Understanding big data-drupalcamp
Download as ODP, PDF1 like340 views
An introductory talk about how to think in big data projects. This talk should help you to change your mindset so you know which problems you should focus on when working on these kind of projects. This talk was done at the 2015 drupalcamp in Spain. The talk was in Spanish, but the slides are in English. You can watch the talk here: https://vimeo.com/128898996
1 of 50
Download to read offline
Recommended
Big data
Big dataArpit Mittal This document discusses big data and how it is affecting organizations. It notes that large amounts of data are being generated daily from sources like the New York Stock Exchange, Facebook, Ancestry.com, and the Internet Archive. Big data is transforming how businesses operate and impacting other parts of life. Hadoop is presented as a programming framework that can help organizations better manage and process massive amounts of data across different tools and platforms.
Big Data - Yesterday, Today and Tomorrow by John Mashey, Techviser
Big Data - Yesterday, Today and Tomorrow by John Mashey, TechviserAngela Hey A history of Big Data by Dr John Mashey. It discusses 1890 census data, IBM mainframes, DEC minicomputer clusters, Silicon Graphics (SGI) applications and a history of Open Source computing.
A Brief History Of Data
A Brief History Of DataDamien Dallimore This document provides a brief history of data from ancient times to the present day. It discusses how humans started counting and recording data visually over 20,000 years ago. Written language emerged around 3,500 BC allowing data to be recorded and transmitted. Major developments include the first library in 1250 BC to store data in mass, the origin of maps in 1150 BC, and using numbers and logic to derive insights from 100 BC to 350 BC. Significant milestones from 1600 to 1900 include the development of statistics, computers, programming languages, data standards, and the internet. Today's "big data" landscape is characterized by volume, variety, velocity, and veracity of data being created. The future will involve understanding data through insights
Bettakultcha June 2014 presentation: big and open data
Bettakultcha June 2014 presentation: big and open dataSimon Wilson Five minutes. 15 seconds per slide. Trying to explain, simply, big data and open data, the differences, and why we should try to embrace them.
Big data VN-INFO meet-up
Big data VN-INFO meet-upSon Nguyen Kim This document discusses big data and the challenges of working with large datasets. It notes that every 2 days now as much data is created as was created from the beginning of civilization until 2003. The Hadoop ecosystem, including tools like MapReduce and machine learning, are proposed solutions for analyzing large and diverse datasets, but challenges remain around usability, speed of analysis, and finding new applications beyond web logs.
A brief history of "big data"
A brief history of "big data"Nicola Ferraro The history of Big Data from the beginning to Spark. An introduction to the big data software tools for developers and data analysts.
1
1AbhijitThakuria2 This document discusses information storage and its importance. It notes that as individuals and businesses create large amounts of digital information every day, storage is needed to store, manage, and retrieve that information. Different types of storage devices exist for different types of data and usage rates. Common storage media include hard drives, flash drives, CDs/DVDs, memory cards, and cloud storage. The document emphasizes that while most information is created by individuals, it is typically stored and managed by large organizations in data centers.
Nosql public
Nosql publicSourajitBasak The document discusses the limitations of relational database management systems (RDBMS) in handling large amounts of complex data, and the rise of NoSQL databases as an alternative. It notes that companies like Google, Facebook, Amazon developed their own non-relational database systems like BigTable, Cassandra, and DynamoDB. The document then categorizes the main types of NoSQL databases as key-value stores, graph databases, and document stores. It argues that a hybrid model combining the best aspects of different database types may be most effective at handling large, complex datasets from many different sources and applications.
How to use git without rage
How to use git without rageJavier Lafora Rey This document provides an overview of using Git version control system, including:
1. The different types of version control systems like local (LVCS), centralized (CVCS), and distributed (DVCS) like Git.
2. Basic Git commands and workflows for creating a repository, adding/committing files, tagging versions, branching, merging, and working with remotes.
3. Examples of common branching workflows for topics, long-running branches, hotfixes, and merging branches with conflicts.
4. How to push/pull from remote repositories, delete remote branches, and work with tracking branches.
Git basics a starter on git and its ecosystem
Git basics a starter on git and its ecosystemFrançois D'Agostini Git is a distributed version control system that allows for non-linear development. It uses a local repository that tracks snapshots of files rather than file differences. The document discusses how to configure Git, create repositories, make commits, view commit histories, work with branches, merge branches, resolve conflicts, work with remote repositories, and leverage tools like Git stash and Git hosting platforms. Popular branching strategies like Git flow are also covered that establish best practices for team collaboration.
APIs para gente normal
APIs para gente normalJavier Lafora Rey Una breve introducción que explica lo que es un API y por qué deberíamos saber en qué consiste, sin bajar al plano técnico.
La charla se dio en theapihour, dentro del zincshower (2014)
Ruby object model: A matter of life and death
Ruby object model: A matter of life and deathJavier Lafora Rey Ruby object model internals for MRI. These slides have some animations, so if you want to see them all, you should download it. Created with libreoffice impress
Databases in Qt
Databases in Qtdanitiger33 This document discusses using Qt for SQL database access and modeling. It describes how QSqlDatabase provides an interface for database connections, and drivers like QODBC can be used for specific databases like SQL Server. It also covers executing queries with QSqlQuery, retrieving result sets, and using QSqlTableModel to present database contents in a view like QListView for CRUD operations. Record-level access and filtering are demonstrated.
API REST for beginners or why you should make your API understandable
API REST for beginners or why you should make your API understandableJavier Lafora Rey This document provides an introduction to building RESTful APIs for beginners. It discusses the history and evolution of APIs from early web technologies like widgets and web scraping to modern standards like SOAP and REST. It then covers key REST concepts like using HTTP methods to specify actions, addressing resources uniquely through URIs, making requests and responses self-descriptive through embedded hyperlinks, and designing APIs that are stateless and cacheable. The document provides examples of RESTful API design and best practices for documentation, data formatting, and versioning.
Big Data
Big DataPriyanka Tuteja This document discusses big data, including what it is, common data sources, its volume, velocity and variety characteristics, solutions like Hadoop and its HDFS and MapReduce components, and the impact and future of big data. It explains that big data refers to large and complex datasets that are difficult to process using traditional tools. Hadoop provides a framework to store and process big data across clusters of commodity hardware.
Big data(1st presentation)
Big data(1st presentation)Takrim Ul Islam Laskar Big Data Is an Advanced Database System, which is in use by all the gigantic institutes like facebook,google,etc
Presentation on BigData by Swapnaja 
Presentation on BigData by Swapnaja Swapnaja Tandale The document discusses big data and how it is being generated from various sources like social media, sensors, and mobile devices. It describes the key characteristics of big data known as the three V's - volume, velocity and variety. It then explains how Hadoop uses HDFS for storage and MapReduce for processing large datasets in parallel across clusters of computers. The conclusion states that big data presents both opportunities and challenges for industries in creating value from large and diverse datasets.
Data mining with big data
Data mining with big dataSandip Tipayle Patil This document discusses big data and data mining. It defines big data as large volumes of structured and unstructured data that are difficult to process using traditional techniques due to their size. It outlines the 4 Vs of big data: volume, velocity, variety, and veracity. The proposed system would use distributed parallel computing with Hadoop to identify relationships in huge amounts of data from different sources and dimensions. It discusses challenges of big data like data location, volume, privacy, and gaining insights. Solutions involve parallel programming, distributed storage, and access restrictions.
Big Data Presentation
Big Data PresentationRitika Barethia Detailed description of big data, with the characteristics of it. What are the limitations of the traditional systems? Where we are using big data? And also the applications of big data.
Big Data
Big DataRaja Ram Dutta Big data refers to large and complex datasets that are difficult to process using traditional data management tools. As data grows from gigabytes to terabytes to petabytes, new techniques are needed to store, process, and analyze this data. Hadoop is an open-source framework that uses distributed storage and processing to handle big data across clusters of computers. It includes HDFS for storage and MapReduce as a programming model for distributed processing of large datasets in parallel.
Spectra Logic BlackPearl Developer Summit 2015
Spectra Logic BlackPearl Developer Summit 2015spectralogic Slides from Spectra Logic’s inaugural BlackPearl Developer Summit, a virtual conference for current and potential Spectra Logic developers. You’ll get product updates from our CEO and BlackPearl product manager, and you will learn how these new features will help customers and developers. You will learn how to build a Spectra S3 client for BlackPearl, our private cloud gateway to our tape and disk storage systems. You will see how one of our partners developed a client and watch it in action. And you will get to ask questions to our BlackPearl Engineering team. Watch the Summit recording at https://www.youtube.com/watch?v=GYoSwrvhVM0
The Internet-of-things: Architecting for the deluge of data
The Internet-of-things: Architecting for the deluge of databcantrill The document discusses the challenges of managing the massive amount of data that will be generated by the Internet of Things (IoT). It argues that storing all raw IoT data authoritatively and allowing for hypothesis exploration through computation will require new approaches. ZFS storage combined with OS-level containers through systems like Manta may provide a way to cope with IoT-generated data at scale while enabling flexible analysis of non-fungible data. The document also discusses how Unix and its model of small, interconnected programs was well-suited for ad hoc data processing tasks.
PUC Masterclass Big Data
PUC Masterclass Big DataArjen de Vries This document provides an overview of a masterclass on big data presented by Prof.dr.ir. Arjen P. de Vries. It discusses defining properties of big data, challenges in big data analytics including capturing, aligning, transforming, modeling and understanding large datasets. It also briefly introduces map-reduce and streaming data analysis. Examples of large datasets that could be analyzed are provided, such as the sizes of datasets from Facebook, Google and other organizations.
Conservation keeping up with technology
Conservation keeping up with technologyDick Eastman The document discusses the latest preservation technology for genealogists, focusing on ensuring genealogy data remains readable in the future and how to easily share data. It covers traditional methods like paper, which is fragile, and microfilm, which requires optimal storage conditions. Modern options discussed include digitizing files and storing multiple backups on different media like CDs, DVDs, drives and cloud services. Cloud computing allows sharing data online while maintaining control. Technologies like smartphones and tablets have made genealogy research more portable and collaborative. Overall the document promotes digitizing and securely backing up data across various media to preserve family history for generations to come.
big-data-notes1.ppt
big-data-notes1.pptSutanuGhosal1 Data analytics is needed everywhere to predict relevant outcomes, increase profits, and efficiently use resources. It involves transforming processed information into knowledge. Companies use data analytics to understand customer behavior and target them with personalized advertisements and offers. Different types of data include structured, semi-structured, unstructured, and big data. Big data is high volume, high velocity, and highly variable information that requires novel processing techniques. Hadoop is an open source software framework that allows distributed processing of big data across clusters of computers using simple programming models like MapReduce. Data analytics helps analyze these different data types to provide business insights.
Bigdata processing with Spark
Bigdata processing with SparkArjen de Vries This document provides information about big data and Hadoop. It discusses how big data is defined in terms of large volumes, variety of data types, and velocity of data ingestion. It then summarizes the MapReduce programming model used in Hadoop for distributed processing of large datasets in parallel across clusters. Key aspects covered include how MapReduce handles scheduling, data distribution, synchronization, and fault tolerance. The document also notes some of the deficiencies of Hadoop, such as sources of latency, its lack of indexes, and its limitations for complex multi-step data analysis workflows.
BIG DATA
BIG DATADr. Shashank Shetty Concepts of Big data and some of the tools used for solving Big Data is Explained in this Presentation
Big Data & Hadoop Introduction
Big Data & Hadoop IntroductionJayant Mukherjee Disclaimer :
The images, company, product and service names that are used in this presentation, are for illustration purposes only. All trademarks and registered trademarks are the property of their respective owners.
Data/Image collected from various sources from Internet.
Intention was to present the big picture of Big Data & Hadoop
Big Data = Big Decisions
Big Data = Big DecisionsInnoTech This document discusses big data and how new data models are disrupting traditional approaches. It notes that while the new models are initially difficult to understand and threaten existing investments, they are capable of processing large volumes of data quickly. The document examines concepts like Hadoop, NoSQL, and how relational and non-relational approaches can work together in a hybrid environment. It concludes that trends point to more unified support of different data types and expanded capabilities in systems like real-time analytics and embedded search.
Internet Infrastructures for Big Data (Verisign's Distinguished Speaker Series)
Internet Infrastructures for Big Data (Verisign's Distinguished Speaker Series)eXascale Infolab Internet Infrastructures for Big Data
Talk given at Verisign's Distinguished Speaker Series, 2014
Prof. Philippe Cudre-Mauroux
eXascale Infolab
http://exascale.info/
More Related Content
Viewers also liked (6)
How to use git without rage
How to use git without rageJavier Lafora Rey This document provides an overview of using Git version control system, including:
1. The different types of version control systems like local (LVCS), centralized (CVCS), and distributed (DVCS) like Git.
2. Basic Git commands and workflows for creating a repository, adding/committing files, tagging versions, branching, merging, and working with remotes.
3. Examples of common branching workflows for topics, long-running branches, hotfixes, and merging branches with conflicts.
4. How to push/pull from remote repositories, delete remote branches, and work with tracking branches.
Git basics a starter on git and its ecosystem
Git basics a starter on git and its ecosystemFrançois D'Agostini Git is a distributed version control system that allows for non-linear development. It uses a local repository that tracks snapshots of files rather than file differences. The document discusses how to configure Git, create repositories, make commits, view commit histories, work with branches, merge branches, resolve conflicts, work with remote repositories, and leverage tools like Git stash and Git hosting platforms. Popular branching strategies like Git flow are also covered that establish best practices for team collaboration.
APIs para gente normal
APIs para gente normalJavier Lafora Rey Una breve introducción que explica lo que es un API y por qué deberíamos saber en qué consiste, sin bajar al plano técnico.
La charla se dio en theapihour, dentro del zincshower (2014)
Ruby object model: A matter of life and death
Ruby object model: A matter of life and deathJavier Lafora Rey Ruby object model internals for MRI. These slides have some animations, so if you want to see them all, you should download it. Created with libreoffice impress
Databases in Qt
Databases in Qtdanitiger33 This document discusses using Qt for SQL database access and modeling. It describes how QSqlDatabase provides an interface for database connections, and drivers like QODBC can be used for specific databases like SQL Server. It also covers executing queries with QSqlQuery, retrieving result sets, and using QSqlTableModel to present database contents in a view like QListView for CRUD operations. Record-level access and filtering are demonstrated.
API REST for beginners or why you should make your API understandable
API REST for beginners or why you should make your API understandableJavier Lafora Rey This document provides an introduction to building RESTful APIs for beginners. It discusses the history and evolution of APIs from early web technologies like widgets and web scraping to modern standards like SOAP and REST. It then covers key REST concepts like using HTTP methods to specify actions, addressing resources uniquely through URIs, making requests and responses self-descriptive through embedded hyperlinks, and designing APIs that are stateless and cacheable. The document provides examples of RESTful API design and best practices for documentation, data formatting, and versioning.
Similar to Understanding big data-drupalcamp (20)
Big Data
Big DataPriyanka Tuteja This document discusses big data, including what it is, common data sources, its volume, velocity and variety characteristics, solutions like Hadoop and its HDFS and MapReduce components, and the impact and future of big data. It explains that big data refers to large and complex datasets that are difficult to process using traditional tools. Hadoop provides a framework to store and process big data across clusters of commodity hardware.
Big data(1st presentation)
Big data(1st presentation)Takrim Ul Islam Laskar Big Data Is an Advanced Database System, which is in use by all the gigantic institutes like facebook,google,etc
Presentation on BigData by Swapnaja
Presentation on BigData by Swapnaja Swapnaja Tandale The document discusses big data and how it is being generated from various sources like social media, sensors, and mobile devices. It describes the key characteristics of big data known as the three V's - volume, velocity and variety. It then explains how Hadoop uses HDFS for storage and MapReduce for processing large datasets in parallel across clusters of computers. The conclusion states that big data presents both opportunities and challenges for industries in creating value from large and diverse datasets.
Data mining with big data
Data mining with big dataSandip Tipayle Patil This document discusses big data and data mining. It defines big data as large volumes of structured and unstructured data that are difficult to process using traditional techniques due to their size. It outlines the 4 Vs of big data: volume, velocity, variety, and veracity. The proposed system would use distributed parallel computing with Hadoop to identify relationships in huge amounts of data from different sources and dimensions. It discusses challenges of big data like data location, volume, privacy, and gaining insights. Solutions involve parallel programming, distributed storage, and access restrictions.
Big Data Presentation
Big Data PresentationRitika Barethia Detailed description of big data, with the characteristics of it. What are the limitations of the traditional systems? Where we are using big data? And also the applications of big data.
Big Data
Big DataRaja Ram Dutta Big data refers to large and complex datasets that are difficult to process using traditional data management tools. As data grows from gigabytes to terabytes to petabytes, new techniques are needed to store, process, and analyze this data. Hadoop is an open-source framework that uses distributed storage and processing to handle big data across clusters of computers. It includes HDFS for storage and MapReduce as a programming model for distributed processing of large datasets in parallel.
Spectra Logic BlackPearl Developer Summit 2015
Spectra Logic BlackPearl Developer Summit 2015spectralogic Slides from Spectra Logic’s inaugural BlackPearl Developer Summit, a virtual conference for current and potential Spectra Logic developers. You’ll get product updates from our CEO and BlackPearl product manager, and you will learn how these new features will help customers and developers. You will learn how to build a Spectra S3 client for BlackPearl, our private cloud gateway to our tape and disk storage systems. You will see how one of our partners developed a client and watch it in action. And you will get to ask questions to our BlackPearl Engineering team. Watch the Summit recording at https://www.youtube.com/watch?v=GYoSwrvhVM0
The Internet-of-things: Architecting for the deluge of data
The Internet-of-things: Architecting for the deluge of databcantrill The document discusses the challenges of managing the massive amount of data that will be generated by the Internet of Things (IoT). It argues that storing all raw IoT data authoritatively and allowing for hypothesis exploration through computation will require new approaches. ZFS storage combined with OS-level containers through systems like Manta may provide a way to cope with IoT-generated data at scale while enabling flexible analysis of non-fungible data. The document also discusses how Unix and its model of small, interconnected programs was well-suited for ad hoc data processing tasks.
PUC Masterclass Big Data
PUC Masterclass Big DataArjen de Vries This document provides an overview of a masterclass on big data presented by Prof.dr.ir. Arjen P. de Vries. It discusses defining properties of big data, challenges in big data analytics including capturing, aligning, transforming, modeling and understanding large datasets. It also briefly introduces map-reduce and streaming data analysis. Examples of large datasets that could be analyzed are provided, such as the sizes of datasets from Facebook, Google and other organizations.
Conservation keeping up with technology
Conservation keeping up with technologyDick Eastman The document discusses the latest preservation technology for genealogists, focusing on ensuring genealogy data remains readable in the future and how to easily share data. It covers traditional methods like paper, which is fragile, and microfilm, which requires optimal storage conditions. Modern options discussed include digitizing files and storing multiple backups on different media like CDs, DVDs, drives and cloud services. Cloud computing allows sharing data online while maintaining control. Technologies like smartphones and tablets have made genealogy research more portable and collaborative. Overall the document promotes digitizing and securely backing up data across various media to preserve family history for generations to come.
big-data-notes1.ppt
big-data-notes1.pptSutanuGhosal1 Data analytics is needed everywhere to predict relevant outcomes, increase profits, and efficiently use resources. It involves transforming processed information into knowledge. Companies use data analytics to understand customer behavior and target them with personalized advertisements and offers. Different types of data include structured, semi-structured, unstructured, and big data. Big data is high volume, high velocity, and highly variable information that requires novel processing techniques. Hadoop is an open source software framework that allows distributed processing of big data across clusters of computers using simple programming models like MapReduce. Data analytics helps analyze these different data types to provide business insights.
Bigdata processing with Spark
Bigdata processing with SparkArjen de Vries This document provides information about big data and Hadoop. It discusses how big data is defined in terms of large volumes, variety of data types, and velocity of data ingestion. It then summarizes the MapReduce programming model used in Hadoop for distributed processing of large datasets in parallel across clusters. Key aspects covered include how MapReduce handles scheduling, data distribution, synchronization, and fault tolerance. The document also notes some of the deficiencies of Hadoop, such as sources of latency, its lack of indexes, and its limitations for complex multi-step data analysis workflows.
BIG DATA
BIG DATADr. Shashank Shetty Concepts of Big data and some of the tools used for solving Big Data is Explained in this Presentation
Big Data & Hadoop Introduction
Big Data & Hadoop IntroductionJayant Mukherjee Disclaimer :
The images, company, product and service names that are used in this presentation, are for illustration purposes only. All trademarks and registered trademarks are the property of their respective owners.
Data/Image collected from various sources from Internet.
Intention was to present the big picture of Big Data & Hadoop
Big Data = Big Decisions
Big Data = Big DecisionsInnoTech This document discusses big data and how new data models are disrupting traditional approaches. It notes that while the new models are initially difficult to understand and threaten existing investments, they are capable of processing large volumes of data quickly. The document examines concepts like Hadoop, NoSQL, and how relational and non-relational approaches can work together in a hybrid environment. It concludes that trends point to more unified support of different data types and expanded capabilities in systems like real-time analytics and embedded search.
Internet Infrastructures for Big Data (Verisign's Distinguished Speaker Series)
Internet Infrastructures for Big Data (Verisign's Distinguished Speaker Series)eXascale Infolab Internet Infrastructures for Big Data
Talk given at Verisign's Distinguished Speaker Series, 2014
Prof. Philippe Cudre-Mauroux
eXascale Infolab
http://exascale.info/
Big Data And Hadoop
Big Data And HadoopAnkur Tripathi This document provides an overview of big data and Hadoop. It defines big data as large volumes of unstructured data that are too costly and time-consuming to load into traditional databases. It notes that big data comes from various sources like web data, social networks, and sensor data. The challenges of big data include slow disk speeds and the need for parallel processing. Hadoop is introduced as an open-source framework that uses HDFS for storage across clusters and MapReduce for parallel processing of large datasets. Key aspects of HDFS and MapReduce are summarized.
Bigdata " new level"
Bigdata " new level"Vamshikrishna Goud Bigdata.
Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. Challenges include capture, storage, analysis, data curation, search, sharing, transfer, visualization, querying, updating and information privacy. The term "big data" often refers simply to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. "There is little doubt that the quantities of data now available are indeed large, but that’s not the most relevant characteristic of this new data ecosystem."[2] Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on."[3] Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet search, fintech, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics,[4] connectomics, complex physics simulations, biology and environmental research.[5]
Data sets grow rapidly - in part because they are increasingly gathered by cheap and numerous information-sensing Internet of things devices such as mobile devices, aerial (remote sensing), software logs, cameras, microphones, radio-frequency identification (RFID) readers and wireless sensor networks.[6][7] The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s;[8] as of 2012, every day 2.5 exabytes (2.5×1018) of data are generated.[9] One question for large enterprises is determining who should own big-data initiatives that affect the entire organization.[10]
Relational database management systems and desktop statistics- and visualization-packages often have difficulty handling big data. The work may require "massively parallel software running on tens, hundreds, or even thousands of servers".[11] What counts as "big data" varies depending on the capabilities of the users and their tools, and expanding capabilities make big data a moving target. "For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration."
Big data with Hadoop - Introduction
Big data with Hadoop - IntroductionTomy Rhymond This document provides an overview of big data and Hadoop. It defines big data as large volumes of structured, semi-structured and unstructured data that is growing exponentially and is too large for traditional databases to handle. It discusses the 4 V's of big data - volume, velocity, variety and veracity. The document then describes Hadoop as an open-source framework for distributed storage and processing of big data across clusters of commodity hardware. It outlines the key components of Hadoop including HDFS, MapReduce, YARN and related modules. The document also discusses challenges of big data, use cases for Hadoop and provides a demo of configuring an HDInsight Hadoop cluster on Azure.
SKILLWISE-BIGDATA ANALYSIS
SKILLWISE-BIGDATA ANALYSISSkillwise Consulting General outline created by SKILLWISE about BIGDATA, which gives you a clear idea about what is bigdata?
Recently uploaded (20)
Meet the Agents: How AI Is Learning to Think, Plan, and Collaborate
Meet the Agents: How AI Is Learning to Think, Plan, and CollaborateMaxim Salnikov Imagine if apps could think, plan, and team up like humans. Welcome to the world of AI agents and agentic user interfaces (UI)! In this session, we'll explore how AI agents make decisions, collaborate with each other, and create more natural and powerful experiences for users.
Adobe Illustrator Crack FREE Download 2025 Latest Version
Adobe Illustrator Crack FREE Download 2025 Latest Versionkashifyounis067 🌍📱👉COPY LINK & PASTE ON GOOGLE http://drfiles.net/ 👈🌍
Adobe Illustrator is a powerful, professional-grade vector graphics software used for creating a wide range of designs, including logos, icons, illustrations, and more. Unlike raster graphics (like photos), which are made of pixels, vector graphics in Illustrator are defined by mathematical equations, allowing them to be scaled up or down infinitely without losing quality.
Here's a more detailed explanation:
Key Features and Capabilities:
Vector-Based Design:
Illustrator's foundation is its use of vector graphics, meaning designs are created using paths, lines, shapes, and curves defined mathematically.
Scalability:
This vector-based approach allows for designs to be resized without any loss of resolution or quality, making it suitable for various print and digital applications.
Design Creation:
Illustrator is used for a wide variety of design purposes, including:
Logos and Brand Identity: Creating logos, icons, and other brand assets.
Illustrations: Designing detailed illustrations for books, magazines, web pages, and more.
Marketing Materials: Creating posters, flyers, banners, and other marketing visuals.
Web Design: Designing web graphics, including icons, buttons, and layouts.
Text Handling:
Illustrator offers sophisticated typography tools for manipulating and designing text within your graphics.
Brushes and Effects:
It provides a range of brushes and effects for adding artistic touches and visual styles to your designs.
Integration with Other Adobe Software:
Illustrator integrates seamlessly with other Adobe Creative Cloud apps like Photoshop, InDesign, and Dreamweaver, facilitating a smooth workflow.
Why Use Illustrator?
Professional-Grade Features:
Illustrator offers a comprehensive set of tools and features for professional design work.
Versatility:
It can be used for a wide range of design tasks and applications, making it a versatile tool for designers.
Industry Standard:
Illustrator is a widely used and recognized software in the graphic design industry.
Creative Freedom:
It empowers designers to create detailed, high-quality graphics with a high degree of control and precision.
Kubernetes_101_Zero_to_Platform_Engineer.pptx
Kubernetes_101_Zero_to_Platform_Engineer.pptxCloudScouts Presentacion de la primera sesion de Zero to Platform Engineer
TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...
TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...Andre Hora Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over time. However, the migration can be timeconsuming and take a long time to conclude. In this context, projects would benefit from automated solutions to support the migration process. In this paper, we propose TestMigrationsInPy, a dataset of test migrations from unittest to pytest. TestMigrationsInPy contains 923 real-world migrations performed by developers. Future research proposing novel solutions to migrate frameworks in Python can rely on TestMigrationsInPy as a ground truth. Moreover, as TestMigrationsInPy includes information about the migration type (e.g., changes in assertions or fixtures), our dataset enables novel solutions to be verified effectively, for instance, from simpler assertion migrations to more complex fixture migrations. TestMigrationsInPy is publicly available at: https://github.com/altinoalvesjunior/TestMigrationsInPy.
Designing AI-Powered APIs on Azure: Best Practices& Considerations
Designing AI-Powered APIs on Azure: Best Practices& ConsiderationsDinusha Kumarasiri AI is transforming APIs, enabling smarter automation, enhanced decision-making, and seamless integrations. This presentation explores key design principles for AI-infused APIs on Azure, covering performance optimization, security best practices, scalability strategies, and responsible AI governance. Learn how to leverage Azure API Management, machine learning models, and cloud-native architectures to build robust, efficient, and intelligent API solutions
Top 10 Client Portal Software Solutions for 2025.docx
Top 10 Client Portal Software Solutions for 2025.docxPortli Discover the top 10 client portal software solutions for 2025. Streamline communication, ensure security, and enhance client experience.
Salesforce Data Cloud- Hyperscale data platform, built for Salesforce.
Salesforce Data Cloud- Hyperscale data platform, built for Salesforce.Dele Amefo Salesforce Data Cloud- Hyperscale data platform, built for Salesforce.
Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)
Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.
Secure Test Infrastructure: The Backbone of Trustworthy Software Development
Secure Test Infrastructure: The Backbone of Trustworthy Software DevelopmentShubham Joshi A secure test infrastructure ensures that the testing process doesn’t become a gateway for vulnerabilities. By protecting test environments, data, and access points, organizations can confidently develop and deploy software without compromising user privacy or system integrity.
Adobe Marketo Engage Champion Deep Dive - SFDC CRM Synch V2 & Usage Dashboards
Adobe Marketo Engage Champion Deep Dive - SFDC CRM Synch V2 & Usage DashboardsBradBedford3 Join Ajay Sarpal and Miray Vu to learn about key Marketo Engage enhancements. Discover improved in-app Salesforce CRM connector statistics for easy monitoring of sync health and throughput. Explore new Salesforce CRM Synch Dashboards providing up-to-date insights into weekly activity usage, thresholds, and limits with drill-down capabilities. Learn about proactive notifications for both Salesforce CRM sync and product usage overages. Get an update on improved Salesforce CRM synch scale and reliability coming in Q2 2025.
Key Takeaways:
Improved Salesforce CRM User Experience: Learn how self-service visibility enhances satisfaction.
Utilize Salesforce CRM Synch Dashboards: Explore real-time weekly activity data.
Monitor Performance Against Limits: See threshold limits for each product level.
Get Usage Over-Limit Alerts: Receive notifications for exceeding thresholds.
Learn About Improved Salesforce CRM Scale: Understand upcoming cloud-based incremental sync.
How to Batch Export Lotus Notes NSF Emails to Outlook PST Easily?
How to Batch Export Lotus Notes NSF Emails to Outlook PST Easily?steaveroggers Migrating from Lotus Notes to Outlook can be a complex and time-consuming task, especially when dealing with large volumes of NSF emails. This presentation provides a complete guide on how to batch export Lotus Notes NSF emails to Outlook PST format quickly and securely. It highlights the challenges of manual methods, the benefits of using an automated tool, and introduces eSoftTools NSF to PST Converter Software — a reliable solution designed to handle bulk email migrations efficiently. Learn about the software’s key features, step-by-step export process, system requirements, and how it ensures 100% data accuracy and folder structure preservation during migration. Make your email transition smoother, safer, and faster with the right approach.
Read More:- https://www.esofttools.com/nsf-to-pst-converter.html
Exploring Wayland: A Modern Display Server for the Future
Exploring Wayland: A Modern Display Server for the FutureICS Wayland is revolutionizing the way we interact with graphical interfaces, offering a modern alternative to the X Window System. In this webinar, we’ll delve into the architecture and benefits of Wayland, including its streamlined design, enhanced performance, and improved security features.
Interactive odoo dashboards for sales, CRM , Inventory, Invoice, Purchase, Pr...
Interactive odoo dashboards for sales, CRM , Inventory, Invoice, Purchase, Pr...AxisTechnolabs Interactive Odoo Dashboard for various business needs can provide users with dynamic, visually appealing dashboards tailored to their specific requirements. such a module that could support multiple dashboards for different aspects of a business
✅Visit And Buy Now : https://bit.ly/3VojWza
✅This Interactive Odoo dashboard module allow user to create their own odoo interactive dashboards for various purpose.
App download now :
Odoo 18 : https://bit.ly/3VojWza
Odoo 17 : https://bit.ly/4h9Z47G
Odoo 16 : https://bit.ly/3FJTEA4
Odoo 15 : https://bit.ly/3W7tsEB
Odoo 14 : https://bit.ly/3BqZDHg
Odoo 13 : https://bit.ly/3uNMF2t
Try Our website appointment booking odoo app : https://bit.ly/3SvNvgU
👉Want a Demo ?📧 [email protected]
➡️Contact us for Odoo ERP Set up : 091066 49361
👉Explore more apps: https://bit.ly/3oFIOCF
👉Want to know more : 🌐 https://www.axistechnolabs.com/
#odoo #odoo18 #odoo17 #odoo16 #odoo15 #odooapps #dashboards #dashboardsoftware #odooerp #odooimplementation #odoodashboardapp #bestodoodashboard #dashboardapp #odoodashboard #dashboardmodule #interactivedashboard #bestdashboard #dashboard #odootag #odooservices #odoonewfeatures #newappfeatures #odoodashboardapp #dynamicdashboard #odooapp #odooappstore #TopOdooApps #odooapp #odooexperience #odoodevelopment #businessdashboard #allinonedashboard #odooproducts
Mastering Fluent Bit: Ultimate Guide to Integrating Telemetry Pipelines with ...
Mastering Fluent Bit: Ultimate Guide to Integrating Telemetry Pipelines with ...Eric D. Schabell It's time you stopped letting your telemetry data pressure your budgets and get in the way of solving issues with agility! No more I say! Take back control of your telemetry data as we guide you through the open source project Fluent Bit. Learn how to manage your telemetry data from source to destination using the pipeline phases covering collection, parsing, aggregation, transformation, and forwarding from any source to any destination. Buckle up for a fun ride as you learn by exploring how telemetry pipelines work, how to set up your first pipeline, and exploring several common use cases that Fluent Bit helps solve. All this backed by a self-paced, hands-on workshop that attendees can pursue at home after this session (https://o11y-workshops.gitlab.io/workshop-fluentbit).
Pixologic ZBrush Crack Plus Activation Key [Latest 2025] New Version![Pixologic ZBrush Crack Plus Activation Key [Latest 2025] New Version](https://cdn.slidesharecdn.com/ss_thumbnails/fashionevolution2-250322112409-f76abaa7-250428124909-b51264ff-250504160528-fc2bb1c5-thumbnail.jpg?width=560&fit=bounds)
Pixologic ZBrush Crack Plus Activation Key [Latest 2025] New Versionsaimabibi60507 Copy & Past Link👉👉
https://dr-up-community.info/
Pixologic ZBrush, now developed by Maxon, is a premier digital sculpting and painting software renowned for its ability to create highly detailed 3D models. Utilizing a unique "pixol" technology, ZBrush stores depth, lighting, and material information for each point on the screen, allowing artists to sculpt and paint with remarkable precision .
Adobe After Effects Crack FREE FRESH version 2025
Adobe After Effects Crack FREE FRESH version 2025kashifyounis067 🌍📱👉COPY LINK & PASTE ON GOOGLE http://drfiles.net/ 👈🌍
Adobe After Effects is a software application used for creating motion graphics, special effects, and video compositing. It's widely used in TV and film post-production, as well as for creating visuals for online content, presentations, and more. While it can be used to create basic animations and designs, its primary strength lies in adding visual effects and motion to videos and graphics after they have been edited.
Here's a more detailed breakdown:
Motion Graphics:
.
After Effects is powerful for creating animated titles, transitions, and other visual elements to enhance the look of videos and presentations.
Visual Effects:
.
It's used extensively in film and television for creating special effects like green screen compositing, object manipulation, and other visual enhancements.
Video Compositing:
.
After Effects allows users to combine multiple video clips, images, and graphics to create a final, cohesive visual.
Animation:
.
It uses keyframes to create smooth, animated sequences, allowing for precise control over the movement and appearance of objects.
Integration with Adobe Creative Cloud:
.
After Effects is part of the Adobe Creative Cloud, a suite of software that includes other popular applications like Photoshop and Premiere Pro.
Post-Production Tool:
.
After Effects is primarily used in the post-production phase, meaning it's used to enhance the visuals after the initial editing of footage has been completed.
What Do Contribution Guidelines Say About Software Testing? (MSR 2025)
What Do Contribution Guidelines Say About Software Testing? (MSR 2025)Andre Hora Software testing plays a crucial role in the contribution process of open-source projects. For example, contributions introducing new features are expected to include tests, and contributions with tests are more likely to be accepted. Although most real-world projects require contributors to write tests, the specific testing practices communicated to contributors remain unclear. In this paper, we present an empirical study to understand better how software testing is approached in contribution guidelines. We analyze the guidelines of 200 Python and JavaScript open-source software projects. We find that 78% of the projects include some form of test documentation for contributors. Test documentation is located in multiple sources, including CONTRIBUTING files (58%), external documentation (24%), and README files (8%). Furthermore, test documentation commonly explains how to run tests (83.5%), but less often provides guidance on how to write tests (37%). It frequently covers unit tests (71%), but rarely addresses integration (20.5%) and end-to-end tests (15.5%). Other key testing aspects are also less frequently discussed: test coverage (25.5%) and mocking (9.5%). We conclude by discussing implications and future research.
Get & Download Wondershare Filmora Crack Latest [2025]![Get & Download Wondershare Filmora Crack Latest [2025]](https://cdn.slidesharecdn.com/ss_thumbnails/revolutionizingresidentialwi-fi-250422112639-60fb726f-250429170801-59e1b240-thumbnail.jpg?width=560&fit=bounds)
Get & Download Wondershare Filmora Crack Latest [2025]saniaaftab72555 Copy & Past Link 👉👉
https://dr-up-community.info/
Wondershare Filmora is a video editing software and app designed for both beginners and experienced users. It's known for its user-friendly interface, drag-and-drop functionality, and a wide range of tools and features for creating and editing videos. Filmora is available on Windows, macOS, iOS (iPhone/iPad), and Android platforms.
Expand your AI adoption with AgentExchange
Expand your AI adoption with AgentExchangeFexle Services Pvt. Ltd. AgentExchange is Salesforce’s latest innovation, expanding upon the foundation of AppExchange by offering a centralized marketplace for AI-powered digital labor. Designed for Agentblazers, developers, and Salesforce admins, this platform enables the rapid development and deployment of AI agents across industries.
Email: [email protected]
Phone: +1(630) 349 2411
Website: https://www.fexle.com/blogs/agentexchange-an-ultimate-guide-for-salesforce-consultants-businesses/?utm_source=slideshare&utm_medium=pptNg
EASEUS Partition Master Crack + License Code
EASEUS Partition Master Crack + License Codeaneelaramzan63 Copy & Paste On Google >>> https://dr-up-community.info/
EASEUS Partition Master Final with Crack and Key Download If you are looking for a powerful and easy-to-use disk partitioning software,
Understanding big data-drupalcamp
- 1. Understanding Big Data... ...or trying to understand a new awesome paradigm
- 5. A small walk through historyA small walk through history
- 10. Data Growth “90% of the data in the world today has been created in the last two years alone.” - IBM http://www-01.ibm.com/software/in/data/bigdata/
- 11. Data growth “There were 5 Exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days”. - Eric Schmidt, Google CEO, 2010
- 17. Traditional approach One powerful computer for all the data...
- 18. Traditional approach ...until it reaches storage limit...
- 19. Traditional approach ...or until it reaches process limit
- 26. Distributed filesystems A DFS manages files and folders across multiple computers. It serves the same purpose as a traditional file system, but is designed to provide file storage and controlled access to files over local and wide area networks.
- 27. You don't want to worry about where a file is located
- 28. You don't want to worry about replicating data
- 29. You don't want to worry about managing failures
- 31. You don't want to worry about breaking computation into pieces
- 32. You don't want to worry about scaling your code
- 33. Hadoop to the rescue
- 37. Map Reduce
- 39. Volume
- 40. Streaming / real time
- 41. Variety
- 42. Structured data
- 49. Questions?
Editor's Notes
- #12: 1 EB = 1024 PB 1 PB = 1024 TB 1 TB = 1024 GB