes pipelines de forma eficiente é uma tarefa que exige uma boa dose de conhecimento sobre o funcionamento interno de algoritmos de MapReduce e alguns truques que você só aprende depois de processar vários terabytes. Esta palestra irá mostrar como arquitetar MapReduce Pipelines eficientes usando o framework Apache Crunch, como integrar seus pipelines com fontes de dados externas como Redis, MongoDB ou mesmo bancos de dados relacionais, qual a melhor granularidade para seus jobs e quando investir em uma arquitetura de MapReduce realmente faz sentido.
Palestra apresentada por Fabiane Bizinella Nardon no QConSP 2013.
MongoDB natively supports geospatial indexing and querying, and it integrates easily with open source visualization tools. In this webinar, learn high-performance techniques for querying and retrieving geospatial data, and how to create a rich visual representation of global weather data using Python, Monary, and Matplotlib.
The weather is everywhere and always. That makes for a lot of data. This talk will walk you through how you can use MongoDB to store and analyze worldwide weather data from the entire 20th century in a graphical application. We’ll discuss loading and indexing terabytes of data in a sharded cluster, and optimizing the schema design for interactive exploration. MongoDB also natively supports geospatial indexing and querying, and it integrates easily with open source visualization tools. You'll earn high-performance techniques for querying and retrieving geospatial data, and how to create a rich visual representation of global weather data using Python, Monary, and Matplotlib.
The Weather of the Century Part 3: VisualizationMongoDB
MongoDB natively supports geospatial indexing and querying, and it integrates easily with open source visualization tools. In this presentation, learn high-performance techniques for querying and retrieving geospatial data, and how to create a rich visual representation of global weather data using Python, Monary, and Matplotlib.
Back to Basics Webinar 5: Introduction to the Aggregation FrameworkMongoDB
This is the fifth webinar of a Back to Basics series that will introduce you to the MongoDB database. This webinar will introduce you to the aggregation framework.
MongoDB Europe 2016 - Debugging MongoDB PerformanceMongoDB
Asya is back, and so is Sherlock Holmes and his techniques to gather and analyze data from your poorly performing MongoDB clusters. In this advanced talk we take a deep look at all the diagnostic data that lives inside MongoDB - how to interrogate and interpret it to help you solve those frustrating performance bottlenecks that we all face occasionally.
MongoDB World 2019: Using Client Side Encryption in MongoDB 4.2 LinkMongoDB
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.
Engineers often ask "how do I know if I should build my application on MongoDB?" IT executives ask a similar question, "which applications in my application portfolio should I migrate to MongoDB?" This presentation will present a framework for answering these questions.
We will cover two sets of criteria: (1) how to determine when to migrate a legacy application to MongoDB and (2) when should MongoDB be used for new applications? The presentation will also include a brief introduction to MongoDB to provide enough MongoDB technical background for analyzing when to use MongoDB?
Learning Objectives:
The basics of MongoDB document model, query capabilities, and architecture required for analyzing when to use MongoDB?
Criteria for determining when to use MongoDB to re-platform legacy applications
Criteria for determining when to use MongoDB for new applications
This talk will demonstrate the Internet of Things with Windows Azure. Using embedded devices that interact with Windows Azure cloud technologies, the Internet of Things ideology is enabled with scalable and resilient cloud systems that imbue the resource constrained devices with elastic, on-demand additional computing power that allows any network connected device to achieve amazing computational feats. The talk features three main device/cloud interactions: persisting unbounded data from sensors, communicating through resilient channels and interacting directly with the Windows Azure cloud to provision and control cloud based infrastructure.
Una sintesi della presentazione di Software Business srl all'evento "Innovazione e Semplificazione" di Napoli 14/06 organizzato in collaborazione con ICM.S e SAP Italia.
Webinar: Data Processing and Aggregation OptionsMongoDB
MongoDB scales easily to store mass volumes of data. However, when it comes to making sense of it all what options do you have? In this talk, we'll take a look at 3 different ways of aggregating your data with MongoDB, and determine the reasons why you might choose one way over another. No matter what your big data needs are, you will find out how MongoDB the big data store is evolving to help make sense of your data.
Eagle6 is a product that use system artifacts to create a replica model that represents a near real-time view of system architecture. Eagle6 was built to collect system data (log files, application source code, etc.) and to link system behaviors in such a way that the user is able to quickly identify risks associated with unknown or unwanted behavioral events that may result in unknown impacts to seemingly unrelated down-stream systems. This session is designed to present the capabilities of the Eagle6 modeling product and how we are using MongoDB to support near-real-time analysis of large disparate datasets.
CouchApps are web applications built using CouchDB, JavaScript, and HTML5. CouchDB is a document-oriented database that stores JSON documents, has a RESTful HTTP API, and is queried using map/reduce views. This talk will answer your basic questions about CouchDB, but will focus on building CouchApps and related tools.
MongoDB World 2019: Exploring your MongoDB Data with Pirates (R) and Snakes (...MongoDB
Does exploring data excite you? Do you use Python or R as your language of choice for data analysis? Does your job title include the term Data Analyst? If you answered yes to any of those questions, then the Exploring Your MongoDB Data with Pirates and Snakes is the session for you! MongoDB Developer Advocate Ken Alger will show the suggested method for using dataframe structures in R and Python with your MongoDB data. He’ll show the code for best practices in both languages to move your array based MongoDB data into the popular fast, flexible, and expressive dataframes used for data analysis in these prominent programming languages.
Introducing the Eve REST API Framework.
FOSDEM 2014, Brussels
PyCon Sweden 2014, Stockholm
PyCon Italy 2014, Florence
Python Meetup, Helsinki
EuroPython 2014, Berlin
Joins and Other Aggregation Enhancements Coming in MongoDB 3.2MongoDB
Applications get great efficiency from MongoDB by combining data that is accessed together into a single document. There are however situations where it is more efficient to have references between documents rather than embedding everything into a single document. This led to joins being our most requested feature. MongoDB 3.2 addresses this through the introduction of the $lookup stage in the aggregation pipeline to implement left-outer joins.
This webinar looks at $lookup as well as the other significant aggregation enhancements coming with MongoDB 3.2—why they're needed, what they deliver, and how to use them.
All Things Open 2014 - Day 2
Thursday, October 23rd, 2014
Doug Turnbull
Search & Big Data Architect for OpenSource Connections
Databases
Stop Worrying & Love the SQL - A Case Study
Solutions for bi-directional Integration between Oracle RDMBS & Apache KafkaGuido Schmutz
A Kafka cluster stores streams of records (messages) in categories called topics. It is the architectural backbone for integrating streaming data with a Data Lake, Microservices and Stream Processing. Today’s enterprises have their core systems often implemented on top of relational databases, such as the Oracle RDBMS. Implementing a new solution supporting the digital strategy using Kafka and the ecosystem can not always be done completely separate from the traditional legacy solutions. Often streaming data has to be enriched with state data which is held in an RDBMS of a legacy application. It’s important to cache this data in the stream processing solution, so that It can be efficiently joined to the data stream. But how do we make sure that the cache is kept up-to-date, if the source data changes? We can either poll for changes from Kafka using Kafka Connect or let the RDBMS push the data changes to Kafka. But what about writing data back to the legacy application, i.e. an anomaly is detected inside the stream processing solution which should trigger an action inside the legacy application. Using Kafka Connect we can write to a database table or view, which could trigger the action. But this not always the best option. If you have an Oracle RDBMS, there are many other ways to integrate the database with Kafka, such as Advanced Queueing (message broker in the database), CDC through Golden Gate or Debezium, Oracle REST Database Service (ORDS) and more. In this session, we present various blueprints for integrating an Oracle RDBMS with Apache Kafka in both directions and discuss how these blueprints can be implemented using the products mentioned before.
Solutions for bi-directional integration between Oracle RDBMS and Apache Kafk...confluent
A Kafka cluster stores streams of records (messages) in categories called topics. It is the architectural backbone for integrating streaming data with a Data Lake, Microservices and Stream Processing. Today's enterprises have their core systems often implemented on top of relational databases, such as the Oracle RDBMS. Implementing a new solution supporting the digital strategy using Kafka and the ecosystem can not always be done completely separate from the traditional legacy solutions. Often streaming data has to be enriched with state data which is held in an RDBMS of a legacy application. It's important to cache this data in the stream processing solution, so that It can be efficiently joined to the data stream. But how do we make sure that the cache is kept up-to-date, if the source data changes? We can either poll for changes from Kafka using Kafka Connect or let the RDBMS push the data changes to Kafka. But what about writing data back to the legacy application, i.e. an anomaly is detected inside the stream processing solution which should trigger an action inside the legacy application. Using Kafka Connect we can write to a database table or view, which could trigger the action. But this not always the best option. If you have an Oracle RDBMS, there are many other ways to integrate the database with Kafka, such as Advanced Queueing (message broker in the database), CDC through Golden Gate or Debezium, Oracle REST Database Service (ORDS) and more. In this session, we present various blueprints for integrating an Oracle RDBMS with Apache Kafka in both directions and discuss how these blueprints can be implemented using the products mentioned before.
Bringing SQL to NoSQL: Rich, Declarative Query for NoSQLKeshav Murthy
Abstract
NoSQL databases bring the benefits of schema flexibility and
elastic scaling to the enterprise. Until recently, these benefits have
come at the expense of giving up rich declarative querying as
represented by SQL.
In today’s world of agile business, developers and organizations need
the benefits of both NoSQL and SQL in a single platform. NoSQL
(document) databases provide schema flexibility; fast lookup; and
elastic scaling. SQL-based querying provides expressive data access
and transformation; separation of querying from modeling and storage;
and a unified interface for applications, tools, and users.
Developers need to deliver applications that can easily evolve,
perform, and scale. Otherwise, the cost, effort, and delay in keeping
up with changing business needs will become significant disadvantages.
Organizations need sophisticated and rapid access to their operational data, in
order to maintain insight into their business. This access should
support both pre-defined and ad-hoc querying, and should integrate
with standard analytical tools.
This talk will cover how to build applications that combine the
benefits of NoSQL and SQL to deliver agility, performance, and
scalability. It includes:
- N1QL, which extends SQL to JSON
- JSON data modeling
- Indexing and performance
- Transparent scaling
- Integration and ecosystem
You will walk away with an understanding of the design patterns and
best practices for effective utilization of NoSQL document
databases - all using open-source technologies.
Application Development & Database Choices: Postgres Support for non Relation...EDB
This talk will cover the advanced features of PostgreSQL that make it the most-loved RDBMS by developers and a great choice for non-relational workloads.
This webinar will explore:
- Global adoption of Postgres
- Document-centric applications
- Geographic Information Systems (GIS)
- Business intelligence
- Central data centers
- Server-side languages
On Tuesday 18th March, the MongoDB team held on online Cloud Workshop in place of the in-person event which was planned.
Attendees learnt how to build modern, event driven applications powered by MongoDB Atlas in Google Cloud Platform (GCP) and were shown relevant operational and security best practices, to get started immediately with their own digital transformations.
Understanding N1QL Optimizer to Tune QueriesKeshav Murthy
Every flight has a flight plan. Every query has a query plan. You must have seen its text form, called EXPLAIN PLAN. Query optimizer is responsible for creating this query plan for every query, and it tries to create an optimal plan for every query. In Couchbase, the query optimizer has to choose the most optimal index for the query, decide on the predicates to push down to index scans, create appropriate spans (scan ranges) for each index, understand the sort (ORDER BY) and pagination (OFFSET, LIMIT) requirements, and create the plan accordingly. When you think there is a better plan, you can hint the optimizer with USE INDEX. This talk will teach you how the optimizer selects the indices, index scan methods, and joins. It will teach you the analysis of the optimizer behavior using EXPLAIN plan and how to change the choices optimizer makes.
Similar to Data liberty in an age post sql - with pizazz - as presented at cloudburst (20)
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
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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.
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.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
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.
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
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.
19. public class SwedishSessionsJob : HadoopJob<SwedishSessionsMapper, SessionsReducer>
{
public override HadoopJobConfiguration Configure(ExecutorContext context)
{
var config = new HadoopJobConfiguration()
{
InputPath = ""/AllSessions/*.gz"",
OutputFolder = "/SwedishSessions/"
};
return config;
}
}
20. public class SwedishSessionsMapper : MapperBase
{
public override void Map(string inputLine, MapperContext context)
{
if (inputLine.Contains("Country=Sweden")
{
context.IncrementCounter("SwedishSession");
context.EmitKeyValue(“SE", "1");
}
}
}
21. public class SessionsReducer : ReducerCombinerBase
{
public override void Reduce(string key, IEnumerable<string> values, ReducerContext context)
{
context.EmitKeyValue(key, values.Count());
}
}
22. var inputData = "Country=Sweden&Name=Magnus";
var result =
StreamingUnit.Execute<Jobs.SwedishJob>(new[]{inputData});
Assert.AreEqual("SEt1", result.ReducerResult.First());
23. Your existing development team
can immediately realise value
The frameworks
facilitate
deterministic
testing for
highly reliable
queries
Complex logic is best expressed in
programmatic form
31. There are many different way to
connect with MongoDB from a
.net project.
Official
Wrapper
Alternative
Tool
32. public class Book
{
public string Author { get; set; }
public string Title { get; set; }
}
// "entities" is the name of the collection
var books = database.GetCollection<Entity>("books");
Book book = new Book
{
Author = "Ernest Hemingway",
Title = "For Whom the Bell Tolls"
};
books.Insert(book);
33. BsonDocument person = new BsonDocument {
{ "name", "John Doe" },
{ "address", new BsonDocument {
{ "street", "123 Main St." },
{ "city", "Centerville" },
{ "state", "PA" },
{ "zip", 12345}
}}
};
var people = database.GetCollection<BsonDocument>("people");
people.Insert(person);
Slide ObjectivesUnderstand the hierarchy of Blob storageSpeaker NotesPut Blob - Creates a new blob or replaces an existing blob within a container.Get Blob - Reads or downloads a blob from the system, including its metadata and properties.Delete Blob - Deletes a blobCopy Blob - Copies a source blob to a destination blob within the same storage account.SnapShot Blob - The Snapshot Blob operation creates a read-only snapshot of a blob.Lease Blob - Establishes an exclusive one-minute write lock on a blob. To write to a locked blob, a client must provide a lease ID.Using the REST API for the Blob service, developers can create a hierarchical namespace similar to a file system. Blob names may encode a hierarchy by using a configurable path separator. For example, the blob names MyGroup/MyBlob1 and MyGroup/MyBlob2 imply a virtual level of organization for blobs. The enumeration operation for blobs supports traversing the virtual hierarchy in a manner similar to that of a file system, so that you can return a set of blobs that are organized beneath a group. For example, you can enumerate all blobs organized under MyGroup/.NotesThe Blob service provides storage for entities, such as binary files and text files. The REST API for the Blob service exposes two resources: containers and blobs. A container is a set of blobs; every blob must belong to a container. The Blob service defines two types of blobs:Block blobs, which are optimized for streaming. This type of blob is the only blob type available with versions prior to 2009-09-19.Page blobs, which are optimized for random read/write operations and which provide the ability to write to a range of bytes in a blob. Page blobs are available only with version 2009-09-19.Containers and blobs support user-defined metadata in the form of name-value pairs specified as headers on a request operation.Using the REST API for the Blob service, developers can create a hierarchical namespace similar to a file system. Blob names may encode a hierarchy by using a configurable path separator. For example, the blob names MyGroup/MyBlob1 and MyGroup/MyBlob2 imply a virtual level of organization for blobs. The enumeration operation for blobs supports traversing the virtual hierarchy in a manner similar to that of a file system, so that you can return a set of blobs that are organized beneath a group. For example, you can enumerate all blobs organized under MyGroup/.A block blob may be created in one of two ways. Block blobs less than or equal to 64 MB in size can be uploaded by calling the Put Blob operation. Block blobs larger than 64 MB must be uploaded as a set of blocks, each of which must be less than or equal to 4 MB in size. A set of successfully uploaded blocks can be assembled in a specified order into a single contiguous blob by calling Put Block List. The maximum size currently supported for a block blob is 200 GB.Page blobs are created and initialized with a maximum size with a call to Put Blob. To write content to a page blob, you call the Put Page operation. The maximum size currently supported for a page blob is 1 TB.Blobs support conditional update operations that may be useful for concurrency control and efficient uploading. Blobs can be read by calling the Get Blob operation. A client may read the entire blob, or an arbitrary range of bytes. For the Blob service API reference, see Blob Service API.
Slide ObjectivesUnderstand the hierarchy of Blob storageSpeaker NotesPut Blob - Creates a new blob or replaces an existing blob within a container.Get Blob - Reads or downloads a blob from the system, including its metadata and properties.Delete Blob - Deletes a blobCopy Blob - Copies a source blob to a destination blob within the same storage account.SnapShot Blob - The Snapshot Blob operation creates a read-only snapshot of a blob.Lease Blob - Establishes an exclusive one-minute write lock on a blob. To write to a locked blob, a client must provide a lease ID.Using the REST API for the Blob service, developers can create a hierarchical namespace similar to a file system. Blob names may encode a hierarchy by using a configurable path separator. For example, the blob names MyGroup/MyBlob1 and MyGroup/MyBlob2 imply a virtual level of organization for blobs. The enumeration operation for blobs supports traversing the virtual hierarchy in a manner similar to that of a file system, so that you can return a set of blobs that are organized beneath a group. For example, you can enumerate all blobs organized under MyGroup/.NotesThe Blob service provides storage for entities, such as binary files and text files. The REST API for the Blob service exposes two resources: containers and blobs. A container is a set of blobs; every blob must belong to a container. The Blob service defines two types of blobs:Block blobs, which are optimized for streaming. This type of blob is the only blob type available with versions prior to 2009-09-19.Page blobs, which are optimized for random read/write operations and which provide the ability to write to a range of bytes in a blob. Page blobs are available only with version 2009-09-19.Containers and blobs support user-defined metadata in the form of name-value pairs specified as headers on a request operation.Using the REST API for the Blob service, developers can create a hierarchical namespace similar to a file system. Blob names may encode a hierarchy by using a configurable path separator. For example, the blob names MyGroup/MyBlob1 and MyGroup/MyBlob2 imply a virtual level of organization for blobs. The enumeration operation for blobs supports traversing the virtual hierarchy in a manner similar to that of a file system, so that you can return a set of blobs that are organized beneath a group. For example, you can enumerate all blobs organized under MyGroup/.A block blob may be created in one of two ways. Block blobs less than or equal to 64 MB in size can be uploaded by calling the Put Blob operation. Block blobs larger than 64 MB must be uploaded as a set of blocks, each of which must be less than or equal to 4 MB in size. A set of successfully uploaded blocks can be assembled in a specified order into a single contiguous blob by calling Put Block List. The maximum size currently supported for a block blob is 200 GB.Page blobs are created and initialized with a maximum size with a call to Put Blob. To write content to a page blob, you call the Put Page operation. The maximum size currently supported for a page blob is 1 TB.Blobs support conditional update operations that may be useful for concurrency control and efficient uploading. Blobs can be read by calling the Get Blob operation. A client may read the entire blob, or an arbitrary range of bytes. For the Blob service API reference, see Blob Service API.
Slide ObjectivesUnderstand the hierarchy of Blob storageSpeaker NotesPut Blob - Creates a new blob or replaces an existing blob within a container.Get Blob - Reads or downloads a blob from the system, including its metadata and properties.Delete Blob - Deletes a blobCopy Blob - Copies a source blob to a destination blob within the same storage account.SnapShot Blob - The Snapshot Blob operation creates a read-only snapshot of a blob.Lease Blob - Establishes an exclusive one-minute write lock on a blob. To write to a locked blob, a client must provide a lease ID.Using the REST API for the Blob service, developers can create a hierarchical namespace similar to a file system. Blob names may encode a hierarchy by using a configurable path separator. For example, the blob names MyGroup/MyBlob1 and MyGroup/MyBlob2 imply a virtual level of organization for blobs. The enumeration operation for blobs supports traversing the virtual hierarchy in a manner similar to that of a file system, so that you can return a set of blobs that are organized beneath a group. For example, you can enumerate all blobs organized under MyGroup/.NotesThe Blob service provides storage for entities, such as binary files and text files. The REST API for the Blob service exposes two resources: containers and blobs. A container is a set of blobs; every blob must belong to a container. The Blob service defines two types of blobs:Block blobs, which are optimized for streaming. This type of blob is the only blob type available with versions prior to 2009-09-19.Page blobs, which are optimized for random read/write operations and which provide the ability to write to a range of bytes in a blob. Page blobs are available only with version 2009-09-19.Containers and blobs support user-defined metadata in the form of name-value pairs specified as headers on a request operation.Using the REST API for the Blob service, developers can create a hierarchical namespace similar to a file system. Blob names may encode a hierarchy by using a configurable path separator. For example, the blob names MyGroup/MyBlob1 and MyGroup/MyBlob2 imply a virtual level of organization for blobs. The enumeration operation for blobs supports traversing the virtual hierarchy in a manner similar to that of a file system, so that you can return a set of blobs that are organized beneath a group. For example, you can enumerate all blobs organized under MyGroup/.A block blob may be created in one of two ways. Block blobs less than or equal to 64 MB in size can be uploaded by calling the Put Blob operation. Block blobs larger than 64 MB must be uploaded as a set of blocks, each of which must be less than or equal to 4 MB in size. A set of successfully uploaded blocks can be assembled in a specified order into a single contiguous blob by calling Put Block List. The maximum size currently supported for a block blob is 200 GB.Page blobs are created and initialized with a maximum size with a call to Put Blob. To write content to a page blob, you call the Put Page operation. The maximum size currently supported for a page blob is 1 TB.Blobs support conditional update operations that may be useful for concurrency control and efficient uploading. Blobs can be read by calling the Get Blob operation. A client may read the entire blob, or an arbitrary range of bytes. For the Blob service API reference, see Blob Service API.
Microsoft’s technology leadership in this area takes best of breed technology from industry and makes it enterprise ready. Furthermore, Microsoft has brought the ability to reuse existing IT skill on a new big data platform. The code for expressing this logic is has a shallow learning curve for experienced Microsoft .net developers.
The “burst” provisioning of data technologies for a duration that encapsulates the uptime of a certain query alone allows for the consideration of “the commoditised query” where very well understood costs can be weighed against business benefits in a profit centre within a business – liberating the previous sunk cost of BI technology.
Relationship DB joins “Tables” of different data together to form a single picture of somethingDocument DB contains all the details of that something in a single document