The document discusses the HOBBIT platform for benchmarking big data platforms. It aims to provide a unified benchmarking platform as a community-driven effort. The platform will include reference datasets and implementations of key performance indicators to standardize benchmarking and allow comparison of results. It will focus on benchmarking tasks related to big linked data and the entire data lifecycle.
An overview of the workshop as presented at the 1st International Workshop on Benchmarking Linked Data (BLINK).
(HOBBIT project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
A summary of the workshop as presented at the 1st International Workshop on Benchmarking Linked Data (BLINK).
(HOBBIT project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
This document summarizes a lecture on computer applications in industrial engineering. It discusses classes and objects in C#, adding controls to Windows forms, and control properties and layout. It also mentions event handling in graphical user interfaces and generated code in Visual Studio forms. The document is a recap of topics covered and encourages students to contact the lecturer with any questions.
The document discusses a web platform called Yhat that allows data scientists to easily integrate predictive models into software applications. Yhat provides tools to deploy models written in R, Python, or Excel as web services with a simple API. This addresses the challenge of porting models between languages that developers currently face. Yhat has seen growing interest since its launch three months ago, with over 30,000 monthly visitors and 117 models deployed.
This document is a resume for Zarin Bhuiyan summarizing their education and experience. Zarin is studying Electrical and Computer Engineering at Olin College of Engineering and has experience in areas such as software development, circuits, 3D printing, and research. Notable experiences include developing SOLIDWORKS tutorials as an intern at Dassault Systemes and working on teams to build a robotic turtle and design services for caregivers.
The document discusses the HOBBIT platform for benchmarking big data platforms. It aims to provide a unified benchmarking platform as a community-driven effort. The platform will include reference datasets and implementations of key performance indicators to standardize benchmarking and allow comparison of results. It will focus on benchmarking tasks related to big linked data and the entire data lifecycle.
An overview of the workshop as presented at the 1st International Workshop on Benchmarking Linked Data (BLINK).
(HOBBIT project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
A summary of the workshop as presented at the 1st International Workshop on Benchmarking Linked Data (BLINK).
(HOBBIT project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
This document summarizes a lecture on computer applications in industrial engineering. It discusses classes and objects in C#, adding controls to Windows forms, and control properties and layout. It also mentions event handling in graphical user interfaces and generated code in Visual Studio forms. The document is a recap of topics covered and encourages students to contact the lecturer with any questions.
The document discusses a web platform called Yhat that allows data scientists to easily integrate predictive models into software applications. Yhat provides tools to deploy models written in R, Python, or Excel as web services with a simple API. This addresses the challenge of porting models between languages that developers currently face. Yhat has seen growing interest since its launch three months ago, with over 30,000 monthly visitors and 117 models deployed.
This document is a resume for Zarin Bhuiyan summarizing their education and experience. Zarin is studying Electrical and Computer Engineering at Olin College of Engineering and has experience in areas such as software development, circuits, 3D printing, and research. Notable experiences include developing SOLIDWORKS tutorials as an intern at Dassault Systemes and working on teams to build a robotic turtle and design services for caregivers.
Este documento trata sobre la visualización de la información. Define la visualización de la información como la representación gráfica de un conjunto de datos, ya sean simples o complejos, con el objetivo de analizarlos. Explica las etapas del proceso de visualización: recopilación de datos, procesamiento, y representación visual. También presenta ejemplos como tablas, gráficos y árboles, e identifica elementos clave como la satisfacción del usuario y modelos conceptuales. Concluye que la cultura futura estará definida por las interfaces
Visualizing Data: The 7 stages of data visualizationcreyesnav
El documento resume los conceptos clave de la visualización de datos según Ben Fry. Describe los 7 pasos del proceso de visualización de datos, incluyendo adquirir, analizar, filtrar, extraer, representar, refinar e interactuar. También cubre los fundamentos de la visualización de datos según Fry, como usar la menor cantidad de datos posible para comunicar un mensaje significativo.
Visualizacion de la Infomación. De los datos al conocimiento.Ignasi Alcalde
La visualización de la información es un disciplina realmente fascinante cuyo interés no ha hecho más que despegar. Si por ejemplo buscamos infographics o data visualization en internet podremos comprobar que el interés crece día a día. Mires donde mires hay información visual que reclama tu atención. La comunicación efectiva e inmediata a través de una simple y fácil visualización prima frente a largos textos de compleja asimilación. Pero… ¿Qué es realmente la visualización de la información? En tus manos tienes una obra práctica que te ayudará a introducirte en la visualización de la información, el proceso de trabajo con datos y las herramientas más comunes.
http://www.editorialuoc.cat/visualizacindelainformacin-p-1674.html?cPath=1
Business intelligence data analytics-visualizationMuthu Natarajan
Business Intelligence, Cloud Computing, Data Analytics, Data Scrubbing, Data Mining, Big Data & Intelligence, How to use Data into Information, Decision Based, Methods for Business Intelligence, Advanced Analytics, OLAP, Multidimensional Data, Data Visualization.
Este documento discute cómo los recursos de visualización de datos, como gráficos, mapas y nubes de palabras, pueden usarse para contar historias complejas de una manera entendible. Se presentan ejemplos como las visualizaciones de datos del médico Hans Rosling y el artista Jonathan Harris. También se describen formatos comunes como mapas, gráficos de barras y líneas, así como nuevos formatos emergentes. El documento argumenta que la visualización de datos permite procesar grandes cantidades de información y encontrar historias en datos aburridos
The document outlines the various stages of data management from collection to analysis and how visualization can aid at each stage. It discusses using visualizations like trees, graphs and networks to plan the data management process and understand relationships between datasets during collection. During collection, visualization can also help understand results from data mining algorithms and the structure of files. At the assurance stage, graphical summaries produced from statistical operations on datasets can be used for security and quality checks. Visualizations like multi-dimensional maps and volumes can then be used for process monitoring and quality assurance. Visualization is also discussed as a way to understand and analyze large web archives by examining file hierarchies and types during preservation. Finally, different visualizations can be applied during analysis depending on user needs
Este documento describe los componentes y aplicaciones de la Web Semántica. Explica que la Web Semántica es una extensión de la Web existente que utiliza lenguajes formales como RDF, OWL y XML para estructurar el contenido y representar el conocimiento de manera que las máquinas puedan procesar y comprender la información de forma más efectiva. Esto permitirá el desarrollo de agentes inteligentes y servicios automatizados que puedan buscar y procesar información de manera más precisa.
Presentation slides:Telling Stories with Data
Geoff McGhee is the Creative Director of Media and Communications and a former John S. Knight Journalism fellow at Stanford University.
La capa de presentación del modelo OSI proporciona una estandarización en la transmisión de datos entre sistemas. Se encarga de representar la información de forma reconocible al ocuparse de los aspectos semánticos y sintácticos de la comunicación, como la compresión, cifrado y estructura de los datos. También puede implementar aplicaciones de criptografía.
Data Visualization for Business - Pallav NadhaniFusionCharts
The document discusses data visualization for business purposes. It notes that data visualization combines art, science, math and technology to visually display measurable quantities using tools like points, lines, curves and color to understand, substantiate hypotheses and discover from data. The document outlines different types of visualizations and provides tips for effective business data visualization like knowing your audience, choosing the right type of visualization, and exploring ways to enhance it. It stresses tailoring visualizations to the goals, roles and needs of different business departments and positions.
Nueva introducción de DataLab Community del 2017. Somos una comunidad abierta de Ciencia de Datos. Generamos colaboración entre profesionales y aprendices, compartiendo conocimientos, desarrollando habilidades y vinculando para impulsar la Ciencia de Datos.
Design activity framework for visualization designDominika Mazur
This document presents a design activity framework for visualization design. It outlines four main design activities: understand, ideate, make, and deploy. Each activity has a specific motivation and outcomes. A variety of methods are provided that can be used within each design activity, including both generative and evaluative methods. The framework is intended to provide structure and flexibility to the visualization design process.
Visual analytics: poniendo en valor el dato a través de la visualizaciónAlex Rayón Jerez
Este documento presenta un taller sobre visualización analítica de datos. Explica brevemente la historia de la visualización de información, desde Priestley en el siglo XVIII hasta Wilkinson en el siglo XX. Define conceptos clave como visualización de datos, visualización de información, geovisualización y visual analytics. Describe el proceso de visualización, incluyendo la transformación de datos univariados, bivariados y multivariados, y la codificación de valores y relaciones a través de líneas, mapas y diagramas. El documento también cubre principios
Este documento trata sobre la importancia de la visualización de datos. Menciona que al visualizar los datos se producen revelaciones y que la visualización de datos no es solo una tarea de cartógrafos, programadores o estadísticos, sino que cualquiera puede visualizar sus propios datos. También destaca que la visualización de datos es tan importante como los datos mismos y proporciona algunos ejemplos de herramientas y sitios web para la visualización de datos.
Big data visualization frameworks allow for analyzing and visualizing large datasets. The document discusses a big data visualization framework created by Abhinav Krishna to enable analyzing and visualizing large amounts of data. The framework helps users understand insights and patterns in big data through interactive visualizations.
La visualización de datos es el estudio de la representación visual de datos para comunicar información de manera clara y efectiva a través de medios gráficos. Requiere experiencia en múltiples disciplinas como el diseño, la comunicación y la información. La visualización de datos tiene como objetivo no solo comunicar la información de manera clara, sino también estimular la participación y atención del espectador.
Ciclo de vida del dato en ambientes de Business IntelligenceAlex Rayón Jerez
Taller práctico "Ciclo de vida del dato en ambientes de Business Intelligence" como primer paso a la capacitación de una organización para la explotación de los datos para aumentar la inteligencia de negocios.
Frontend Architecture and Data VisualizationAltocloud
Frontend Architecture and Data Visualization at Altocloud. Altocloud connects your business with the right customers at the right time in their journey – improving conversions and enhancing customer experience.
Data Visualization & Content Analytics: Nuxeo Platform LTS 2015Nuxeo
This document discusses Nuxeo Data Visualization. It provides structured and consistent data from a content repository that is available for users whenever needed. It features visual dashboards that provide insights into data to help with decision making. Specific elements discussed include repository, search, and workflow data visualizations that are securely scalable and have powerful search and filtering capabilities. Nuxeo Elements are also discussed as a way to build custom elements and applications using standards like Web Components and Polymer.
Construyendo un panel de visualización de indicadores claveAlex Rayón Jerez
Taller práctico "Construyendo un panel de visualización de indicadores clave" como tercer paso a la capacitación de una organización para la explotación de los datos para aumentar la inteligencia de negocios.
The document summarizes a presentation given by Jim Spohrer from IBM on smart service systems and cognitive assistants. Some key points:
- A service science perspective considers how service systems, value co-creation, and capabilities evolve through interactions between entities that have different capabilities, constraints, rights, and responsibilities.
- Cognitive systems and cognitive assistants can help augment and scale human expertise.
- IBM is working on developing cognitive assistants that can help with different occupations by assisting with various tasks.
- The vision is for cognitive technologies and assistants to augment and scale human expertise across many domains.
The document discusses big data analytics and tools. It introduces the concept of an "Internet of Corporate Things" and expanding analytics beyond just corporate data. It emphasizes that new tools and approaches are needed to take advantage of big data. The document provides guidance on starting a big data analytics initiative, including choosing a pilot use case, designing a new data architecture with a data lake, building an analytics center of excellence, and training analysts. It also summarizes various big data analytics tools for storage, delivery, and analyzing large datasets.
Este documento trata sobre la visualización de la información. Define la visualización de la información como la representación gráfica de un conjunto de datos, ya sean simples o complejos, con el objetivo de analizarlos. Explica las etapas del proceso de visualización: recopilación de datos, procesamiento, y representación visual. También presenta ejemplos como tablas, gráficos y árboles, e identifica elementos clave como la satisfacción del usuario y modelos conceptuales. Concluye que la cultura futura estará definida por las interfaces
Visualizing Data: The 7 stages of data visualizationcreyesnav
El documento resume los conceptos clave de la visualización de datos según Ben Fry. Describe los 7 pasos del proceso de visualización de datos, incluyendo adquirir, analizar, filtrar, extraer, representar, refinar e interactuar. También cubre los fundamentos de la visualización de datos según Fry, como usar la menor cantidad de datos posible para comunicar un mensaje significativo.
Visualizacion de la Infomación. De los datos al conocimiento.Ignasi Alcalde
La visualización de la información es un disciplina realmente fascinante cuyo interés no ha hecho más que despegar. Si por ejemplo buscamos infographics o data visualization en internet podremos comprobar que el interés crece día a día. Mires donde mires hay información visual que reclama tu atención. La comunicación efectiva e inmediata a través de una simple y fácil visualización prima frente a largos textos de compleja asimilación. Pero… ¿Qué es realmente la visualización de la información? En tus manos tienes una obra práctica que te ayudará a introducirte en la visualización de la información, el proceso de trabajo con datos y las herramientas más comunes.
http://www.editorialuoc.cat/visualizacindelainformacin-p-1674.html?cPath=1
Business intelligence data analytics-visualizationMuthu Natarajan
Business Intelligence, Cloud Computing, Data Analytics, Data Scrubbing, Data Mining, Big Data & Intelligence, How to use Data into Information, Decision Based, Methods for Business Intelligence, Advanced Analytics, OLAP, Multidimensional Data, Data Visualization.
Este documento discute cómo los recursos de visualización de datos, como gráficos, mapas y nubes de palabras, pueden usarse para contar historias complejas de una manera entendible. Se presentan ejemplos como las visualizaciones de datos del médico Hans Rosling y el artista Jonathan Harris. También se describen formatos comunes como mapas, gráficos de barras y líneas, así como nuevos formatos emergentes. El documento argumenta que la visualización de datos permite procesar grandes cantidades de información y encontrar historias en datos aburridos
The document outlines the various stages of data management from collection to analysis and how visualization can aid at each stage. It discusses using visualizations like trees, graphs and networks to plan the data management process and understand relationships between datasets during collection. During collection, visualization can also help understand results from data mining algorithms and the structure of files. At the assurance stage, graphical summaries produced from statistical operations on datasets can be used for security and quality checks. Visualizations like multi-dimensional maps and volumes can then be used for process monitoring and quality assurance. Visualization is also discussed as a way to understand and analyze large web archives by examining file hierarchies and types during preservation. Finally, different visualizations can be applied during analysis depending on user needs
Este documento describe los componentes y aplicaciones de la Web Semántica. Explica que la Web Semántica es una extensión de la Web existente que utiliza lenguajes formales como RDF, OWL y XML para estructurar el contenido y representar el conocimiento de manera que las máquinas puedan procesar y comprender la información de forma más efectiva. Esto permitirá el desarrollo de agentes inteligentes y servicios automatizados que puedan buscar y procesar información de manera más precisa.
Presentation slides:Telling Stories with Data
Geoff McGhee is the Creative Director of Media and Communications and a former John S. Knight Journalism fellow at Stanford University.
La capa de presentación del modelo OSI proporciona una estandarización en la transmisión de datos entre sistemas. Se encarga de representar la información de forma reconocible al ocuparse de los aspectos semánticos y sintácticos de la comunicación, como la compresión, cifrado y estructura de los datos. También puede implementar aplicaciones de criptografía.
Data Visualization for Business - Pallav NadhaniFusionCharts
The document discusses data visualization for business purposes. It notes that data visualization combines art, science, math and technology to visually display measurable quantities using tools like points, lines, curves and color to understand, substantiate hypotheses and discover from data. The document outlines different types of visualizations and provides tips for effective business data visualization like knowing your audience, choosing the right type of visualization, and exploring ways to enhance it. It stresses tailoring visualizations to the goals, roles and needs of different business departments and positions.
Nueva introducción de DataLab Community del 2017. Somos una comunidad abierta de Ciencia de Datos. Generamos colaboración entre profesionales y aprendices, compartiendo conocimientos, desarrollando habilidades y vinculando para impulsar la Ciencia de Datos.
Design activity framework for visualization designDominika Mazur
This document presents a design activity framework for visualization design. It outlines four main design activities: understand, ideate, make, and deploy. Each activity has a specific motivation and outcomes. A variety of methods are provided that can be used within each design activity, including both generative and evaluative methods. The framework is intended to provide structure and flexibility to the visualization design process.
Visual analytics: poniendo en valor el dato a través de la visualizaciónAlex Rayón Jerez
Este documento presenta un taller sobre visualización analítica de datos. Explica brevemente la historia de la visualización de información, desde Priestley en el siglo XVIII hasta Wilkinson en el siglo XX. Define conceptos clave como visualización de datos, visualización de información, geovisualización y visual analytics. Describe el proceso de visualización, incluyendo la transformación de datos univariados, bivariados y multivariados, y la codificación de valores y relaciones a través de líneas, mapas y diagramas. El documento también cubre principios
Este documento trata sobre la importancia de la visualización de datos. Menciona que al visualizar los datos se producen revelaciones y que la visualización de datos no es solo una tarea de cartógrafos, programadores o estadísticos, sino que cualquiera puede visualizar sus propios datos. También destaca que la visualización de datos es tan importante como los datos mismos y proporciona algunos ejemplos de herramientas y sitios web para la visualización de datos.
Big data visualization frameworks allow for analyzing and visualizing large datasets. The document discusses a big data visualization framework created by Abhinav Krishna to enable analyzing and visualizing large amounts of data. The framework helps users understand insights and patterns in big data through interactive visualizations.
La visualización de datos es el estudio de la representación visual de datos para comunicar información de manera clara y efectiva a través de medios gráficos. Requiere experiencia en múltiples disciplinas como el diseño, la comunicación y la información. La visualización de datos tiene como objetivo no solo comunicar la información de manera clara, sino también estimular la participación y atención del espectador.
Ciclo de vida del dato en ambientes de Business IntelligenceAlex Rayón Jerez
Taller práctico "Ciclo de vida del dato en ambientes de Business Intelligence" como primer paso a la capacitación de una organización para la explotación de los datos para aumentar la inteligencia de negocios.
Frontend Architecture and Data VisualizationAltocloud
Frontend Architecture and Data Visualization at Altocloud. Altocloud connects your business with the right customers at the right time in their journey – improving conversions and enhancing customer experience.
Data Visualization & Content Analytics: Nuxeo Platform LTS 2015Nuxeo
This document discusses Nuxeo Data Visualization. It provides structured and consistent data from a content repository that is available for users whenever needed. It features visual dashboards that provide insights into data to help with decision making. Specific elements discussed include repository, search, and workflow data visualizations that are securely scalable and have powerful search and filtering capabilities. Nuxeo Elements are also discussed as a way to build custom elements and applications using standards like Web Components and Polymer.
Construyendo un panel de visualización de indicadores claveAlex Rayón Jerez
Taller práctico "Construyendo un panel de visualización de indicadores clave" como tercer paso a la capacitación de una organización para la explotación de los datos para aumentar la inteligencia de negocios.
The document summarizes a presentation given by Jim Spohrer from IBM on smart service systems and cognitive assistants. Some key points:
- A service science perspective considers how service systems, value co-creation, and capabilities evolve through interactions between entities that have different capabilities, constraints, rights, and responsibilities.
- Cognitive systems and cognitive assistants can help augment and scale human expertise.
- IBM is working on developing cognitive assistants that can help with different occupations by assisting with various tasks.
- The vision is for cognitive technologies and assistants to augment and scale human expertise across many domains.
The document discusses big data analytics and tools. It introduces the concept of an "Internet of Corporate Things" and expanding analytics beyond just corporate data. It emphasizes that new tools and approaches are needed to take advantage of big data. The document provides guidance on starting a big data analytics initiative, including choosing a pilot use case, designing a new data architecture with a data lake, building an analytics center of excellence, and training analysts. It also summarizes various big data analytics tools for storage, delivery, and analyzing large datasets.
Accelerating SDLC for Large Public Sector Enterprise ApplicationsSplunk
This document discusses how big data analytics tools like Splunk can be used to accelerate the software development lifecycle for large public sector applications. It provides examples of how Splunk was used to improve productivity by enabling immediate log access across many servers and files. Splunk also created real-time performance dashboards to help identify root causes of issues. Additional analytics revealed insights like peak usage times and patterns, user behaviors on forms, and browser/device details. The summary concludes that these tools can improve IT and business while providing lessons on proper Splunk setup and logging the right application data.
The document discusses IBM's Cognitive Systems Institute Group (CSIG) and its director Jim Spohrer. CSIG works to build cognitive systems and platforms using techniques from fields like natural language processing, machine learning, and neuromorphic computing. The goal is to develop cognitive assistants that can augment human expertise to help solve complex problems. Universities are seen as important partners in this work through collaborations on research and by inspiring students to help build smarter service systems for the future.
How much does it cost to build a mobile app? That's probably the most asked question for mobile app developers. This presentation give insight into mobile app development process and how business people/clients can get better answers by providing more information when asking for app development cost estimates.
Bringing Cities, Libraries and Citizens Together through Open Data Hackathonsacecarruthers
This document discusses how open data hackathons can bring cities, libraries, and citizens together. It provides details about Edmonton Public Library's partnership with the City of Edmonton to host International Open Data Day hackathons in 2014 and 2015. A variety of projects were created at these events to visualize and analyze open data. Surveys found that participants enjoyed networking and learning new skills. To improve future events, suggestions included providing more structure, guidance on open data, and ensuring enough time for projects. The hackathons helped the library and city collaborate to engage the community and realize the potential of open data.
DOES15 - Sherry Chang - Intel’s Journey to Large Scale DevOps Transformation Gene Kim
Sherry Chang, Enterprise Architect, Intel
Is it possible to transform large enterprises with 100’s of in-flight projects across myriad technology stacks and entrenched processes, requiring massive workforce re-skilling? In this session, I’ll share approaches we employed to increase the likelihood of success through DevOps adoption by:
-Offering of a common Continuous Delivery Service, similar to industry offerings from Codeship.io, CloudBees, and others
-Establishing a Maturity Model to help teams incrementally adopt DevOps practices
-Coaching teams through Kaizen sessions to eliminate bottlenecks and waste in their value stream
This document discusses different approaches to data preparation for business intelligence. It describes manual data preparation as time-intensive and not scalable. Large IT projects can automate data preparation but require high initial costs. Technology solutions provide a middle ground by offering collaborative data preparation tools that are quicker and cheaper than large projects but require new skills. The document then discusses Progress Easyl as an example technology solution, highlighting its features like uniting different data sources, filtering and enriching data, and sharing reports.
Repository Power: How Repositories can support Open Access Mandates (OR2015 O...OpenAIRE
OpenAIRE presentation at the Open Repositories Conference (OR2015), in Indianapolis, 10/Jun/2015 - Session - P4B: Supporting Open Scholarship and Open Science. Presented by Wolfram Horstmann (Univ. Goettingen) on behalf of the paper authors: Najla Rettberg, Jochen Schirrwagen, Pedro Principe, Eloy Rodrigues, José Carvalho, Paolo Manghi, Natalia Manola.
The Internet of Things and Developers: What the Enterprise Needs to KnowApigee | Google Cloud
Developers hold the key to realizing IoT. What do enterprises need to know?
Whatever your IoT vision is for the business, developers are the ones who are going to help make it a reality.
We uncover the results of an extensive first-party research where we explore the current state of IoT and how it differs from popular perception.
The webcast, led by Evans data and Apigee will address:
- What is the current state of IoT development?
- Is an IoT developer different from a mobile developer?
- What expectations exist around APIs, big data, cloud?
- How can enterprises realize value from IoT development decisions?
Download podcast: http://bit.ly/1EDYdHc
E2D3 is Opensource, Intaractive, Dynamic Data Visualization platform on Excel.
It's Easy, Useful, and Intuitive.
Use E2D3 app for powerful presentation of your data.
Charlie Sundling is the CEO of Pipeline Software and has over 25 years experience in computer science and project management. He will give a presentation on an artificial intelligence system developed jointly with US civil nuclear operators to improve management of complex reactor refueling projects. The presentation will discuss how the AI system was able to monitor thousands of tasks and communicate with hundreds of workers in parallel to analyze schedules every 30 seconds and distribute updates, taking over work that would otherwise require 200 additional human project managers. The case study showed results including a 90% reduction in status chasing, improved visibility and resource utilization, and avoiding project delays worth millions of dollars.
The Rationale for Continuous Delivery (The culture and practice of good softw...C4Media
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/1Ff5T3D.
Dave Farley discusses the problems raised by inefficient processes creating poor quality output, too late to capitalise on the expected business value, and proposes solutions to them. Filmed at qconlondon.com.
Dave Farley is a thought-leader in the field of Continuous Delivery, DevOps and Software Development in general. He is co-author of the Jolt-award winning book 'Continuous Delivery', a regular conference speaker, blogger and a contributor to the Reactive Manifesto.
Emergent Design: History, Concepts, and PrinciplesTechWell
Software design is about change. A good design facilitates adding features—and adding new developers to the team. Yet any change to the code impacts design and could damage existing functionality. Without design idioms and practices, the code can degrade into a "big ball of spaghetti” and a maintenance nightmare. Your team must know which decisions to make early in design and which to defer. Rob Myers reviews “families” of design attributes and practices, showing the common principles within each. Exploring emergent design by tracing how the concept itself has evolved and matured over time, Rob covers traditional attributes of good object-oriented code (cohesion, encapsulation, polymorphism, coupling); design patterns and the wisdom discovered within; S.O.L.I.D. principles—all culminating in emergent design, where simple (not easy) practices meet the simplest of guidelines, such as Kent Beck’s “Four Rules of Simple Design.” And the result is code that is easy to understand and delightful to work on.
This document provides an overview of a lecture on big data analytics given by Dr. Ching-Yung Lin. The key points covered in the lecture include:
- Definitions and characteristics of big data based on the 3V's of volume, velocity and variety.
- Techniques used for big data such as massive parallelism, distributed storage and processing, machine learning and data visualization.
- Factors that have enabled big data to become prominent in recent years like greater data collection, open source software and commodity hardware.
- Examples of big data platforms, databases and analytics techniques including Hadoop, Spark, NoSQL databases and graph databases.
- The large and growing market for big data
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
2. Agenda
• Data Visualization.
• INDAVI.
• INDAVI Features.
• What Do We Offer For Developers?
• Future Work
28/10/2015 Helwan University
3. Agenda
• Data Visualization.
• INDAVI.
• INDAVI Features.
• What Do We Offer For Developers?
• Future Work.
38/10/2015 Helwan University
4. Data Visualization : Why?
• 1 TRILLION
• Connected objects and devices on the planet generated data in 2015.
• 2.5 BILLION
• GB of new data is generated everyday.
48/10/2015 Helwan University
6. Data Visualization : Why?
68/10/2015 Helwan University
Understanding + Exploring = Meaning
7. Data Visualization : Why?
8/10/2015 Helwan University 7
Cont …
Medical Scatter Plot
• Learning From Data & Taking Decision.
8. What is our Innovation !!!
8/10/2015 Helwan University 8
9. Agenda
• Data Visualization.
• INDAVI.
• INDAVI Features.
• What Do We Offer For Developers?
• Future Work.
98/10/2015 Helwan University
10. Interactive Data Visualization : INDAVI
A smart cross platform framework.
Serves (Data analyst, Statistician and Computer scientist).
NOT only for users, but also for developers.
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Cont …
12. Interactive Data Visualization : INDAVI
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Cont …
Stock Market Line Chart
• What is the highest value?
SECShareValues
Number Of Hours
13. Agenda
• Data Visualization.
• INDAVI.
• INDAVI Features.
• What Do We Offer For Developers?
• Future Work.
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14. INDAVI Features
• Grammar Of Graphics ( GOG ).
• Graphs’ Linking.
• Manage large display using FTIR.
• Software Extensibility.
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16. INDAVI Feature #2 Graphs Talk Each Other!
• Innovation # 2
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Data Views
17. INDAVI Feature #2 Graphs Talk Each Other!
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Cont …
• Innovation # 2 ( For now and For The Future ).
Linked Data Views = Further Insight
18. INDAVI Feature #3 FTIR
• Innovation # 3 ( Large Display Problem )
Frustrated Total Internal Reflection
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Prepared By : INDAVI TEAM
19. INDAVI Feature #4 Extensibility.
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• Innovation # 4 ( Building new Graphs ).
Developer is using API only or by using terminal.
From Scratch
20. Agenda
• Data Visualization.
• INDAVI.
• INDAVI Features.
• What Do We Offer For Developers?
• Future Work.
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21. What Do We Offer For Developers?
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22. Agenda
• Data Visualization.
• INDAVI.
• INDAVI Features.
• What Do We Offer For Developers?
• Future Work
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23. What Is Next ?
• 3D Coordinates System.
• Apply Statistical Visualization Techniques.
• Apply Augmented Reality.
• Start New Cloud Version.
• Real-time Applications. ( Internet Of Things ).
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24. Summary
• Building Grammar Of Graphics ( No naming again ).
• Linking Between Graphs.
• Solving Large Display Problem using FTIR Technology .
• Software Extensibility.
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