Glenn Cedströmer fra Visit Technology Group orienterte om hvordan VTG vil håndtere innhold i den nasjonale booking switchen. Kick-off innholdsprosjektet Nasjonal Booking 1.juni.
Big Data 'State of the Union' (BDT101) | AWS re:Invent 2013Amazon Web Services
Big Data is more than petabytes and capacity. It is the opportunity to use data to your advantage to make smart decisions that increase productivity and grow your business. In this session, you'll learn about the latest advancements in data analytics, databases, storage, and high performance computing (HPC) at AWS and discover how to put data to work in your own organization.
Geographic information systems (GIS) are great for capturing, storing, analyzing, and managing data and
associated attributes of spatially referenced points on earth. In the strictest sense, GIS displays only geographical
information. But have you ever considered other information being included? How about documents and assets
– they have locations on earth. We can understand a wealth of information by adding spatial components.
This presentation presents the common challenges in building an analytics platform (audience platform is chosen as the use case) and provides a few guidelines and recommendations on how to address them. The presentation starts with motivating the need for such a platform and the components that make it up. It then provides common design options for these components and suggests alternatives for them. The presentation concludes with a design proposal that is being evaluated for the audience platform in Inmobi.
When it comes to dealing with large, complex, and disparate data sets, traditional database technologies are unable to keep pace with the rich analytics necessary to power today’s data-driven applications. Graph analytics databases are becoming the underlying infrastructure for AI and machine learning. These databases allow users to ask complex questions across complex data, which is not always practical or even possible at scale using other approaches. They also enable faster insights against massive data sets when combined with pattern recognition, statistical analysis, and AI/ machine learning. And in the case of standards-based graph databases, they connect with popular visualization tools like Graphileon, allowing users to easily explore their data stores and quickly build compelling graph-based applications.
Big Data 'State of the Union' (BDT101) | AWS re:Invent 2013Amazon Web Services
Big Data is more than petabytes and capacity. It is the opportunity to use data to your advantage to make smart decisions that increase productivity and grow your business. In this session, you'll learn about the latest advancements in data analytics, databases, storage, and high performance computing (HPC) at AWS and discover how to put data to work in your own organization.
Geographic information systems (GIS) are great for capturing, storing, analyzing, and managing data and
associated attributes of spatially referenced points on earth. In the strictest sense, GIS displays only geographical
information. But have you ever considered other information being included? How about documents and assets
– they have locations on earth. We can understand a wealth of information by adding spatial components.
This presentation presents the common challenges in building an analytics platform (audience platform is chosen as the use case) and provides a few guidelines and recommendations on how to address them. The presentation starts with motivating the need for such a platform and the components that make it up. It then provides common design options for these components and suggests alternatives for them. The presentation concludes with a design proposal that is being evaluated for the audience platform in Inmobi.
When it comes to dealing with large, complex, and disparate data sets, traditional database technologies are unable to keep pace with the rich analytics necessary to power today’s data-driven applications. Graph analytics databases are becoming the underlying infrastructure for AI and machine learning. These databases allow users to ask complex questions across complex data, which is not always practical or even possible at scale using other approaches. They also enable faster insights against massive data sets when combined with pattern recognition, statistical analysis, and AI/ machine learning. And in the case of standards-based graph databases, they connect with popular visualization tools like Graphileon, allowing users to easily explore their data stores and quickly build compelling graph-based applications.
Big Data, IoT, data lake, unstructured data, Hadoop, cloud, and massively parallel processing (MPP) are all just fancy words unless you can find uses cases for all this technology. Join me as I talk about the many use cases I have seen, from streaming data to advanced analytics, broken down by industry. I’ll show you how all this technology fits together by discussing various architectures and the most common approaches to solving data problems and hopefully set off light bulbs in your head on how big data can help your organization make better business decisions.
Is your organization considering migrating an existing data center over to AWS to reduce cost, improve reliability, security, and operational performance of your IT operations? If so, join us for a webinar on how to plan and execute your migration to the cloud from classification of applications, assessing your application needs, identifying the target applications and other various migration strategies.
Castle in the clouds - Building the Connexys SaaS application with Fusion Mid...Lucas Jellema
SaaS applications serve users in many organizations from a single application instance running in a cloud. Common SaaS requirements include: customization including hiding and adding fields, managing boilerplate text & influencing the look & feel and a Service API for retrieving and manipulating data as well as allowing registration of listeners - applications outside the cloud that are notified by the SaaS application of events. Deep link navigation into the SaaS application allows visual integration with local apps.
Connexys provides a SaaS application (150+ customers) to support human resource and recruitment processes. The Connexys NextGen application is developed on Fusion Middleware using ADF. The application has an impressive number of specific SaaS enhancements (some inspired by Salesforce.com) that make it a compelling & competitive SaaS offering.
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Field Activity Planner SaaS SW for the Digital OilfieldOlav Sylthe
Field Activity Planner is a SaaS SW for timeline 2D/3D visualization of dependencies and cost in work processes for offshore installations and marine operations. Thus allowing you to save time and money and moving into digital oilfield solutions available 24/7 in your browser.
Enterprise Data and Analytics Architecture Overview for Electric UtilityPrajesh Bhattacharya
How would you go about creating an enterprise data and analytics architecture for electric utility that 1) will be relevant in the long run, 2) will be easy to implement and 3) will start bringing value to the organization fairly quickly? What will be the components? Who will be the users? The operation of electric utility will change significantly by 2025. How will you future-proof the architecture?
How to Exchange Data between CAD and GISSafe Software
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Building Analytic Apps for SaaS: “Analytics as a Service”Amazon Web Services
TIBCO Jaspersoft® for AWS is a business intelligence suite that helps you deliver stunning interactive reports and dashboards inside your app that make it easy for your customers to get answers. Purpose-built for AWS, our reporting and analytics server quickly and easily connects to Amazon Relational Database Service (RDS), Amazon Redshift, and Amazon EMR. It includes ad-hoc reporting, dashboards, data analysis, data visualization, and data blending. In less than 10 minutes, you can be analyzing and reporting on your data. You get a full Cloud BI server starting at less than $1/hour, with no user or data limits and no additional fees.
This webinar deck shows how embeddable analytics with TIBCO Jaspersoft for AWS gives you the power to create the experience your end users demand and how to scale and manage that experience across your customer base with AWS.
AWS Summit Berlin 2013 - Building web scale applications with AWSAWS Germany
AWS provides a platform that is ideally suited for deploying highly available and reliable systems that can scale with a minimal amount of human interaction. This talk describes a set of architectural patterns that support highly available services that are also scalable, low cost, low latency and allow for agile development practices. We walk through the various architectural decisions taken for each tier and explain our choices for appropriate AWS services and building blocks to ensure the security, scale, availability and reliability of the application.
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Description
The data warehouse has been an analytics workhorse for decades. Unprecedented volumes of data, new types of data, and the need for advanced analyses like machine learning brought on the age of the data lake. But Hadoop by itself doesn't really live up to the hype. Now, many companies have a data lake, a data warehouse, or a mishmash of both, possibly combined with a mandate to go to the cloud. The end result can be a sprawling mess, a lot of duplicated effort, a lot of missed opportunities, a lot of projects that never made it into production, and a lot of financial investment without return. Technical and spiritual unification of the two opposed camps can make a powerful impact on the effectiveness of analytics for the business overall. Over time, different organizations with massive IoT workloads have found practical ways to bridge the artificial gap between these two data management strategies. Look under the hood at how companies have gotten IoT ML projects working, and how their data architectures have changed over time. Learn about new architectures that successfully supply the needs of both business analysts and data scientists. Get a peek at the future. In this area, no one likes surprises.
*Look at successful data architectures from companies like Philips, Anritsu, Uber,
*Learn to eliminate duplication of effort between data science and BI data engineering teams
*Avoid some of the traps that have caused so many big data analytics implementations to fail
*Get AI and ML projects into production where they have real impact, without bogging down essential BI
*Study analytics architectures that work, why and how they work, and where they're going from here
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Paige Roberts,Vertica, Open Source Relations Manager
Webinar: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.InfiniteGraph
This August 16, 2011 webinar, hosted by DBTA with InfiniteGraph, examines the technology behind InfiniteGraph and explores common use cases involving very large scale graph processing, and social network analysis. InfiniteGraph was designed specifically to traverse complex relationships in big data, and provide the framework for products built to provide real-time network analysis, business decision support and relationship analytics. Moderator: Tom Wilson, President, DBTA and Unisphere Research. Presenters: Darren Wood, Chief Architect, InfiniteGraph, and Mark Maagdenberg, Senior Field Engineer, InfiniteGraph.
Data Driven Advanced Analytics using Denodo Platform on AWSDenodo
Watch full webinar here: https://buff.ly/3JC8gCS
Accelerating cloud adoption and modernizing analytics in the cloud has become a necessity to facilitate timely, insightful, and impactful decision making. However, with the widespread data in an organization across disparate hybrid cloud data sources poses a challenge with real time and well governed analytics. Data Virtualization is a modern data integration technique in which a single semantic layer can be built to help drive data democratization and speed up the analytics in an efficient and cost-effective manner.
Watch this session to learn:
- How various AWS services (Redshift, S3, RDS) can be quickly integrated using Denodo Platform’s logical data management by implementing a logical data fabric (LDF)
- How LDF helps you manage and deliver your data for data science and analytics programs, supporting your business users.
- How governed Data Services layer enables self-service analytics in your complex AWS data landscape
Hans Petter Aalmo Innholdsseminar nasjonal booking VisitNorwayBIT Reiseliv
Hans Petter Aalmo i VisitNorway understreket i sitt innlegg hvor viktig korrekt, troverdig og oppdatert innhold også er for VisitNorway. Kick-off innholdsprosjektet Nasjonal Booking 1.juni.
Kjell Galstad, Elisabeth Anspach og Anita Melzer, BIT Reiseliv, presenterer analyse over innhold på bookingportaler. Og presenterer behovet for å standardisere informasjonen som skal ut i Nasjonal Booking Switch. Kick-off innholdsprosjekt Nasjonal Booking.
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Big Data, IoT, data lake, unstructured data, Hadoop, cloud, and massively parallel processing (MPP) are all just fancy words unless you can find uses cases for all this technology. Join me as I talk about the many use cases I have seen, from streaming data to advanced analytics, broken down by industry. I’ll show you how all this technology fits together by discussing various architectures and the most common approaches to solving data problems and hopefully set off light bulbs in your head on how big data can help your organization make better business decisions.
Is your organization considering migrating an existing data center over to AWS to reduce cost, improve reliability, security, and operational performance of your IT operations? If so, join us for a webinar on how to plan and execute your migration to the cloud from classification of applications, assessing your application needs, identifying the target applications and other various migration strategies.
Castle in the clouds - Building the Connexys SaaS application with Fusion Mid...Lucas Jellema
SaaS applications serve users in many organizations from a single application instance running in a cloud. Common SaaS requirements include: customization including hiding and adding fields, managing boilerplate text & influencing the look & feel and a Service API for retrieving and manipulating data as well as allowing registration of listeners - applications outside the cloud that are notified by the SaaS application of events. Deep link navigation into the SaaS application allows visual integration with local apps.
Connexys provides a SaaS application (150+ customers) to support human resource and recruitment processes. The Connexys NextGen application is developed on Fusion Middleware using ADF. The application has an impressive number of specific SaaS enhancements (some inspired by Salesforce.com) that make it a compelling & competitive SaaS offering.
Build vs buy : data pipeline - approachspry_pradeep
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Field Activity Planner SaaS SW for the Digital OilfieldOlav Sylthe
Field Activity Planner is a SaaS SW for timeline 2D/3D visualization of dependencies and cost in work processes for offshore installations and marine operations. Thus allowing you to save time and money and moving into digital oilfield solutions available 24/7 in your browser.
Enterprise Data and Analytics Architecture Overview for Electric UtilityPrajesh Bhattacharya
How would you go about creating an enterprise data and analytics architecture for electric utility that 1) will be relevant in the long run, 2) will be easy to implement and 3) will start bringing value to the organization fairly quickly? What will be the components? Who will be the users? The operation of electric utility will change significantly by 2025. How will you future-proof the architecture?
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TIBCO Jaspersoft® for AWS is a business intelligence suite that helps you deliver stunning interactive reports and dashboards inside your app that make it easy for your customers to get answers. Purpose-built for AWS, our reporting and analytics server quickly and easily connects to Amazon Relational Database Service (RDS), Amazon Redshift, and Amazon EMR. It includes ad-hoc reporting, dashboards, data analysis, data visualization, and data blending. In less than 10 minutes, you can be analyzing and reporting on your data. You get a full Cloud BI server starting at less than $1/hour, with no user or data limits and no additional fees.
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AWS Summit Berlin 2013 - Building web scale applications with AWSAWS Germany
AWS provides a platform that is ideally suited for deploying highly available and reliable systems that can scale with a minimal amount of human interaction. This talk describes a set of architectural patterns that support highly available services that are also scalable, low cost, low latency and allow for agile development practices. We walk through the various architectural decisions taken for each tier and explain our choices for appropriate AWS services and building blocks to ensure the security, scale, availability and reliability of the application.
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*Look at successful data architectures from companies like Philips, Anritsu, Uber,
*Learn to eliminate duplication of effort between data science and BI data engineering teams
*Avoid some of the traps that have caused so many big data analytics implementations to fail
*Get AI and ML projects into production where they have real impact, without bogging down essential BI
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Watch full webinar here: https://buff.ly/3JC8gCS
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- How LDF helps you manage and deliver your data for data science and analytics programs, supporting your business users.
- How governed Data Services layer enables self-service analytics in your complex AWS data landscape
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