The document summarizes the evolution of collections databases from the 1960s to present day. It discusses how early systems automated library card catalogs, how CMS systems emerged in museums driven by accountability needs, and how continual technology changes like personal computers and the internet impacted systems. It also explores current trends like APIs, cloud computing, and underutilization of CMS functionality despite advances.
The story of how data became big starts many years before the current buzz around big data.The history of Big Data as a term may be brief – but many of the foundations it is built on were laid many years ago. Now, let’s look at a detailed account of the major milestones in the history of sizing data volumes in the evolution of the idea of “big data” and observations pertaining to data or information explosion:
Big data-public-private-forum--2013 publioc-sector_meeting_spain_big_data_tec...Tomas Pariente Lobo
Talk to Public Sector officials in Spain about Technological trends in Big Data. Aimed to create awareness of the BIG project (http://www.big-project.eu/) and get feedbak for the sector roadmap
Slides for an introductory course on Big Data Tools for Artificial Intelligence. This first set of slides introduces the concept of big data and the current context.
Big data provides opportunities for businesses through insights into customers and markets not previously available. It allows targeting of marketing, development of new products, and optimization of operations. However, managing large and diverse datasets presents technological challenges around storage, processing power, and coordination across distributed systems. New approaches like Hadoop and cloud computing aim to enable businesses to gain value from big data despite these challenges.
This document discusses the rise of big data and the data economy. It begins by comparing the growth of transportation infrastructure like highways and the internet to the growth of digital data. It then discusses the various types of data being created, including website data, social media data, mobile data, and machine data. It explains that while the scale of data seems vast, most individual data points are worthless alone. The value comes from combining different types of data to generate new insights. It concludes by looking briefly at the history of data analysis and hypothesis testing, and how our approaches may need to evolve to analyze the vast amounts of data now available.
A database is a collection of organized information that allows for efficient retrieval. Databases have existed for thousands of years in various formats, though early databases were recorded without computers through systems like those used by banks over 500 years ago. Major developments in databases occurred in the 1960s and 1970s with new data models, the Entity-Relationship model, and the introduction of SQL in the 1980s. Client-server computing became common in the early 1990s along with tools for application development and personal productivity. The Internet further accelerated database growth and accessibility in the mid-1990s.
The document discusses addressing data management challenges in the cloud. It begins by introducing the scale of digital data using common size prefixes like kilobyte and petabyte. It then discusses sources of massive data from sensors, social media, and scientific experiments. The challenges of big data are defined through the 3Vs model of increasing volume, velocity and variety of data types. Cloud computing architectures and delivery models like IaaS, PaaS and SaaS are introduced as ways to provide elastic resources for data management. The concept of polyglot persistence using the appropriate data store for the job is discussed over relying solely on relational databases.
The story of how data became big starts many years before the current buzz around big data.The history of Big Data as a term may be brief – but many of the foundations it is built on were laid many years ago. Now, let’s look at a detailed account of the major milestones in the history of sizing data volumes in the evolution of the idea of “big data” and observations pertaining to data or information explosion:
Big data-public-private-forum--2013 publioc-sector_meeting_spain_big_data_tec...Tomas Pariente Lobo
Talk to Public Sector officials in Spain about Technological trends in Big Data. Aimed to create awareness of the BIG project (http://www.big-project.eu/) and get feedbak for the sector roadmap
Slides for an introductory course on Big Data Tools for Artificial Intelligence. This first set of slides introduces the concept of big data and the current context.
Big data provides opportunities for businesses through insights into customers and markets not previously available. It allows targeting of marketing, development of new products, and optimization of operations. However, managing large and diverse datasets presents technological challenges around storage, processing power, and coordination across distributed systems. New approaches like Hadoop and cloud computing aim to enable businesses to gain value from big data despite these challenges.
This document discusses the rise of big data and the data economy. It begins by comparing the growth of transportation infrastructure like highways and the internet to the growth of digital data. It then discusses the various types of data being created, including website data, social media data, mobile data, and machine data. It explains that while the scale of data seems vast, most individual data points are worthless alone. The value comes from combining different types of data to generate new insights. It concludes by looking briefly at the history of data analysis and hypothesis testing, and how our approaches may need to evolve to analyze the vast amounts of data now available.
A database is a collection of organized information that allows for efficient retrieval. Databases have existed for thousands of years in various formats, though early databases were recorded without computers through systems like those used by banks over 500 years ago. Major developments in databases occurred in the 1960s and 1970s with new data models, the Entity-Relationship model, and the introduction of SQL in the 1980s. Client-server computing became common in the early 1990s along with tools for application development and personal productivity. The Internet further accelerated database growth and accessibility in the mid-1990s.
The document discusses addressing data management challenges in the cloud. It begins by introducing the scale of digital data using common size prefixes like kilobyte and petabyte. It then discusses sources of massive data from sensors, social media, and scientific experiments. The challenges of big data are defined through the 3Vs model of increasing volume, velocity and variety of data types. Cloud computing architectures and delivery models like IaaS, PaaS and SaaS are introduced as ways to provide elastic resources for data management. The concept of polyglot persistence using the appropriate data store for the job is discussed over relying solely on relational databases.
This document discusses different types of bullying, including physical bullying like punching and kicking as well as psychological bullying like ignoring someone or demanding money. It notes that bullying can occur through physical or online means. The targets of bullying are often those seen as different, such as gawky, racially different, or unusual children. Bullying is enabled through the actions of the perpetrator, crowd, bystanders, and sometimes even teachers. Schools without clear rules against bullying and without outside oversight are more prone to these issues. The document calls for solutions to address bullying in schools.
The student used several programs throughout their coursework including InDesign, Blogger, Photoshop, PowerPoint, Survey Monkey, and Word. For their final magazine, they used InDesign to design pages, Photoshop to edit photos, and a digital camera to take photos. They concluded that InDesign and PowerPoint became easier to use with more practice, while Survey Monkey and Prezi took some time to learn but were helped by available tutorials.
1) Australia has experienced the longest period of continuous economic growth of any developed country, averaging 3.3% annual GDP growth for 21 years without a recession.
2) Australia is well positioned to benefit from Asia's economic rise given its proximity and exports of commodities and other goods/services to the region.
3) Despite its dependence on mining and commodities, Australia has a highly developed services sector accounting for over 80% of its GDP, and has a very business friendly climate according to various indices.
Lauren Morgan made several changes to the design and layout of a double page spread (DPS) for a magazine based on feedback from a focus group. This included deleting some graphic features and secondary articles to reduce clutter, adding consistent page numbers and logos at the bottom of each page, and using the same font styles across pages to create a uniform brand identity and style. Images were arranged evenly on the pages and the font was changed to improve readability and complement the design changes.
An introduction on what Social Media really is and how it may be used to prevent and handle a crisis, educate the public, and also for restoration and rescue after an incident.
Presentation during the COSMIC Project workshop on February 15, 2014, in Thessaloniki, Greece.
How We Analyzed 1000 Dumps in One Day - Dina Goldshtein, Brightsource - DevOp...DevOpsDays Tel Aviv
The document describes BrightSource Energy's process for analyzing crash dumps from their solar power plant control software. Originally, crashes were analyzed manually using debuggers like Visual Studio, which could take 10 minutes per dump and there were often dozens of dumps per day. They developed an automatic analysis workflow using the ClrMD NuGet package to analyze dumps. The script uses ClrMD to find the exception, call stack, and faulty component in each dump. It then alerts the relevant owner and creates a ticket in Redmine. This reduced analysis time from hours to seconds and allowed them to analyze around 1000 dumps in a single day.
DevOps Days Tel Aviv 2013: How not to do Devops: Confessions of a Thought Lea...DevOpsDays Tel Aviv
The document discusses various ways that DevOps initiatives can go wrong if not properly implemented, such as abandoning quality controls without establishing new ones, overfocusing on tools rather than culture, and ignoring signs of burnout. It provides counterpoints and "antidotes" to help avoid these pitfalls, such as establishing peer reviews, prioritizing individuals and interactions, and emphasizing rest and balance.
This document provides definitions and brief explanations of key terms related to Kognitio's analytical platform and database technologies. Some of the key terms defined include 10GbE networking, ACID compliance, Amazon Web Services, analytical platforms, analytical workloads, blade servers, cores, CPUs, data warehouses, databases appliances, dimensions, disk storage, elastic block store, ETL processes, external scripting, external tables, in-memory databases, JDBC, latency, linear scalability, massively parallel processing, MDX, measures, memory, nodes, NoSQL databases, ODBC, OLAP, OLTP, parallel processing, persistence layers, private clouds, public clouds, and R language.
The shooting script outlines 28 shots for a music video featuring Jess. The shots include various locations like a field, kitchen, and stairs. Jess is shown dancing, writing a note attached to a balloon, and releasing the balloon. Most shots focus on Jess and her movements, with costumes including baggy shirts and leggings. Audio includes instrumental music and song lyrics. Shots vary in length from 1 to 17 seconds to tell the story through Jess' actions and emotions.
This document discusses big data analytics and Kognitio's analytical platform. It provides examples of clients using Kognitio to gain insights from large datasets, including a media company using 40TB of data from 22 sources, and a retailer accelerating queries from over 5 hours to minutes. It outlines Kognitio's in-memory reference architecture and ability to execute third-party scripts within SQL. A quote from a satisfied client praises Kognitio's jaw-dropping performance.
This document discusses different types of bullying, including physical bullying like punching and kicking as well as psychological bullying like ignoring someone or demanding money. It notes that bullying can occur through physical or online means. The targets of bullying are often those seen as unusual, gawky, or of a different race. Bullying is enabled when perpetrators, crowds, teachers, and sideliners collude together and when schools lack clear rules against it. Solutions to bullying require awareness and prevention efforts.
Big data and the bi wild west kognitio hiskey mar 2013Kognitio
This session reviews “Big Data” case studies from media analysis, retail analytics and customer loyalty that go beyond the data warehouse and Hadoop. Disruption from the “Facebook generation,” armed with iPads, Droid Phones and netbooks brings a melee of new tools, devices and data sources. An analytical platform is the ‘Golden Spike’ to hitch stable, proven, and mature BI solutions with the data frontier—deep analytics, predictive modeling, sentiment analysis, etc. to enable competitive advantage.
-or- “Big Data and the BI Wild West: Don’t Bring an Elephant to a Gun Fight!”
-or- “Big Data and the BI Wild West: Don’t Bring an Elephant to a Gun Fight!”
Containing Chaos with Kubernetes - Terrence Ryan, Google - DevOpsDays Tel Avi...DevOpsDays Tel Aviv
The document discusses Kubernetes and container orchestration. It begins with an introduction to the problem of managing containers and microservices across multiple machines. It then covers key Kubernetes concepts like pods, controllers, services, labels and selectors. It also demonstrates Kubernetes in action and discusses options for hosting Kubernetes clusters, particularly Google Container Engine which provides a hosted Kubernetes environment.
How To Survive Among Giants - Making Big Data RelevantKyros Vogiatzoglou
Presented at the CAiSE 2014 International Conference, in Thessaloniki, Greece, in June 2014.
You have to make a decision for your business: Are you going to to try and talk to millions of people, or just pick the few that are worth communicating with? I suggest you do the latter.
The document discusses layout drafts for a digipak. It was written by Lauren Morgan and contains 3 sections but no other details are provided in the document. The document is very brief and does not contain much substantive information to summarize in 3 sentences or less.
Collections Databases; Making the system work for youirowson
This document provides an overview of Ian Rowson's presentation on selecting and implementing a Museum Collections Management System (CMS). Some key points:
- CMS projects involve significant time and resources, so it is important to minimize risks by following best practices. Rowson outlines seven "golden rules" to help with this.
- Choosing a flexible, standards-compliant system is important to allow for future changes and data exchange. Homegrown databases often fail to meet long-term needs.
- Ensuring you can export data in an open format is essential to avoid being locked into one system forever. Suppliers should demonstrate this capability.
- Getting support from various departments and an experienced supplier can help navigate technical
The document discusses the evolution of data storage and retrieval from oral traditions to modern databases integrated with the World Wide Web. It describes how early databases used file-based systems that had limitations in efficiency and usability. The development of relational databases and the ability to dynamically query databases from web servers enabled more powerful data-driven websites and applications. The integration of databases and client-side technologies like Flash further enhanced the interactivity and capabilities of websites and web applications.
Cloud computing concepts are becoming more widely used and defined. It generally refers to network-based storage, computation, and software-as-a-service models provided by external parties and billed based on usage. Major companies like Amazon, Google, Microsoft, and IBM are offering these services. The New York Times converted its archives to PDF using Amazon's cloud services in under 24 hours for around $500. While universities are lagging behind in computing power, partnerships like those between the NSF, Google and IBM aim to enhance academic research opportunities using emerging cloud paradigms.
My personal journey through the World of Open Source! How What Was Old Beco...Ceph Community
- Steve Wakefield's personal journey began in proprietary storage and led him to his first experience with open source via Ceph and Inktank. He was amazed by the power of the open source community to develop capabilities.
- Open source is the only sustainable option going forward. SUSE Enterprise Storage provides an enterprise-grade version of Ceph for petabyte to exabyte storage needs at massive cost savings over traditional storage.
- Computing has swung between centralized and distributed models over time, and is swinging back to centralized cloud processing but will also grow at the edge with 5G and IoT. Open source projects like Ceph, OpenStack, and containers allow for this hybrid model.
This document discusses different types of bullying, including physical bullying like punching and kicking as well as psychological bullying like ignoring someone or demanding money. It notes that bullying can occur through physical or online means. The targets of bullying are often those seen as different, such as gawky, racially different, or unusual children. Bullying is enabled through the actions of the perpetrator, crowd, bystanders, and sometimes even teachers. Schools without clear rules against bullying and without outside oversight are more prone to these issues. The document calls for solutions to address bullying in schools.
The student used several programs throughout their coursework including InDesign, Blogger, Photoshop, PowerPoint, Survey Monkey, and Word. For their final magazine, they used InDesign to design pages, Photoshop to edit photos, and a digital camera to take photos. They concluded that InDesign and PowerPoint became easier to use with more practice, while Survey Monkey and Prezi took some time to learn but were helped by available tutorials.
1) Australia has experienced the longest period of continuous economic growth of any developed country, averaging 3.3% annual GDP growth for 21 years without a recession.
2) Australia is well positioned to benefit from Asia's economic rise given its proximity and exports of commodities and other goods/services to the region.
3) Despite its dependence on mining and commodities, Australia has a highly developed services sector accounting for over 80% of its GDP, and has a very business friendly climate according to various indices.
Lauren Morgan made several changes to the design and layout of a double page spread (DPS) for a magazine based on feedback from a focus group. This included deleting some graphic features and secondary articles to reduce clutter, adding consistent page numbers and logos at the bottom of each page, and using the same font styles across pages to create a uniform brand identity and style. Images were arranged evenly on the pages and the font was changed to improve readability and complement the design changes.
An introduction on what Social Media really is and how it may be used to prevent and handle a crisis, educate the public, and also for restoration and rescue after an incident.
Presentation during the COSMIC Project workshop on February 15, 2014, in Thessaloniki, Greece.
How We Analyzed 1000 Dumps in One Day - Dina Goldshtein, Brightsource - DevOp...DevOpsDays Tel Aviv
The document describes BrightSource Energy's process for analyzing crash dumps from their solar power plant control software. Originally, crashes were analyzed manually using debuggers like Visual Studio, which could take 10 minutes per dump and there were often dozens of dumps per day. They developed an automatic analysis workflow using the ClrMD NuGet package to analyze dumps. The script uses ClrMD to find the exception, call stack, and faulty component in each dump. It then alerts the relevant owner and creates a ticket in Redmine. This reduced analysis time from hours to seconds and allowed them to analyze around 1000 dumps in a single day.
DevOps Days Tel Aviv 2013: How not to do Devops: Confessions of a Thought Lea...DevOpsDays Tel Aviv
The document discusses various ways that DevOps initiatives can go wrong if not properly implemented, such as abandoning quality controls without establishing new ones, overfocusing on tools rather than culture, and ignoring signs of burnout. It provides counterpoints and "antidotes" to help avoid these pitfalls, such as establishing peer reviews, prioritizing individuals and interactions, and emphasizing rest and balance.
This document provides definitions and brief explanations of key terms related to Kognitio's analytical platform and database technologies. Some of the key terms defined include 10GbE networking, ACID compliance, Amazon Web Services, analytical platforms, analytical workloads, blade servers, cores, CPUs, data warehouses, databases appliances, dimensions, disk storage, elastic block store, ETL processes, external scripting, external tables, in-memory databases, JDBC, latency, linear scalability, massively parallel processing, MDX, measures, memory, nodes, NoSQL databases, ODBC, OLAP, OLTP, parallel processing, persistence layers, private clouds, public clouds, and R language.
The shooting script outlines 28 shots for a music video featuring Jess. The shots include various locations like a field, kitchen, and stairs. Jess is shown dancing, writing a note attached to a balloon, and releasing the balloon. Most shots focus on Jess and her movements, with costumes including baggy shirts and leggings. Audio includes instrumental music and song lyrics. Shots vary in length from 1 to 17 seconds to tell the story through Jess' actions and emotions.
This document discusses big data analytics and Kognitio's analytical platform. It provides examples of clients using Kognitio to gain insights from large datasets, including a media company using 40TB of data from 22 sources, and a retailer accelerating queries from over 5 hours to minutes. It outlines Kognitio's in-memory reference architecture and ability to execute third-party scripts within SQL. A quote from a satisfied client praises Kognitio's jaw-dropping performance.
This document discusses different types of bullying, including physical bullying like punching and kicking as well as psychological bullying like ignoring someone or demanding money. It notes that bullying can occur through physical or online means. The targets of bullying are often those seen as unusual, gawky, or of a different race. Bullying is enabled when perpetrators, crowds, teachers, and sideliners collude together and when schools lack clear rules against it. Solutions to bullying require awareness and prevention efforts.
Big data and the bi wild west kognitio hiskey mar 2013Kognitio
This session reviews “Big Data” case studies from media analysis, retail analytics and customer loyalty that go beyond the data warehouse and Hadoop. Disruption from the “Facebook generation,” armed with iPads, Droid Phones and netbooks brings a melee of new tools, devices and data sources. An analytical platform is the ‘Golden Spike’ to hitch stable, proven, and mature BI solutions with the data frontier—deep analytics, predictive modeling, sentiment analysis, etc. to enable competitive advantage.
-or- “Big Data and the BI Wild West: Don’t Bring an Elephant to a Gun Fight!”
-or- “Big Data and the BI Wild West: Don’t Bring an Elephant to a Gun Fight!”
Containing Chaos with Kubernetes - Terrence Ryan, Google - DevOpsDays Tel Avi...DevOpsDays Tel Aviv
The document discusses Kubernetes and container orchestration. It begins with an introduction to the problem of managing containers and microservices across multiple machines. It then covers key Kubernetes concepts like pods, controllers, services, labels and selectors. It also demonstrates Kubernetes in action and discusses options for hosting Kubernetes clusters, particularly Google Container Engine which provides a hosted Kubernetes environment.
How To Survive Among Giants - Making Big Data RelevantKyros Vogiatzoglou
Presented at the CAiSE 2014 International Conference, in Thessaloniki, Greece, in June 2014.
You have to make a decision for your business: Are you going to to try and talk to millions of people, or just pick the few that are worth communicating with? I suggest you do the latter.
The document discusses layout drafts for a digipak. It was written by Lauren Morgan and contains 3 sections but no other details are provided in the document. The document is very brief and does not contain much substantive information to summarize in 3 sentences or less.
Collections Databases; Making the system work for youirowson
This document provides an overview of Ian Rowson's presentation on selecting and implementing a Museum Collections Management System (CMS). Some key points:
- CMS projects involve significant time and resources, so it is important to minimize risks by following best practices. Rowson outlines seven "golden rules" to help with this.
- Choosing a flexible, standards-compliant system is important to allow for future changes and data exchange. Homegrown databases often fail to meet long-term needs.
- Ensuring you can export data in an open format is essential to avoid being locked into one system forever. Suppliers should demonstrate this capability.
- Getting support from various departments and an experienced supplier can help navigate technical
The document discusses the evolution of data storage and retrieval from oral traditions to modern databases integrated with the World Wide Web. It describes how early databases used file-based systems that had limitations in efficiency and usability. The development of relational databases and the ability to dynamically query databases from web servers enabled more powerful data-driven websites and applications. The integration of databases and client-side technologies like Flash further enhanced the interactivity and capabilities of websites and web applications.
Cloud computing concepts are becoming more widely used and defined. It generally refers to network-based storage, computation, and software-as-a-service models provided by external parties and billed based on usage. Major companies like Amazon, Google, Microsoft, and IBM are offering these services. The New York Times converted its archives to PDF using Amazon's cloud services in under 24 hours for around $500. While universities are lagging behind in computing power, partnerships like those between the NSF, Google and IBM aim to enhance academic research opportunities using emerging cloud paradigms.
My personal journey through the World of Open Source! How What Was Old Beco...Ceph Community
- Steve Wakefield's personal journey began in proprietary storage and led him to his first experience with open source via Ceph and Inktank. He was amazed by the power of the open source community to develop capabilities.
- Open source is the only sustainable option going forward. SUSE Enterprise Storage provides an enterprise-grade version of Ceph for petabyte to exabyte storage needs at massive cost savings over traditional storage.
- Computing has swung between centralized and distributed models over time, and is swinging back to centralized cloud processing but will also grow at the edge with 5G and IoT. Open source projects like Ceph, OpenStack, and containers allow for this hybrid model.
Planning and Managing Digital Library & Archive Projectsac2182
The document provides an overview of a workshop on developing and managing digital library and archive projects. It includes the workshop schedule, introductions from attendees, strategies for success, managing born-digital assets and digitized content, infrastructure requirements, and considerations for digital preservation over the long-term.
This document discusses rethinking the library services platform (LSP) model to improve interoperability between systems. It notes that while new LSPs have emerged, significant lack of interoperability remains between components of the library technology ecosystem. The author argues that libraries should adopt a platform approach like Windows or Apple, where vendors provide tools and services to allow third parties to build applications on their platforms. This could encourage more applications and make platforms more valuable. Prioritizing the library user perspective may change how libraries think about LSPs. Standards bodies are working on interoperability issues but more remains to be done to fully integrate solutions.
Databases have been used for over 40 years to organize information in a variety of contexts like inventory, class schedules, and personal records. Relational databases remain popular today despite attempts to replace them with object-oriented databases. Cloud computing and big data have further transformed databases by allowing extremely large datasets to be analyzed for trends and patterns. Modern databases can provide targeted recommendations and offers by analyzing individual user information and behaviors.
Review of big data analytics (bda) architecture trends and analysis Conference Papers
This document reviews big data analytics (BDA) architecture trends and analysis. It discusses the evolution of data analytics from ancient times to modern technologies like Hadoop and Spark. It describes key features of BDA like flexibility, scalability, and fault tolerance. Common BDA architectures like lambda and kappa architectures are summarized. The lambda architecture uses batch, speed, and serving layers to handle both real-time and batch processing. The kappa architecture simplifies this by removing the batch layer and handling all processing through streaming. Overall, the document provides a high-level overview of BDA architectures and technologies.
Cloudera Breakfast: Advanced Analytics Part II: Do More With Your DataCloudera, Inc.
This document discusses how Cloudera Enterprise Data Hub (EDH) can be used for advanced analytics. EDH allows users to perform diverse concurrent analytics on large datasets without moving the data. It includes tools for machine learning, graph analytics, search, and statistical analysis. EDH protects data through security features and system change tracking. The document argues that EDH is the only platform that can support all these analytics capabilities in a single, integrated system. It provides several examples of how advanced analytics on EDH have helped organizations like the government address important problems.
The document summarizes the goals and components of the Artificial Technology Center and its Digital Library project. The Center aims to advance high-speed internet applications through research and development. Its Digital Library will integrate a physical library with web-based resources to provide new ways for users to access and organize multimedia information from the internet. The Digital Library will have several key software and hardware components, including a physical library space, a website for remote control and access, a query engine for storing and categorizing collected content, and a server to power the system. The goal is to create new commercially viable internet products and technologies through this innovative library environment.
BCO 117 IT Software for Business Lecture Reference Notes.docxjesuslightbody
BCO 117 IT Software for Business
Lecture Reference Notes
Cloud
computing
Eras in IT infrastructure evolution
Chapter 5. IT Infrastructure and EmergingTechnologies
Management Information Systems (Kenneth P. Laudon, Jane C. Laudon)
An information technology (IT) paradigm, a model for enabling ubiquitous access to shared pools of configurable resources (such as computer networks, servers, storage, applications and services), which
can be rapidly provisioned with minimal management effort, often over the Internet.
· Computing as a service
· Computing on the Internet
· Business line for computing corporations
Hassan, Qusay (2011).
"Demystifying Cloud Computing"(PDF).
The Journal of Defense Software Engineering.
Cloud computing
Cloud computing
Cloud computing
Cloud computing
www.euruni.edu
Cloud computing examples
Software as a Service
Platform as a Service
Insfrastructure as a Service
Cloud computing examples
Cloud computing examples
https://aws.amazon.com/products/?hp=tile&so-exp=below
Cloud computing examples
Cloud computing examples
Cloud computing examples
www.euruni.edu
Cloud computing examples
Cloud computing examples
Cloud computing examples
www.euruni.edu
Cloud computing success
Key concepts
·
Reliability – reliability of the system, measured in Mean Time Between Failures (MTBF)
·
Availability – uptime of the system or application, measured in parts per million (PPM) of downtime
·
Serviceability – easily restoring the system after a failure, measured in Mean Time To Repair (MTTR)
·
Manageability – the ease with which the entire system can be managed, measured in systems per headcount.
·
Scalability - the ability of an information system to be used or produced in a range of capabilities
·
“Updatability”– a key factor linked to performance, integration with other IS and security
https://software.intel.com/en-us/articles/total-cost-of-ownership-factors-to-consider
Top Benefits of Cloud Computing
http://www.mushibhuiyan.com/category/cloud/
Debate
https://www.forbes.com/sites/louiscolumbus/2013/08/13/idg-cloud-computing-survey-security-integration-challenge-growth/#268d6d3755cb
Debate
https://www.forbes.com/sites/louiscolumbus/2013/08/13/idg-cloud-computing-survey-security-integration-challenge-growth/#268d6d3755cbCloud Computing strategy
https://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=WUW12350USEN
www.euruni.edu
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i.
This document provides an overview of a lecture on database management systems. It discusses the history of data collection and storage from ancient times through modern technologies. It then covers key topics to be discussed in the lecture, including the different types of databases, typical functionality of database management systems, and the advantages of the database approach. The document outlines the learning objectives and provides context around the importance of data as a resource and the problems involved with storing and accessing large amounts of data.
Mongo Internal Training session by Soner Altinmustafa sarac
Database management systems first appeared in the 1960s as computers grew more powerful. Navigational databases in the 1960s allowed only sequential processing. Edgar Codd suggested the relational model in the 1970s, allowing users to search databases through integration of navigational and other models. A relational database organizes data in tables based on relations and uses SQL for querying.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
The document discusses aggregation as an intervention tactic to improve discoverability of online content. It argues that early web approaches focused on human accessibility but hid complexity, while aggregation can expose relationships and make content more understandable and findable by machines. Done strategically with purposes of engagement, value-adding, and enhancing discoverability through promiscuous metadata, aggregation can help unlock online riches.
The document discusses ATMOS, a cloud-based content retrieval library. Some key points:
1) ATMOS provides the benefits of cloud computing like convenient APIs, simple metadata-based retrieval and classification, high reliability and security.
2) Using ATMOS as the basis for a content retrieval system could help solve problems with data manipulation and add more universality to retrieval, allowing both machine and manual indexing.
3) The library presented retrieves images that are visually or cognitively similar to a sample image provided by the user, ignoring weak image noises and prioritizing similar shapes and edges.
The document discusses the rise of NoSQL databases as an alternative to traditional relational databases. It provides a brief history of NoSQL, noting that new types of applications and data led developers to look for databases that offer more flexibility and scalability. It also describes the main types of NoSQL databases - key-value stores, graph stores, column stores, and document stores - and discusses some of the advantages of NoSQL databases like flexibility, scalability, availability and lower costs.
1. Library systems are becoming more modular and "unbundled" with separate components like the OPAC, serials management, and acquisitions that can be obtained from different vendors.
2. Library systems are entering the computing mainstream where components use common standards and can be integrated with other campus and organization systems.
3. Libraries need to provide services to patrons through the online locations and devices they are accustomed to using like social media and mobile apps to remain relevant.
The Archives Forum - The National Archives - 02 March 2011David F. Flanders
The document summarizes a presentation given by David F. Flanders about digital infrastructure innovation and the future of archives. It discusses how archives can innovate with limited budgets in the short term by improving search engine optimization, using application programming interfaces, and engaging communities. In the medium term, archives can prepare for increased budgets by crowdsourcing content and metadata from communities. Long term innovations may include addressing why digitization is endless, understanding how context is missing from the web, embracing open licensing, and preparing for technologies like augmented reality.
Similar to The evolution of the collections management system (20)
The Archives Forum - The National Archives - 02 March 2011
The evolution of the collections management system
1. The Evolution of the Collections Database
Ian Rowson
This presentation is about how both changes in technology and wider influences have affected Collections
Management System (CMS) development, and how they will continue to do so. As I represent Adlib
information systems, this talk will have a strong adlib flavour.
I’m going to attempt to break it down into a chronological progression, and try not to get too bogged down in
the technicalities, although of course they do play their part in the story.
The beginnings of collections automation
Libraries led the way with their use of computer systems to store catalogue data in the late 1960s, and as a
software product, Adlib shares this heritage. Prior to this of course, libraries had employed card catalogues.
Computerised library systems largely rely on cataloguing according to the MARC standard, also developed in
the 60s – one copy of a book is, after all, very much like another, and therefore cataloguing can become a
largely automated process. Library catalogues were basically replacement for the old card index system,
workflow processes such as book purchasing and management of loans didn’t follow until later.
Adlib came on the scene in the mid 70’s, and was built using the FORTRAN 4 programming language. The
software was designed as a generic ‘information management’ tool. In other words, a software toolkit for
building database applications, a bit like the modern Microsoft Access or Filemaker Pro.
The first customer system was shipped in 1978.
A restriction on the uptake of automation in libraries was cost. This was the time way before PCs, so
computers were large, and expensive. Adlib software was designed to run on PRIME mini computers.
While researching this presentation I came across this great still from a tv advert for PRIME computers which
I have to share with you. We can laugh at the idea of ‘stepping into the 80s with Prime’, but doesn’t that
picture remind us (those of us who are old enough to remember the 80s, anyway) how far things have
moved on, technologically speaking?
And for me, this is the great dilemma of museum computing. We want to preserve our collections data, like
our collections, into the future. But can we be sure that in 20 years time that we won’t be laughing at the
technology we use today? I think we probably will be.
Technology races ahead at breakneck speed. Obsolescence of computing hardware, operating systems and
software not to mention data storage media are among the greatest risks posed to our data. It’s not just that
these issues may arise if we’re unlucky. They WILL arise, and so we have to be ready for them.
If you take only one thought away from this session, I’d like you to perhaps ponder about data preservation
issues in your own institution.
What led to the demise of PRIME, along with so many other computer manufacturers, was of course the
emergence of the personal computer, the PC. Fortunately, Adlib as a company had anticipated and prepared
for this eventuality, and our software had been successfully ported to MS-DOS, then and so on through the
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2. different versions of Windows, with each development customer’s data was safely carried forward into the
new computing environment.
These changes happened in the form of a continuous evolution. At no point in time was a total cut-off
imposed upon the users of the Adlib software which “forced” them into adopting a new technology. Older
implementations faded away “naturally” and new technology was introduced gradually. This was, and still is,
a deliberate choice allowing users, but also the software developers and support staff, to live through smooth
transitions. For this reason new developments will continue to take place on multiple tracks, but with a
convergence towards the same technology
If planned correctly, a technology transition can occur as a natural process, almost unnoticed by the user.
For example, at the moment we are in the midst of another such transition. Like many of our competitors of a
similar age and heritage, Adlib started off running it’s own ‘proprietary’ or native database platform. This data
format is unique to our software.
Modern IT departments are reluctant to implement such databases, preferring instead to adopt the more
widely employed database platforms, such as MS SQL Server and ORACLE. About 4 years ago we adapted
Adlib to be able to run on those platforms, and we’ve been gradually upgrading customer systems, on
request, to use them.
Eventually we anticipate that the use of the proprietary database will eventually decline, but this process will
likely take a fair number of years. We certainly have no plans any time soon to withdraw support for the
many hundreds of ‘native’ adlib systems which are currently out in the field.
I mentioned earlier about how Adlib was developed as a ’database building kit’. The name ‘adlib’ actually
stands for ‘adaptive library’, meaning the structure of the system is flexible.
Adlib’s application building toolset, which, true to the original concept from the 70s, is shipped with each copy
of the software, enabled the trained system administrator to carry out a whole range of tasks, including
adding new databases or fields or indexes or screen layouts to the system. Such is the capability of this tool
that we have no need to use externally provided database software within our organisation. All our internal
systems, such as our customer relationship management and helpdesk databases, are built using our own
software.
The slide shows one screen from the current version of Adlib designer, which is windows based application.
Back in the early days of Adlib, this functionality was offered but through a character based interface that
ran from the operating system prompt. This was powerful, but quite tricky to use.
A library cataloguing system was the first commercially available product built using Adlib, but it wasn’t long
before customers using this application came to us and asked if we could build them a database for
recording their object collections as well. This was done on an ad-hoc basis, until the emergence of
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3. Collections Trust’s (at that time MDA) Spectrum standard gave clear direction for software developers about
what a museum CMS should look like.
Adlib in fact played a supporting role in the development of the Spectrum standard, and you can be sure we
will continue to do so in future.
Incidentally, the same approach was adopted for the development of the Adlib archive application in the late
90s, although this time the standard to be implemented in the software was the archival management
standard, ISAD(G)
What I’ve simplistically sketched out so far is a linear form of technical development, eventually leading to
the Adlib Museum CMS package in use in over 1,500 institutions worldwide.
However, developments such as this which were mirrored across the world by many software companies,
were not universally welcomed by the museum profession in the early days. In her MA thesis entitled The
Evolution Of Museum Collection Management Software, Perian Sully describes how in the late 60s, IBM and
the US Metropolitan Museum of Art had convened a conference to discuss the future of computer technology
in US museums:
And I quote:
“This concern that curatorial or scholarly product would be overshadowed or undermined by the computer is
a recurrent topic to this day. This fear was summarized in 1968 by curator J.C. Gardin, when discussing the
institutional implications of collections technology. He asks if there is:
a) a danger of substituting superficial, mechanical knowledge for “organic and deeper form of culture” gained
from the personal work of curators,
b) a contradiction between rigidly organized data of the database and the intellectual viewpoints of personal
curatorial files, and
c) a risk of subordinating individual research to “de facto monopolies of information that may eventually have
the power to control the ‘whos’ and ‘whats’ of scientific inquiry?”
Despite the early worries of curators that their oversight and knowledge would not be properly reflected
within these new computer systems, the need for tracking and accountability of objects took centre stage
with other professionals.”
Sully, P (2006)
In other words, the great motivator for the uptake of CMS in US museums was the need to carry out audits
collections to be able to demonstrate accountability.
Sulley continues:
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4. “Museums of all sizes found that they needed to get their record-keeping in order. In the 1960s, large
institutions had led the charge, but during the 1970s mid-sized museums realized that, they too, needed to
make sure their records were in order. Fortunately, computers had decreased substantially in cost. The
microcomputer became widely available to museums with fewer resources.”
Sully, P (2006)
Here in the UK, I would argue that although accountability was no doubt a driver in the early days, a great
impetus was felt in the late 1990’s by the new labour government’s ‘e-learning’ objectives, mainly set by the
National Grid for Learning, the vision for which was first outlined in the report Connecting the Learning
Society (Department for Education & Employment, 1997).
Then there came a swathe of texts focussed on delivering digital collections to fuel an ‘educational provision’
agenda, but these did tend to gloss over issues about the management or curatorship of the digital
collections developed for this purpose: See, for example; A Netful of Jewels: New Museums in the Learning
Age (National Museum Director’s Conference, 1999) and Building the Digital Museum: A National Resource
for the Learning Age.(Smith 2000) Together these texts signalled a new direction in policy which aimed to
fully establish learning as the central function of the museum. New technologies were deemed to be the
method of delivering that service to the wider community (Smith, L 2000).
The funding possibilities which ran ‘on the back of’ these initiatives led to a great expansion of CMS
implementation in the UK. This infamous ‘rush to digitise’ resulted in many projects that opened a window on
to collections data, some of which were perhaps were not quite ready to have a window opened on them –
mainly for reasons of incomplete or unverified data. After all, what museum is not carrying a documentation
backlog?
The overriding desire to open up collections data for educational/public access become a major justification
for accessing funding to undertake a CMS project. This of course, was made possible and desirable by the
increasing growth of the world wide web.
Current CMS have since matured to offer a bewildering array of functionality, not unlike business software
applications, such as MS Word for example. Who uses more than about 20% of the capabilities of these?
Although (like in the library model beforehand) CMS began as simple tools for cataloguing collections, they
are now used to track inventories, donor information, condition reports, artist biographies, exhibition
information, bibliographic texts, and curatorial papers as well as present multimedia files and interface with
the museum’s Website. The function is shifting from being a collections management system to a content
management system.
(Sully, P 2006)
We now take for granted such features as image/multi-media management, driven by needs to provide
exciting interactive material for web users, but enabled by the capabilities of the inexpensive powerful PC.
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5. Also web driven is support for the ‘social networking’ phenomena, we are incorporating into adlib products
the ability to capture User Generated Content such as comments, tagging, uploaded images, etc.
However, despite all this functionality, from my own personal experience, (and this is borne out by Sully’s
research) the CMS installed in the average museum remains quite severely under-utilised. I wonder why this
should be?
Sulley did do some research into this issue. She tells us; Richard Gerrard looked at the number of failed
projects in the past and suggested that failure was a historical trend, because there was often early
enthusiasm for new features, buoyed by an infusion of grants. This, he said, created inflated expectations on
the part of users, a lack of critical examination by developers, and resistance within the institution’s
administrative structure. Soon thereafter, the feature which promises this great advancement in productivity
is abandoned in favor of the next technological wonder.
(Sully, P 2006)
My take on this is that it often seems that the purchase and installation of a CMS is championed by a
particular member of staff. When they leave to go to another job, systems can then often seem to ‘drift’
without direction. What is really needed is for a specific member of staff to be assigned to manage the
system, but often this does not happen in a smaller institution. It is much more reliant on the interests of
particular personalities, whose main job is invariably something else.
I’m going to bring things right up to date, to look at how current trends are shaping the CMS of the future.
A key driver of development at the moment is that of the API – applications programming interface
But what is an API, and why would you need one?
Modern computer program design (service oriented architecture - SOA) promotes the breaking up of
complex applications in small manageable components that communicate with each other using APIs.
Designing programs in this way not only makes a system flexible and scalable, but it also provides a platform
for integration between different software components (even from different vendors). Adlib currently supports
this model to some degree.
Let me give you a real-world example, that of a fairly recent development, the Adlib image handler API.
The idea behind this is as follows.
Adlib, like most other CMS packages, has in-built the capability to display linked images of collection objects.
However, many customers are already using other software with similar capabilities, such as content
management and/or digital asset management packages, leading to overlap and duplication of functionality.
Images which are stored in one software package need to be accessible from the others.
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6. APIs offer a solution to this problem.
The Adlib media handler separates out from our software the image management function, in such a way
that it can be easily accessed by either adlib, or other external software. Furthermore, the possibility is also
raised that images held in other software (such as a DAMS) could be linked to by the Adlib CMS, instead of
using the Adlib image handler.
But we are not stopping there. In future, eventually all programs in the Adlib suite will follow the (SOA)
paradigm. To support this, a new set of APIs being developed, supporting both data access and metadata
access. The modules will be accessible though web services and as “traditional” (managed) DLLs.
External stakeholders (including customers) were invited to cooperate in the API development process
earlier this year, and development is already under way.
Another current development from the IT world is that of Cloud computing – but what does it mean?
I’ve reverted to Wikipedia for an explanation:
Cloud computing is a style of computing in which information technology resources are provided as a service
over the Internet. Users need not have knowledge of, expertise in, or control over the technology
infrastructure "in the cloud" that supports them. The term cloud is used as a metaphor for the Internet, based
on how the Internet is depicted in computer network diagrams, and is an abstraction for the complex
infrastructure it conceals.
The concept incorporates infrastructure as a service (IaaS), and software as a service (SaaS) as well as
other technology trends from the last couple of years that have the common theme of reliance on the Internet
for satisfying the computing needs of the users. Cloud computing services usually provide common business
applications online that are accessed from a web browser, while the software and data are stored on the
remote servers.
The key driver behind cloud computing is that users can avoid capital expenditure on hardware and software,
rather paying a provider only for what they use. Consumption is billed on a utility (e.g. resources consumed,
like electricity) or subscription (e.g. time based, like a newspaper) basis with little or no upfront cost. Other
benefits of this time sharing style approach are low barriers to entry, shared infrastructure and costs, low
management overhead and immediate access to a broad range of applications. Users can generally
terminate the contract at any time (thereby avoiding return on investment risk and uncertainty) and the
services are usually covered by service level agreement
According to Nicholas Carr the strategic importance of information technology is diminishing as it becomes
standardised and cheaper. He argues that the cloud computing paradigm shift is similar to the displacement
of electricity generators by electricity grids early in the 20th century.
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7. (Wikipedia 2009)
Adlib have been offering our CMS systems ‘in the cloud’ as a subscription service for a couple of years now,
and while we have a few, mainly commercial customers using these services, generally speaking uptake
from the museum sector has been slow.
I’d suggest there are a couple of possible reasons for this:
In the UK, museums so far have been able to access funding for capital projects from a variety of
sources. Funding which pays an annual fee, on the other hand, is more difficult to raise.
Museums are reluctant to hand-over custody of their data to an outside organisation, and of course
there are risks associated with this which must be managed.
Wikipedia lists seven security issues which one should discuss with a cloud-computing vendor in order to
mitigate risks:
1. Who has access to your data?
2. Is the vendor is willing to undergo external audits and/or security certifications?
3. Data location—ask if a provider allows for any control over the location of your data
4. Data segregation—is data encryption is available?
5. Recovery—find out what will happen to data in the case of a disaster; do they offer complete
restoration and, if so, how long that would take?
6. Investigative Support—enquire whether a vendor has the ability to investigate any inappropriate or
illegal activity?
7. Long-term viability—ask what will happen to data if the company goes out of business; how will data
be returned and in what format?
In practice, one can best determine data-recovery capabilities by experiment: asking to get back some data,
seeing how long it takes, and verifying that it is correct.
(Wikipedia 2009)
Our brand name ADLIB stands for “ADaptive LIBrary” system and although the use of our software is no
longer restricted to just libraries, the “adaptive” or “flexible” qualification has always been retained as the key
benefit of using our software.
Flexibility in the form of the Adlib Designer toolkit, which allows the trained System Administrator to
make changes to both the database structure, and the behaviour of the software.
Flexibility in the form of APIs which allow tight integration with other software applications in use
within the institution, and allow data to be re-purposed in audio tours, on the web or by digital asset
management systems.
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8. Flexibility in the form of different ways you can run the software – by traditional purchase, or ‘in the
cloud’ as a service.
In the next generation of products we want to move a step further and place even more flexibility in the
hands of the actual user of the system, as opposed to the system administrator. In current versions this
process has already started, for instance by enabling the user to adapt their own toolbar, or by enabling the
user to generate reports on the fly by using the “print wizard”. This principle will be implemented throughout
with more “personal” preferences settings. One can think about search behaviour (e.g. default truncation or
provision of lists) or the appearance of the software (allows the user to add style sheets, personal output
formats, or change colour schemes).
One thing that you can be sure of, is that development of the Adlib product range will remain at leading edge
of CMS development. We understand that technology is a shifting sand on which to build, but we employ
proven strategies to deal with that.
Adlib has the experience and the capability to help all collecting institutions to secure their data for future
generations.
References
SMITH, L., (ed.) (2000) Building the Digital Museum: A National Resource for the Learning Age. Cambridge,
MDA
SULLY, P (2006) Inventory, Access, Interpretation: The Evolution Of Museum Collection Management
Software, [online] MA Thesis, John F. Kennedy University Available at:
http://conference.archimuse.com/biblio/inventory_access_interpretation_the_evolution_of_muse.html
http://en.wikipedia.org/wiki/API
http://en.wikipedia.org/wiki/Cloud_computing
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