Talk at the Wellington Web Design Meetup on April 8, 2010. Data visualization is used to communicate : To make a point, to form a hypothesis, to help achieve a goal.
Despite un-unprecedented technology innovation, since 2004, US labor productivity growth has been going down to a pathetic 0.5% per year. Why Technology doesn't drive growth anymore?
The Path to Maximize Big Data in the CloudHortonworks
More and more companies are taking the journey to become truly data driven. Cloud computing enables new levels of business agility for developers, IT, and data scientists while providing a pay-as-you-go model of unlimited scale and no upfront hardware costs to spin up clusters within minutes to start modeling and analyzing large data sets immediately. Understand who is moving to the cloud, what your peers think and other interesting stats!
This document discusses trends in business intelligence and analytics. It notes that the amount of digital data created annually is growing 40-60% per year. By 2019, the business intelligence and analytics market is projected to reach $23 billion. While most companies want to make decisions based on data, only 37% report being successful at it. The document advocates for empowering users with self-service business intelligence tools that automate processes and provide real-time insights. It also predicts that by 2020, natural language and artificial intelligence will be standard features in modern business intelligence platforms.
(1) The document discusses the current capabilities and limitations of artificial intelligence including what AI can do today such as safer autonomous vehicles, better medical imaging analysis, and information search and retrieval.
(2) It notes what AI still cannot do including develop common sense, act as intelligent personal assistants, have "smart" conversations, or function as household robots with agile dexterity.
(3) The document also references mistakes that humans would not make as well as how AI systems do not truly understand what they are discussing, and provides examples of early AI technologies from 1994 and how AI continues to progress through combinations with other technologies.
O documento repete várias vezes a mensagem "EQUIPE: eliasfarias.com.br – Venha pra cá você também", convidando as pessoas a se juntarem à equipe no site eliasfarias.com.br.
This document discusses the theory of data visualization. It emphasizes showing data with clarity, precision and efficiency according to Edward Tufte. Anscombe's Quartet example shows graphs can be misleading without examining the underlying data. Effective graphs have high data-ink ratios, are free of chartjunk like unnecessary grids or patterns, and accurately represent relationships. Data should not be distorted to strengthen effects. The document also discusses redesigning graphs to reduce clutter and better integrate data and text.
Fresh Thinking on Communicating with DataAndy Kirk
This document summarizes a webinar presentation by Andy Kirk on fresh thinking for communicating with data visualization. The webinar covered six types of thinking that can help data visualizers approach their work in a fresh way: contextual thinking, imaginative thinking, journalistic thinking, critical thinking, organized thinking, and thinking based on personal convictions. Kirk provided examples to illustrate each type of thinking and emphasized embracing fresh perspectives to create effective visualizations.
The document announces the 7th annual international workshop on Lifelong Learning within European Frameworks to be held in April 2016 in Mogilev, Belarus. The workshop will bring together academics, educators, and experts from various European states to promote collaboration, share new findings and concepts, and help develop common European education frameworks. It provides important dates, submission guidelines, registration information, and contact details for the event.
Despite un-unprecedented technology innovation, since 2004, US labor productivity growth has been going down to a pathetic 0.5% per year. Why Technology doesn't drive growth anymore?
The Path to Maximize Big Data in the CloudHortonworks
More and more companies are taking the journey to become truly data driven. Cloud computing enables new levels of business agility for developers, IT, and data scientists while providing a pay-as-you-go model of unlimited scale and no upfront hardware costs to spin up clusters within minutes to start modeling and analyzing large data sets immediately. Understand who is moving to the cloud, what your peers think and other interesting stats!
This document discusses trends in business intelligence and analytics. It notes that the amount of digital data created annually is growing 40-60% per year. By 2019, the business intelligence and analytics market is projected to reach $23 billion. While most companies want to make decisions based on data, only 37% report being successful at it. The document advocates for empowering users with self-service business intelligence tools that automate processes and provide real-time insights. It also predicts that by 2020, natural language and artificial intelligence will be standard features in modern business intelligence platforms.
(1) The document discusses the current capabilities and limitations of artificial intelligence including what AI can do today such as safer autonomous vehicles, better medical imaging analysis, and information search and retrieval.
(2) It notes what AI still cannot do including develop common sense, act as intelligent personal assistants, have "smart" conversations, or function as household robots with agile dexterity.
(3) The document also references mistakes that humans would not make as well as how AI systems do not truly understand what they are discussing, and provides examples of early AI technologies from 1994 and how AI continues to progress through combinations with other technologies.
O documento repete várias vezes a mensagem "EQUIPE: eliasfarias.com.br – Venha pra cá você também", convidando as pessoas a se juntarem à equipe no site eliasfarias.com.br.
This document discusses the theory of data visualization. It emphasizes showing data with clarity, precision and efficiency according to Edward Tufte. Anscombe's Quartet example shows graphs can be misleading without examining the underlying data. Effective graphs have high data-ink ratios, are free of chartjunk like unnecessary grids or patterns, and accurately represent relationships. Data should not be distorted to strengthen effects. The document also discusses redesigning graphs to reduce clutter and better integrate data and text.
Fresh Thinking on Communicating with DataAndy Kirk
This document summarizes a webinar presentation by Andy Kirk on fresh thinking for communicating with data visualization. The webinar covered six types of thinking that can help data visualizers approach their work in a fresh way: contextual thinking, imaginative thinking, journalistic thinking, critical thinking, organized thinking, and thinking based on personal convictions. Kirk provided examples to illustrate each type of thinking and emphasized embracing fresh perspectives to create effective visualizations.
The document announces the 7th annual international workshop on Lifelong Learning within European Frameworks to be held in April 2016 in Mogilev, Belarus. The workshop will bring together academics, educators, and experts from various European states to promote collaboration, share new findings and concepts, and help develop common European education frameworks. It provides important dates, submission guidelines, registration information, and contact details for the event.
Separating Myth from Truth in Data VisualisationAndy Kirk
This document outlines an agenda for a one-day workshop on data visualization and infographic design. The workshop aims to challenge existing thinking about creating and consuming visualizations, equip attendees with an appreciation of analytical and design choices, provide practice opportunities, and inspire attendees. The agenda covers fundamentals, the design methodology, data representation types, color theory, interactivity, and tools. Exercises are integrated throughout. The trainer, Andy Kirk, has extensive experience delivering visualization training globally.
The document discusses different types of data that can be visualized, including entities, relationships, attributes, and operations. It describes entities as objects of interest and relationships as structures that relate entities. Attributes are properties of entities or relationships, and can have multiple dimensions. The document also discusses types of numbers according to Stanley Smith Stevens' taxonomy, including nominal, ordinal, interval, and ratio scales. Finally, it covers data aggregations at different levels from individual transactions to factoids.
Designing Data Visualizations to Strengthen Health SystemsAmanda Makulec
Slide deck from our hands-on workshop hosted at the 4th Global Symposium on Health Systems Research, focused on basic design tips, tricks, and best practices to improve your charts and graphs.
Information visualisation: Data ink design principlesErik Duval
The document discusses Erik Duval's presentation on Edward Tufte's principles of data ink design. It outlines Tufte's key principles: showing the data above all else, maximizing the data-ink ratio by removing non-data ink, erasing redundant data ink, and revising and editing visualizations. The data-ink ratio refers to the proportion of ink devoted to displaying non-redundant data information. The principles aim to clearly display the maximum amount of data with the minimum amount of graphical elements.
Data Visualisation and Infographic Design: 'State of the Union'Andy Kirk
This document is a presentation by Andy Kirk on the state of data visualization and infographic design. It covers various projects in these areas, techniques used, relevant technologies, issues in the field, the marketplace for data visualization professionals, and predictions for 2014 and beyond. The presentation includes numerous examples and links to specific works and resources within each topic.
Data Visualisation Literacy - Learning to SeeAndy Kirk
This document discusses factors that influence the consumption and creation of effective data visualizations. It explores both sides of visualization literacy - reading/consuming visualizations and creating them. Key factors discussed for consumption include subject matter/relevance, trust/prejudice, skills/confidence, time/pressure, and emotions. For creation, the document advises defining audiences, being transparent about methods, offering guidance for complex charts, fitting the purpose/setting, and having conviction while avoiding overload. The goal is to better understand how the general public engages with visualizations and help both everyday people and professionals improve visualization literacy.
These slides are from recent talks by Andy Kirk of visualisingdata.com. The subject refers to the many different mindsets or roles that are required to be fulfilled for the effective design of data visualisation.
This document discusses data visualization and provides guidance on best practices. It outlines the data visualization process from defining goals and gathering data to designing visualizations, developing them, and delivering the final product. It emphasizes that effective visualization tells a story that draws the viewer into the data. Common pitfalls and tools are also mentioned.
This document provides an overview of big data. It defines big data as large volumes of diverse data that are growing rapidly and require new techniques to capture, store, distribute, manage, and analyze. The key characteristics of big data are volume, velocity, and variety. Common sources of big data include sensors, mobile devices, social media, and business transactions. Tools like Hadoop and MapReduce are used to store and process big data across distributed systems. Applications of big data include smarter healthcare, traffic control, and personalized marketing. The future of big data is promising with the market expected to grow substantially in the coming years.
An immersive workshop at General Assembly, SF. I typically teach this workshop at General Assembly, San Francisco. To see a list of my upcoming classes, visit https://generalassemb.ly/instructors/seth-familian/4813
I also teach this workshop as a private lunch-and-learn or half-day immersive session for corporate clients. To learn more about pricing and availability, please contact me at http://familian1.com
3 Things Every Sales Team Needs to Be Thinking About in 2017Drift
Thinking about your sales team's goals for 2017? Drift's VP of Sales shares 3 things you can do to improve conversion rates and drive more revenue.
Read the full story on the Drift blog here: http://blog.drift.com/sales-team-tips
Creating a Data-Driven Government: Big Data With PurposeTyrone Grandison
The U.S. Department of Commerce collects, processes and disseminates data on a range of issues that impact our nation. Whether it's data on the economy, the environment, or technology, data is critical in fulfilling the Department's mission of creating the conditions for economic growth and opportunity. It is this data that provides insight, drives innovation, and transforms our lives. The U.S. Department of Commerce has become known as "America's Data Agency" due to the tens of thousands of datasets including satellite imagery, material standards and demographic surveys.
But having a host of data and ensuring that this data is open and accessible to all are two separate issues. The latter, expanding open data access, is now a key pillar of the Commerce Department's mission. It was this focus on enhancing open data that led to the creation of the Commerce Data Service (CDS).
The mission at the Commerce Data Service is to enable more people to use big data from across the department in innovative ways and across multiple fields. In this talk, I will explore how we are using big data to create a data-driven government.
This talk is a keynote given at the Texas tech University's Big Data Symposium.
This document outlines a presentation on big data for development (BD4D). It discusses the rise of big data and how BD4D techniques like data analytics can be applied. Potential BD4D applications include healthcare, emergency response, and agriculture. Data sources include mobile phones, crowdsourcing, and social media. The presentation also covers BD4D research in Pakistan using mobile data and challenges like data bias, privacy and causation. Open research areas are suggested to further mitigate challenges and advance predictive and multimodal BD4D analytics.
This document discusses the challenges facing IT departments in adapting to new technologies and rising user expectations in the mobile-cloud era. It notes that citizens and government employees now expect access to applications and data from any device. However, IT departments face budget constraints, legacy systems, skills shortages, and increasing security threats from cybercrime. The document examines the strategic options available to IT, such as providing mobile access, using data-driven security, building a hybrid cloud infrastructure, and adopting agile development practices. It emphasizes that IT departments must develop transformation strategies, enable technology changes, and become operationally agile in order to adapt successfully to this new environment.
This document discusses data science innovations and systems of insight. It provides examples of new data sources like social media language and drone/mobile sensor data that can generate novel insights. Systems of insight use machine learning and natural language generation to automatically analyze data, detect patterns, and present findings and narratives to users without extensive data preparation. This approach reduces the time spent on data wrangling and moves organizations from crisis-level talent shortages to faster decision making. The document advocates starting to use innovative data sources and systems of insight to generate customer insights, optimize processes, and gain a competitive advantage.
지난 4월 3일에 대전 KAIST 증강현실연구센터 콜로키움에서 발표한 자료입니다.
‘Digital Twin’ is a digital replication of real world objects, processes, phenomena that can be used for various purposes. Digital twin concept backs to manufacturing industry in early 2000s for the PLM (Product Lifecycle Management) purposes. It is based on the idea that a digital informational construct about a physical system could be created as an entity on its own. As cities are going through digital transformation, there are many attempts to apply digital twin concept to manage urban issues. Those attempts look set to play an increasingly important role in the creation of smart cities around the world and in addressing major public health, safety and environmental issues. Bringing the virtual and real worlds together in this way can help to give better analysis, visualization, and simulation to decision-making process. This will be a multi-way process with iterative feedback among stakeholders. In this colloquium, I talked about the recent trends of Smart City from the perspective of digital twin.
The Crisis of Self Sovereignty in The Age of Surveillance CapitalismJongseung Kim
Surveillance capitalism is a new economic system that claims human experience as free raw material for hidden commercial practices of extraction, prediction, and sales. It relies on accumulating behavioral surplus data from users and using machine learning to generate prediction products that are sold to businesses. This allows firms like Google to convert behavioral surplus directly into revenue. The amount of surplus accumulated affects the accuracy of predictions, driving firms to amass ever greater stores of behavioral data for continued profits in behavioral futures markets.
All Things Open 2014 - Day 1
Wednesday, October 22nd, 2014
Jason Hare
Director of Open Data of the Open Data Institute
Open Government/Open Data
Sustainable Open Data Markets
Heavy, Messy, Misleading: How Big Data is a human problem, not a tech onePulsar Platform
This document discusses how big data is primarily a human problem rather than a technological one. It argues that while technology enables the collection and analysis of vast amounts of data, humans define the problems, frame the questions, and interpret the results, which can be biased. The document also notes that while a lot of data is collected, most is never analyzed due to challenges in preparing, standardizing, and making sense of large, messy datasets. Overall, big data represents an innovation in human decision-making and problem-solving rather than just a technical advancement.
Separating Myth from Truth in Data VisualisationAndy Kirk
This document outlines an agenda for a one-day workshop on data visualization and infographic design. The workshop aims to challenge existing thinking about creating and consuming visualizations, equip attendees with an appreciation of analytical and design choices, provide practice opportunities, and inspire attendees. The agenda covers fundamentals, the design methodology, data representation types, color theory, interactivity, and tools. Exercises are integrated throughout. The trainer, Andy Kirk, has extensive experience delivering visualization training globally.
The document discusses different types of data that can be visualized, including entities, relationships, attributes, and operations. It describes entities as objects of interest and relationships as structures that relate entities. Attributes are properties of entities or relationships, and can have multiple dimensions. The document also discusses types of numbers according to Stanley Smith Stevens' taxonomy, including nominal, ordinal, interval, and ratio scales. Finally, it covers data aggregations at different levels from individual transactions to factoids.
Designing Data Visualizations to Strengthen Health SystemsAmanda Makulec
Slide deck from our hands-on workshop hosted at the 4th Global Symposium on Health Systems Research, focused on basic design tips, tricks, and best practices to improve your charts and graphs.
Information visualisation: Data ink design principlesErik Duval
The document discusses Erik Duval's presentation on Edward Tufte's principles of data ink design. It outlines Tufte's key principles: showing the data above all else, maximizing the data-ink ratio by removing non-data ink, erasing redundant data ink, and revising and editing visualizations. The data-ink ratio refers to the proportion of ink devoted to displaying non-redundant data information. The principles aim to clearly display the maximum amount of data with the minimum amount of graphical elements.
Data Visualisation and Infographic Design: 'State of the Union'Andy Kirk
This document is a presentation by Andy Kirk on the state of data visualization and infographic design. It covers various projects in these areas, techniques used, relevant technologies, issues in the field, the marketplace for data visualization professionals, and predictions for 2014 and beyond. The presentation includes numerous examples and links to specific works and resources within each topic.
Data Visualisation Literacy - Learning to SeeAndy Kirk
This document discusses factors that influence the consumption and creation of effective data visualizations. It explores both sides of visualization literacy - reading/consuming visualizations and creating them. Key factors discussed for consumption include subject matter/relevance, trust/prejudice, skills/confidence, time/pressure, and emotions. For creation, the document advises defining audiences, being transparent about methods, offering guidance for complex charts, fitting the purpose/setting, and having conviction while avoiding overload. The goal is to better understand how the general public engages with visualizations and help both everyday people and professionals improve visualization literacy.
These slides are from recent talks by Andy Kirk of visualisingdata.com. The subject refers to the many different mindsets or roles that are required to be fulfilled for the effective design of data visualisation.
This document discusses data visualization and provides guidance on best practices. It outlines the data visualization process from defining goals and gathering data to designing visualizations, developing them, and delivering the final product. It emphasizes that effective visualization tells a story that draws the viewer into the data. Common pitfalls and tools are also mentioned.
This document provides an overview of big data. It defines big data as large volumes of diverse data that are growing rapidly and require new techniques to capture, store, distribute, manage, and analyze. The key characteristics of big data are volume, velocity, and variety. Common sources of big data include sensors, mobile devices, social media, and business transactions. Tools like Hadoop and MapReduce are used to store and process big data across distributed systems. Applications of big data include smarter healthcare, traffic control, and personalized marketing. The future of big data is promising with the market expected to grow substantially in the coming years.
An immersive workshop at General Assembly, SF. I typically teach this workshop at General Assembly, San Francisco. To see a list of my upcoming classes, visit https://generalassemb.ly/instructors/seth-familian/4813
I also teach this workshop as a private lunch-and-learn or half-day immersive session for corporate clients. To learn more about pricing and availability, please contact me at http://familian1.com
3 Things Every Sales Team Needs to Be Thinking About in 2017Drift
Thinking about your sales team's goals for 2017? Drift's VP of Sales shares 3 things you can do to improve conversion rates and drive more revenue.
Read the full story on the Drift blog here: http://blog.drift.com/sales-team-tips
Creating a Data-Driven Government: Big Data With PurposeTyrone Grandison
The U.S. Department of Commerce collects, processes and disseminates data on a range of issues that impact our nation. Whether it's data on the economy, the environment, or technology, data is critical in fulfilling the Department's mission of creating the conditions for economic growth and opportunity. It is this data that provides insight, drives innovation, and transforms our lives. The U.S. Department of Commerce has become known as "America's Data Agency" due to the tens of thousands of datasets including satellite imagery, material standards and demographic surveys.
But having a host of data and ensuring that this data is open and accessible to all are two separate issues. The latter, expanding open data access, is now a key pillar of the Commerce Department's mission. It was this focus on enhancing open data that led to the creation of the Commerce Data Service (CDS).
The mission at the Commerce Data Service is to enable more people to use big data from across the department in innovative ways and across multiple fields. In this talk, I will explore how we are using big data to create a data-driven government.
This talk is a keynote given at the Texas tech University's Big Data Symposium.
This document outlines a presentation on big data for development (BD4D). It discusses the rise of big data and how BD4D techniques like data analytics can be applied. Potential BD4D applications include healthcare, emergency response, and agriculture. Data sources include mobile phones, crowdsourcing, and social media. The presentation also covers BD4D research in Pakistan using mobile data and challenges like data bias, privacy and causation. Open research areas are suggested to further mitigate challenges and advance predictive and multimodal BD4D analytics.
This document discusses the challenges facing IT departments in adapting to new technologies and rising user expectations in the mobile-cloud era. It notes that citizens and government employees now expect access to applications and data from any device. However, IT departments face budget constraints, legacy systems, skills shortages, and increasing security threats from cybercrime. The document examines the strategic options available to IT, such as providing mobile access, using data-driven security, building a hybrid cloud infrastructure, and adopting agile development practices. It emphasizes that IT departments must develop transformation strategies, enable technology changes, and become operationally agile in order to adapt successfully to this new environment.
This document discusses data science innovations and systems of insight. It provides examples of new data sources like social media language and drone/mobile sensor data that can generate novel insights. Systems of insight use machine learning and natural language generation to automatically analyze data, detect patterns, and present findings and narratives to users without extensive data preparation. This approach reduces the time spent on data wrangling and moves organizations from crisis-level talent shortages to faster decision making. The document advocates starting to use innovative data sources and systems of insight to generate customer insights, optimize processes, and gain a competitive advantage.
지난 4월 3일에 대전 KAIST 증강현실연구센터 콜로키움에서 발표한 자료입니다.
‘Digital Twin’ is a digital replication of real world objects, processes, phenomena that can be used for various purposes. Digital twin concept backs to manufacturing industry in early 2000s for the PLM (Product Lifecycle Management) purposes. It is based on the idea that a digital informational construct about a physical system could be created as an entity on its own. As cities are going through digital transformation, there are many attempts to apply digital twin concept to manage urban issues. Those attempts look set to play an increasingly important role in the creation of smart cities around the world and in addressing major public health, safety and environmental issues. Bringing the virtual and real worlds together in this way can help to give better analysis, visualization, and simulation to decision-making process. This will be a multi-way process with iterative feedback among stakeholders. In this colloquium, I talked about the recent trends of Smart City from the perspective of digital twin.
The Crisis of Self Sovereignty in The Age of Surveillance CapitalismJongseung Kim
Surveillance capitalism is a new economic system that claims human experience as free raw material for hidden commercial practices of extraction, prediction, and sales. It relies on accumulating behavioral surplus data from users and using machine learning to generate prediction products that are sold to businesses. This allows firms like Google to convert behavioral surplus directly into revenue. The amount of surplus accumulated affects the accuracy of predictions, driving firms to amass ever greater stores of behavioral data for continued profits in behavioral futures markets.
All Things Open 2014 - Day 1
Wednesday, October 22nd, 2014
Jason Hare
Director of Open Data of the Open Data Institute
Open Government/Open Data
Sustainable Open Data Markets
Heavy, Messy, Misleading: How Big Data is a human problem, not a tech onePulsar Platform
This document discusses how big data is primarily a human problem rather than a technological one. It argues that while technology enables the collection and analysis of vast amounts of data, humans define the problems, frame the questions, and interpret the results, which can be biased. The document also notes that while a lot of data is collected, most is never analyzed due to challenges in preparing, standardizing, and making sense of large, messy datasets. Overall, big data represents an innovation in human decision-making and problem-solving rather than just a technical advancement.
Heavy, Messy, Misleading: why Big Data is a human problem, not a tech onePulsar
"Big data" has been around for a few years now but for every hundred people talking about it there’s probably only one actually doing it. As a result Big Data has become the preferred vehicle for inflated expectations and misguided strategy.
As always, the seed of the issue is in the expression itself. Big Data is not so much about a quality of the data or the tools to mine it, it’s about a new approach to product, policy or business strategy design. And that’s way harder and trickier to implement than any new technology stack.
In this talk we look at where Big Data is going, what are the real opportunities, limitations and dangers and what can we do to stop talking about it and start doing it today.
The REAL Impact of Big Data on PrivacyClaudiu Popa
The awesome promise of Big Data is tempered by the need to protect personal information. Data scientists must expertly navigate the legislative waters and acquire the skills to protect privacy and security. This talk provides enterprise leaders with answers and suggests questions to ask when the time comes to consider the vast opportunities offered by big data.
Heavy, messy, misleading. Why Big Data is a human problem, not a technology one.Francesco D'Orazio
"Big data" has been around for a few years now but for every hundred people talking about it there’s probably only one actually doing it. As a result Big Data has become the preferred vehicle for inflated expectations and misguided strategy.
As always, language holds the key and the seed of the issue is reflected in the expression itself. "Big Data" is not so much about a quality of the data or the tools to mine it, it’s about a new approach to product, policy or business strategy design. And that’s way harder and trickier to implement than any new technology stack.
In this talk I look at where Big Data is going, what are the real opportunities, limitations and dangers and what can we do to stop talking about it and start doing it today.
This document summarizes how the role of data has grown exponentially since 2010 when the term "big data" was introduced. Some key points made are:
- The amount of data in the world doubles every two years and is predicted to reach 44 zettabytes by 2020.
- 80% of data is now unstructured, presenting new data management challenges.
- Many governments have made more data openly accessible, and countries with more open data tend to be less corrupt.
- Advances in data and artificial intelligence are automating many jobs but also improving recruitment, project management, and other business functions for companies that master how to leverage data.
Big data and analytics are held in high regard by agencies worldwide, but implementing government programs remains challenging. Bloomberg Businessweek Research Services and SAP launched a global survey in summer 2013 to analyze the views of public sector executives on the use and benefits of analytics.
Catalant CEO and Co-Founder, Rob Biederman, presented at the Future of Work Austin event in March of 2017. In this presentation, he shares his thoughts on the history of work and what changes we can expect in the coming years. Work is being reimagined; learn how your company can get ahead of this shift.
The document discusses how big data analytics is impacting the IT industry and what CIOs must do to incorporate big data analytics. It notes that we are becoming a big data, mobile, and real-time nation. By 2015, big data is predicted to generate millions of new IT jobs in areas like data collection, analysis, mobile technology, social media, and cloud computing. The rise of big data requires CIOs to adapt their approach to information governance and develop strategies to manage growing amounts of unstructured data.
This document summarizes the history of big data from 1944 to 2013. It outlines key milestones such as the first use of the term "big data" in 1997, the growth of internet traffic in the late 1990s, Doug Laney coining the three V's of big data in 2001, and the focus of big data professionals shifting from IT to business functions that utilize data in 2013. The document serves to illustrate how data storage and analysis have evolved over time due to technological advances and changing needs.
BigData & Supply Chain: A "Small" IntroductionIvan Gruer
In the frame of the master in logistic LOG2020, a brief presentation about BigData and its impacts on Supply Chains at IUAV.
Topics and contents have been developed along the research for the MBA final dissertation at MIB School of Management.
Similar to Data Visualisation by Olivier Lorrain (20)
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
2. Data Visualisation “The main goal of data visualization is its ability to visualize data, communicating information clearly and effectivelty.” Vital Friedman, editor-in-chief of www.smashingmagazine.com
3. To Make a Point Impact of One child policy 1979 Source: www.census.gov/ipc/www/idb/informationGateway.php
4. To Form a Hypothesis China’s Population: 1 330 000 000 Which country will be the most populous in 2030? India’s Population: 1 173 000 000 Source: www.census.gov/ipc/www/idb/informationGateway.php
5. To Help Achieve a Goal Task in a Power plant: Monitor Temperature of Liquid B Temperature (C) Temperature (C) 56.2 Digital Dial
6. To Help Achieve a Goal Task in a Power plant: Monitor Temperature of Liquid B Temperature (C) Threshold Threshold Time (min)
7.
8.
9.
10.
11. Dull Table or Animated Data 3800 US stores in 2005 Growth of WalMart blog.kiwitobes.com/?p=51
19. Data visualisation could be a powerful communication tool Always bear in mind the users / audience of the data visualisation Key Points
20. Toby Segaran - http://kiwitobes.com Gap Minder – Debunking myths about the “third world” www.gapminder.org/videos/ted-talks/hans-rosling-ted-2006-debunking-myths-about-the-third-world/ Data Visualisation tools www.yworks.com/en/products.html www.graphviz.org/ Edward Tufte – Visual Explanationswww.edwardtufte.com/tufte Further Reading
21. Free data Freebase – www.freebase.com OECD - http://stats.oecd.org/index.aspx Statistic NZ - http://search.stats.govt.nz/nav/0 Demographic David Foot, Boom, Bust and Echo - http://www.footwork.com/book.asp Further Reading