slides from our talk "Low-Cost Open Data as-a-service" from the Semantic Web Developers workshop of ESWC'2015 (full paper: http://ceur-ws.org/Vol-1361/paper7.pdf)
Text Analytics & Linked Data Management As-a-ServiceMarin Dimitrov
slides from the talk on "Text Analytics & Linked Data Management As-a-Service with S4" from the ESWC'2015 workshop on Semantic Web Enterprise Adoption & Best Practices
full paper available at http://2015.wasabi-ws.org/papers/wasabi15_1.pdf
On-Demand RDF Graph Databases in the CloudMarin Dimitrov
slides from the S4 webinar "On-Demand RDF Graph Databases in the Cloud"
RDF database-as-a-service running on the Self-Service Semantic Suite (S4) platform: http://s4.ontotext.com
video recording of the talk is available at http://info.ontotext.com/on-demand-rdf-graph-database
Enabling Low-cost Open Data Publishing and ReuseMarin Dimitrov
In the space of just a few years we’ve seen the transformational power of open data; both for transparency and accountability in public data, and efficiency and innovation with businesses in private data. In its first year, institutions and individuals throughout Europe have supported public sector bodies in releasing data and numerous start-ups, developers and SMEs in reusing this data for economic benefit.
However, we are still at the beginning of the open data movement, and there is still more that can be done to make open data simpler to use and to make it available to a wider audience.
The core goal of the DaPaaS project is to provide a Data- and Platform-as-a-Service environment, where 3rd parties (such as governmental organisations, SMEs, developers and larger companies) can publish and host both data sets and data-intensive applications, which can then be accessed by end-user applications in a cross-platform manner. You can find out more about DaPaaS on the detailed about page.
Essentially, DaPaaS aims to make publishing, consumption, and reuse of open data, as well as deploying open data applications, easier and cheaper for SMEs and small public bodies which otherwise may not have sufficient technical expertise, infrastructure and resources required to do so.
see also http://www.slideshare.net/eswcsummerschool/wed-roman-tutopendatapub-38742186
overview of the RDF graph database-as-a-service (GraphDB based) on the Self-Service Semantic Suite (S4)
http://s4.ontotext.com
presentation for the AKSW Group of the University of Leipzig
Text Analytics & Linked Data Management As-a-ServiceMarin Dimitrov
slides from the talk on "Text Analytics & Linked Data Management As-a-Service with S4" from the ESWC'2015 workshop on Semantic Web Enterprise Adoption & Best Practices
full paper available at http://2015.wasabi-ws.org/papers/wasabi15_1.pdf
On-Demand RDF Graph Databases in the CloudMarin Dimitrov
slides from the S4 webinar "On-Demand RDF Graph Databases in the Cloud"
RDF database-as-a-service running on the Self-Service Semantic Suite (S4) platform: http://s4.ontotext.com
video recording of the talk is available at http://info.ontotext.com/on-demand-rdf-graph-database
Enabling Low-cost Open Data Publishing and ReuseMarin Dimitrov
In the space of just a few years we’ve seen the transformational power of open data; both for transparency and accountability in public data, and efficiency and innovation with businesses in private data. In its first year, institutions and individuals throughout Europe have supported public sector bodies in releasing data and numerous start-ups, developers and SMEs in reusing this data for economic benefit.
However, we are still at the beginning of the open data movement, and there is still more that can be done to make open data simpler to use and to make it available to a wider audience.
The core goal of the DaPaaS project is to provide a Data- and Platform-as-a-Service environment, where 3rd parties (such as governmental organisations, SMEs, developers and larger companies) can publish and host both data sets and data-intensive applications, which can then be accessed by end-user applications in a cross-platform manner. You can find out more about DaPaaS on the detailed about page.
Essentially, DaPaaS aims to make publishing, consumption, and reuse of open data, as well as deploying open data applications, easier and cheaper for SMEs and small public bodies which otherwise may not have sufficient technical expertise, infrastructure and resources required to do so.
see also http://www.slideshare.net/eswcsummerschool/wed-roman-tutopendatapub-38742186
overview of the RDF graph database-as-a-service (GraphDB based) on the Self-Service Semantic Suite (S4)
http://s4.ontotext.com
presentation for the AKSW Group of the University of Leipzig
Sigma EE: Reaping low-hanging fruits in RDF-based data integrationRichard Cyganiak
A presentation I gave at I-Semantics 2010 on Sigma EE, an RDF-based data integration front-end.
Sigma EE is now available for download here: http://sig.ma/?page=help
The Evolution of the Fashion Retail Industry in the Age of AI with Kshitij Ku...Databricks
AI is fundamentally transforming how we live and work.
Zalando is a data driven company. We deliver an optimal customer experience that drives engagement. We continue to improve this experience by leveraging the latest technologies and machine learning techniques — such as building a cutting edge cloud based infrastructure to support our operations at scale.
We provide our data scientists across Zalando with the means to implement artificial intelligence use cases, leveraging data from all parts of our company and the best machine learning techniques from across the industry. Apache Spark delivered through Databricks is at the core of this strategy.
In this keynote, I’ll share our AI journey thus far, and share how we are exploring ways to unify data through A.I. with Spark and Databricks.
Дмитрий Лавриненко "Big & Fast Data for Identity & Telemetry services"Fwdays
- Business goal
- What is Fast Data for us
- What is Fast & Big Data solution
- Reference Architecture
- Data Science for Big Data
- Technology Stack
- Solution Architecture
- Identity & Telemetry Data Processing Facts
- Continuous Deployment
- Quality Control
Scylla Summit 2022: Scalable and Sustainable Supply Chains with DLT and ScyllaDBScyllaDB
Explore how IOTA addressed supply chain digitization challenges, including the role of data serialization formats (EPCIS 2.0), Distributed Ledgers (IOTA), and scalable, resilient databases (ScyllaDB) across specific use cases.
To watch all of the recordings hosted during Scylla Summit 2022 visit our website here: https://www.scylladb.com/summit.
Narasimhan Sampath and Avinash Ramineni share how Choice Hotels International used Spark Streaming, Kafka, Spark, and Spark SQL to create an advanced analytics platform that enables business users to be self-reliant by accessing the data they need from a variety of sources to generate customer insights and property dashboards and enable data-driven decisions with minimal IT engagement. Narasimhan and Avinash highlight the architecture, lessons learned, and the challenges that were overcome on both the business and technology fronts.
The analytics platform is designed as a framework to enable self-service data intake, data processing, and report/model generation by the business users. The data-driven framework consists of a distributed hybrid-cloud data ingestor for data intake and a Cloudera CDH cluster with Spark as the distributed compute engine. The solution is built in such a way that storage and compute have been decoupled and encourages the concept of BYOC (bring your own compute). The platform uses EC2 instances to run CDH and leverages Amazon S3 as a data warehouse storage layer (data lake), Spark as an ETL engine, and Spark SQL as a distributed query engine. Results (computations/derived tables) are exposed to the end users via Spark SQL and are discovered via Tableau. The platform supports both batch and streaming use cases and is built on the following technology stack: AWS (S3, EC2, SQS, SNS), Cloudera CDH (YARN, Navigator, Sentry), Spark, Kafka, Spark SQL, and Spark Streaming.
Streaming data in the cloud with Confluent and MongoDB Atlas | Robert Waters,...HostedbyConfluent
Are you looking for a cloud-based architecture that includes the best of breed streaming and database technologies? In this session you will learn how to setup and configure the Confluent Cloud with MongoDB Atlas. We'll start the journey learning about the basic connectivity between the two cloud services and end with a brief discovery of what you can do with data once it is in MongoDB Atlas. By the end of this session you will know how to securely setup and configure the MongoDB Atlas connectors in the Confluent Cloud in both a source and sink configuration.
In this webinar Thomas Cook, Sales Director, AnzoGraph DB, provides a history lesson on the origins of SPARQL, including its roots in the Semantic Web, and how linked open data is used to create Knowledge Graphs. Then, he dives into "What is RDF?", "What is a URI?" and "What is SPARQL?", wrapping up with a real-world demonstration via a Zeppelin notebook.
When We Spark and When We Don’t: Developing Data and ML PipelinesStitch Fix Algorithms
The data platform at Stitch Fix runs thousands of jobs a day to feed data products that provide algorithmic capabilities to power nearly all aspects of the business, from merchandising to operations to styling recommendations. Many of these jobs are distributed across Spark clusters, while many others are scheduled as isolated single-node tasks in containers running Python, R, or Scala. Pipelines are often comprised of a mix of task types and containers.
This talk will cover thoughts and guidelines on how we develop, schedule, and maintain these pipelines at Stitch Fix. We’ll discuss guidelines on how we think about which portions of the pipelines we develop to run on what platforms (e.g. what is important to run distributed across Spark clusters vs run in stand-alone containers) and how we get them to play well together. We’ll also provide an overview of tools and abstractions that have been developed at Stitch Fix to facilitate the process from development, to deployment, to monitoring them in production.
It’s All About The Cards: Sharing on Social Media Encouraged HTML Metadata G...Shawn Jones
In a perfect world, all articles consistently contain sufficient metadata to describe the resource. We know this is not the reality, so we are motivated to investigate the evolution of the metadata that is present when authors and publishers supply their own. Because applying metadata takes time, we recognize that each news article author has a limited metadata budget with which to spend their time and effort. How are they spending this budget? What are the top metadata categories in use? How did they grow over time? What purpose do they serve? We also recognize that not all metadata fields are used equally. What is the growth of individual fields over time? Which fields experienced the fastest adoption? In this paper, we review 227,726 HTML news articles from 29 outlets captured by the Internet Archive between 1998 and 2016. Upon reviewing the metadata fields in each article, we discovered that 2010 began a metadata renaissance as publishers embraced metadata for improved search engine ranking, search engine tracking, social media tracking, and social media sharing. When analyzing individual fields, we find that one application of metadata stands out above all others: social cards -- the cards generated by platforms like Twitter when one shares a URL. Once a metadata standard was established for cards in 2010, its fields were adopted by 20% of articles in the first year and reached more than 95% adoption by 2016. This rate of adoption surpasses efforts like schema.org and Dublin Core by a fair margin. When confronted with these results on how news publishers spend their metadata budget, we must conclude that it is all about the cards.
Simplified minimalistic workflows for the publication of Linked Open DataSalvatore Virtuoso
Our colleague Yuri Glikman of Fraunhofer FOKUS (LinDA partner) presented the LinDA transformation tool at the recent Samos Summit (http://samos-summit.blogspot.de/).
Personalization allows Stitch Fix to style its clients and provide recommendations to help them find what they love. To do this, the company gathers information about a client’s preferences up front when they sign up from the service and learns more about them as they become longer-term customers. This information is important for making recommendations but also must be protected and managed with care.
The data science team at Stitch Fix is the primary owner of the recommendation systems. Backing them up is the data platform team, who maintain the data infrastructure, data warehouse, and supporting tools and services. This data warehouse has several different data sources that read and write into it. This includes a logging pipeline for events, every Spark-based ETL, and daily snapshots of structured data from Stitch Fix applications.
Neelesh Srinivas Salian explains Stitch Fix’s process to better understand the movement and evolution of data within its data warehouse, from the initial ingestion from outside sources through all of its ETLs. Neelesh also details how Stitch Fix built a service that helps the company understand the lineage information that is associated with each table in the data warehouse. This service helps the company understand the source, parentage, and journey of all data in the warehouse. Although Stitch Fix makes sure to anonymize and filter out sensitive information from this data, the company needs a more flexible long-term solution as the business expands.
Scalable Data Management for Kafka and Beyond | Dan Rice, BigIDHostedbyConfluent
Data in motion has changed both the scale and scope of data and analytics - enabling organizations to capture more information and use it more effectively. But to get the most value from it - you need to know what’s there, make it risk aware, and take action on it. In this session, you’ll learn how to leverage modern ML-augmented data management solutions to automatically find, identify, and classify sensitive data across Spark, Databricks, and beyond - and how to apply policies for compliance and risk mitigation to get the most value from our data.
Jan van Ansem - Help a friend: how the Developers community can help to get Data Warehousing development up to date with modern development technology.
PGDay.Amsterdam 2018 - Jeroen de Graaff - Step-by-step implementation of Post...PGDay.Amsterdam
Rijkswaterstaat is the Service of the Ministry of Infrastructure and Water Management in the Netherlands. During this presentation, I will share our journey to develop and apply PostgreSQL at Rijkswaterstaat. Our work is ICT-driven and access to our data, both historical and actual is key for executing our task now and in the future.
presentation from the 5th "EC Framework Programmes - funding opportunities" seminar organised by the Applied Research and Communications Fund
http://www.arcfund.net/arcartShow.php?id=16150
Sigma EE: Reaping low-hanging fruits in RDF-based data integrationRichard Cyganiak
A presentation I gave at I-Semantics 2010 on Sigma EE, an RDF-based data integration front-end.
Sigma EE is now available for download here: http://sig.ma/?page=help
The Evolution of the Fashion Retail Industry in the Age of AI with Kshitij Ku...Databricks
AI is fundamentally transforming how we live and work.
Zalando is a data driven company. We deliver an optimal customer experience that drives engagement. We continue to improve this experience by leveraging the latest technologies and machine learning techniques — such as building a cutting edge cloud based infrastructure to support our operations at scale.
We provide our data scientists across Zalando with the means to implement artificial intelligence use cases, leveraging data from all parts of our company and the best machine learning techniques from across the industry. Apache Spark delivered through Databricks is at the core of this strategy.
In this keynote, I’ll share our AI journey thus far, and share how we are exploring ways to unify data through A.I. with Spark and Databricks.
Дмитрий Лавриненко "Big & Fast Data for Identity & Telemetry services"Fwdays
- Business goal
- What is Fast Data for us
- What is Fast & Big Data solution
- Reference Architecture
- Data Science for Big Data
- Technology Stack
- Solution Architecture
- Identity & Telemetry Data Processing Facts
- Continuous Deployment
- Quality Control
Scylla Summit 2022: Scalable and Sustainable Supply Chains with DLT and ScyllaDBScyllaDB
Explore how IOTA addressed supply chain digitization challenges, including the role of data serialization formats (EPCIS 2.0), Distributed Ledgers (IOTA), and scalable, resilient databases (ScyllaDB) across specific use cases.
To watch all of the recordings hosted during Scylla Summit 2022 visit our website here: https://www.scylladb.com/summit.
Narasimhan Sampath and Avinash Ramineni share how Choice Hotels International used Spark Streaming, Kafka, Spark, and Spark SQL to create an advanced analytics platform that enables business users to be self-reliant by accessing the data they need from a variety of sources to generate customer insights and property dashboards and enable data-driven decisions with minimal IT engagement. Narasimhan and Avinash highlight the architecture, lessons learned, and the challenges that were overcome on both the business and technology fronts.
The analytics platform is designed as a framework to enable self-service data intake, data processing, and report/model generation by the business users. The data-driven framework consists of a distributed hybrid-cloud data ingestor for data intake and a Cloudera CDH cluster with Spark as the distributed compute engine. The solution is built in such a way that storage and compute have been decoupled and encourages the concept of BYOC (bring your own compute). The platform uses EC2 instances to run CDH and leverages Amazon S3 as a data warehouse storage layer (data lake), Spark as an ETL engine, and Spark SQL as a distributed query engine. Results (computations/derived tables) are exposed to the end users via Spark SQL and are discovered via Tableau. The platform supports both batch and streaming use cases and is built on the following technology stack: AWS (S3, EC2, SQS, SNS), Cloudera CDH (YARN, Navigator, Sentry), Spark, Kafka, Spark SQL, and Spark Streaming.
Streaming data in the cloud with Confluent and MongoDB Atlas | Robert Waters,...HostedbyConfluent
Are you looking for a cloud-based architecture that includes the best of breed streaming and database technologies? In this session you will learn how to setup and configure the Confluent Cloud with MongoDB Atlas. We'll start the journey learning about the basic connectivity between the two cloud services and end with a brief discovery of what you can do with data once it is in MongoDB Atlas. By the end of this session you will know how to securely setup and configure the MongoDB Atlas connectors in the Confluent Cloud in both a source and sink configuration.
In this webinar Thomas Cook, Sales Director, AnzoGraph DB, provides a history lesson on the origins of SPARQL, including its roots in the Semantic Web, and how linked open data is used to create Knowledge Graphs. Then, he dives into "What is RDF?", "What is a URI?" and "What is SPARQL?", wrapping up with a real-world demonstration via a Zeppelin notebook.
When We Spark and When We Don’t: Developing Data and ML PipelinesStitch Fix Algorithms
The data platform at Stitch Fix runs thousands of jobs a day to feed data products that provide algorithmic capabilities to power nearly all aspects of the business, from merchandising to operations to styling recommendations. Many of these jobs are distributed across Spark clusters, while many others are scheduled as isolated single-node tasks in containers running Python, R, or Scala. Pipelines are often comprised of a mix of task types and containers.
This talk will cover thoughts and guidelines on how we develop, schedule, and maintain these pipelines at Stitch Fix. We’ll discuss guidelines on how we think about which portions of the pipelines we develop to run on what platforms (e.g. what is important to run distributed across Spark clusters vs run in stand-alone containers) and how we get them to play well together. We’ll also provide an overview of tools and abstractions that have been developed at Stitch Fix to facilitate the process from development, to deployment, to monitoring them in production.
It’s All About The Cards: Sharing on Social Media Encouraged HTML Metadata G...Shawn Jones
In a perfect world, all articles consistently contain sufficient metadata to describe the resource. We know this is not the reality, so we are motivated to investigate the evolution of the metadata that is present when authors and publishers supply their own. Because applying metadata takes time, we recognize that each news article author has a limited metadata budget with which to spend their time and effort. How are they spending this budget? What are the top metadata categories in use? How did they grow over time? What purpose do they serve? We also recognize that not all metadata fields are used equally. What is the growth of individual fields over time? Which fields experienced the fastest adoption? In this paper, we review 227,726 HTML news articles from 29 outlets captured by the Internet Archive between 1998 and 2016. Upon reviewing the metadata fields in each article, we discovered that 2010 began a metadata renaissance as publishers embraced metadata for improved search engine ranking, search engine tracking, social media tracking, and social media sharing. When analyzing individual fields, we find that one application of metadata stands out above all others: social cards -- the cards generated by platforms like Twitter when one shares a URL. Once a metadata standard was established for cards in 2010, its fields were adopted by 20% of articles in the first year and reached more than 95% adoption by 2016. This rate of adoption surpasses efforts like schema.org and Dublin Core by a fair margin. When confronted with these results on how news publishers spend their metadata budget, we must conclude that it is all about the cards.
Simplified minimalistic workflows for the publication of Linked Open DataSalvatore Virtuoso
Our colleague Yuri Glikman of Fraunhofer FOKUS (LinDA partner) presented the LinDA transformation tool at the recent Samos Summit (http://samos-summit.blogspot.de/).
Personalization allows Stitch Fix to style its clients and provide recommendations to help them find what they love. To do this, the company gathers information about a client’s preferences up front when they sign up from the service and learns more about them as they become longer-term customers. This information is important for making recommendations but also must be protected and managed with care.
The data science team at Stitch Fix is the primary owner of the recommendation systems. Backing them up is the data platform team, who maintain the data infrastructure, data warehouse, and supporting tools and services. This data warehouse has several different data sources that read and write into it. This includes a logging pipeline for events, every Spark-based ETL, and daily snapshots of structured data from Stitch Fix applications.
Neelesh Srinivas Salian explains Stitch Fix’s process to better understand the movement and evolution of data within its data warehouse, from the initial ingestion from outside sources through all of its ETLs. Neelesh also details how Stitch Fix built a service that helps the company understand the lineage information that is associated with each table in the data warehouse. This service helps the company understand the source, parentage, and journey of all data in the warehouse. Although Stitch Fix makes sure to anonymize and filter out sensitive information from this data, the company needs a more flexible long-term solution as the business expands.
Scalable Data Management for Kafka and Beyond | Dan Rice, BigIDHostedbyConfluent
Data in motion has changed both the scale and scope of data and analytics - enabling organizations to capture more information and use it more effectively. But to get the most value from it - you need to know what’s there, make it risk aware, and take action on it. In this session, you’ll learn how to leverage modern ML-augmented data management solutions to automatically find, identify, and classify sensitive data across Spark, Databricks, and beyond - and how to apply policies for compliance and risk mitigation to get the most value from our data.
Jan van Ansem - Help a friend: how the Developers community can help to get Data Warehousing development up to date with modern development technology.
PGDay.Amsterdam 2018 - Jeroen de Graaff - Step-by-step implementation of Post...PGDay.Amsterdam
Rijkswaterstaat is the Service of the Ministry of Infrastructure and Water Management in the Netherlands. During this presentation, I will share our journey to develop and apply PostgreSQL at Rijkswaterstaat. Our work is ICT-driven and access to our data, both historical and actual is key for executing our task now and in the future.
presentation from the 5th "EC Framework Programmes - funding opportunities" seminar organised by the Applied Research and Communications Fund
http://www.arcfund.net/arcartShow.php?id=16150
Много често, когато искаме да станем по-добри backend програмисти се опитваме да научим различни езици за програмиране и съответните библиотеки. Проблема е че в Rails, Express.js, Django или Zend Framework има горе долу едни и същи концепции. Ако искаме да се научим как да пишем код за големи системи, които скалират добре и се справят сами с различни грешки и неочаквани ситуации, трябва да овладеем един друг дял от човешкото познание, който се нарича разпределени системи. В моята презентация ще видим защо трябва да задълбаем в тях и какви са основните принципи като консистентност(consistency), достъпност(availability) и издръжливост на разделения(partition tolerance). Също, ще разгледаме стъпки, които всеки може да направи за да научи повече по темата и да получава нови и актуални знания.
As software engineers we do trade-offs every day. We often need to pick between things like space vs time or budget vs scope. Or sometimes the amount of creative waste we can afford to have. And when we make the decision we need to be in full comprehension of both the upside and downside of a particular choice. In this talk we will discuss why our organization decided to move from Python to Java. We will go over each tradeoff we decided to do and the motivation behind it.
Dec'2013 webinar from the EUCLID project on managing large volumes of Linked Data
webinar recording at https://vimeo.com/84126769 and https://vimeo.com/84126770
more info on EUCLID: http://euclid-project.eu/
Crossing the Chasm with Semantic TechnologyMarin Dimitrov
After more than a decade of active efforts towards establishing Semantic Web, Linked Data and related standards, the verdict of whether the technology has delivered its promise and has proven itself in the enterprise is still unclear, despite the numerous existing success stories.
Every emerging technology and disruptive innovation has to overcome the challenge of “crossing the chasm” between the early adopters, who are just eager to experiment with the technology potential, and the majority of the companies, who need a proven technology that can be reliably used in mission critical scenarios and deliver quantifiable cost savings.
Succeeding with a Semantic Technology product in the enterprise is a challenging task involving both top quality research and software development practices, but most often the technology adoption challenges are not about the quality of the R&D but about successful business model generation and understanding the complexities and challenges of the technology adoption lifecycle by the enterprise.
This talk will discuss topics related to the challenge of “crossing the chasm” for a Semantic Technology product and provide examples from Ontotext’s experience of successfully delivering Semantic Technology solutions to enterprises.
Capital One: Using Cassandra In Building A Reporting PlatformDataStax Academy
As a leader in the financial industry, Capital One applications generate huge amounts of data that require fast and accurate handling, storage and analysis. We are transforming how we report operational data to our internal users so that they can make quick and precise business decisions to serve our customers. As part of this transformation, we are building a new Go-based data processing framework that will enable us to transfer data from multiple data stores (RDBMS, files, etc.) to a single NoSQL database - Cassandra. This new NoSQL store will act as a reporting database that will receive data on a near real-time basis and serve the data through scorecards and reports. We would like to share our experience in defining this fast data platform and the methodologies used to model financial data in Cassandra.
Ingest, Transform & Visualize w Amazon Web ServicesBigDataCamp
Startups and enterprises derive actionable insights from a myriad of data sources that are growing rapidly and must be processed quickly. While most organizations understand the pivotal role that data can play for their business, the process of transforming data and analytics from a concept to an actual business driver is often less clear. Arun will talk about how organizations can determine what they need from their IT infrastructure to turn raw data into valuable answers and insights.
Weathering the Data Storm – How SnapLogic and AWS Deliver Analytics in the Cl...SnapLogic
In this webinar, learn how SnapLogic and Amazon Web Services helped Earth Networks create a responsive, self-service cloud for data integration, preparation and analytics.
We also discuss how Earth Networks gained faster data insights using SnapLogic’s Amazon Redshift data integration and other connectors to quickly integrate, transfer and analyze data from multiple applications.
To learn more, visit: www.snaplogic.com/redshift
Serverless is the future of the cloud or is it?
And the launch of the Whitepaper on ethics in cloud and data centre 2018 - bit.ly/2024wp - sign the pledge https://change.org/p/sustainable-servers-by-2024
During the “Architecting for the Cloud” breakfast seminar where we discussed the requirements of modern cloud-based applications and how to overcome the confinement of traditional on-premises infrastructure.
We heard from data management practitioners and cloud strategists about how organizations are meeting the challenges associated with building new or migrating existing applications to the cloud.
Finally, we discussed how the right cloud-based architecture can:
- Handle rapid user growth by adding new servers on demand
- Provide high performance even in the face of heavy application usage
- Offer around-the-clock resiliency and uptime
- Provide easy and fast access across multiple geographies
- Deliver cloud-enabled apps in public, private, or hybrid cloud environments
Pragmatic Enterprise Application Migration to AWSKacy Clarke
A presentation given to the Boston AWS Meetup on July 14, 2015, with best practices for migrating mission critical enterprise applications to production on AWS
Choosing technologies for a big data solution in the cloudJames Serra
Has your company been building data warehouses for years using SQL Server? And are you now tasked with creating or moving your data warehouse to the cloud and modernizing it to support “Big Data”? What technologies and tools should use? That is what this presentation will help you answer. First we will cover what questions to ask concerning data (type, size, frequency), reporting, performance needs, on-prem vs cloud, staff technology skills, OSS requirements, cost, and MDM needs. Then we will show you common big data architecture solutions and help you to answer questions such as: Where do I store the data? Should I use a data lake? Do I still need a cube? What about Hadoop/NoSQL? Do I need the power of MPP? Should I build a "logical data warehouse"? What is this lambda architecture? Can I use Hadoop for my DW? Finally, we’ll show some architectures of real-world customer big data solutions. Come to this session to get started down the path to making the proper technology choices in moving to the cloud.
The Common BI/Big Data Challenges and Solutions presented by seasoned experts, Andriy Zabavskyy (BI Architect) and Serhiy Haziyev (Director of Software Architecture).
This was a complimentary workshop where attendees had the opportunity to learn, network and share knowledge during the lunch and education session.
Horses for Courses: Database RoundtableEric Kavanagh
The blessing and curse of today's database market? So many choices! While relational databases still dominate the day-to-day business, a host of alternatives has evolved around very specific use cases: graph, document, NoSQL, hybrid (HTAP), column store, the list goes on. And the database tools market is teeming with activity as well. Register for this special Research Webcast to hear Dr. Robin Bloor share his early findings about the evolving database market. He'll be joined by Steve Sarsfield of HPE Vertica, and Robert Reeves of Datical in a roundtable discussion with Bloor Group CEO Eric Kavanagh. Send any questions to info@insideanalysis.com, or tweet with #DBSurvival.
Silwood Webinar: Comparing data models for different instances of CRM and ERP...Roland Bullivant
The need to find the differences and variances in the data models of different instances of packaged ERP and CRM is often overlooked in a project - until it becomes necessary.
This is important in many data intensive initiatives where an organisation has multiple instances of an application or is involved in an upgrade, merge or migration event. In situations where development or customisation work is being performed under Agile Sprint conditions the need to identify and manage iterations of the data model is critical.
For many smaller systems with easily accessible and understood data models this is a relatively straightforward process. For packages from SAP, Oracle, Salesforce and Microsoft however it is much more difficult and requires a specialist tool to enable comparison to be done quickly, accurately and easily.
Safyr provides those abilities and more for the world's most complex packages applications. This webinar explores the need for comparison across a range of projects and illustrates how Safyr can make light of a difficult and time consuming task.
Transform your DBMS to drive engagement innovation with Big DataAshnikbiz
Erik Baardse and Ajit Gadge from EDB Postgres presented on how to transform your DBMS in order to drive digital business. How Postgres enables you to support a wider range of workloads with your relational database which opens the Big Data doors. They also cover EnterpriseDB’s Strategy around Big Data which focuses on 3 areas and finally last but not the last how to find money in IT with Big Data and digital transformation
Slides from ThousandEyes EMEA webinar on Thursday March 7th 2019 at 1000 GMT. Presented by Ian Waters, Director of Solutions Marketing and Tim Hale, Solutions Engineer. Content focuses on the move of enterprises to SD-WAN technologies and WAN transformation in general.
Measuring the Productivity of Your Engineering Organisation - the Good, the B...Marin Dimitrov
High-performing engineering teams regularly dedicate time on measuring the performance & quality of the systems and applications they’re building or on measuring & improving the various aspects of the development lifecycle. High-performing product companies are also data-driven when it comes to measuring the impact of new features & products in terms of business KPIs and Northstar metrics.
Can a data-driven approach be applied to measuring the performance, maturity and continuous improvement of an engineering team or the whole engineering organisation? In this discussion we’ll cover various important topics related to quantifying the performance of an engineering organisation
The career development of our teammates is among the key responsibilities of a leader - and оur personal career development vision & plan plays a critical role for our long term growth and success. Despite their importance, our career vision is often not getting enough attention and level of detail, or is hampered by easily avoidable mistakes. In this discussion, we’ll address typical mistakes related to long-term career planning, some best practices, and practical steps for building our own long-term career development vision (or the ones of the teammates we are leading), so that career planning becomes a long term journey with clear why/how/what, rather than just a list of SMART goals
Uber began its open source journey in 2015 when three passionate engineers decided to contribute Uber’s work back to the community. In only four years, Uber’s open source program has fostered 350+ outstanding open source projects with 2,000+ contributors worldwide delivering over 70,000 commits. Since 2017, four of Uber’s open source projects have won InfoWorld’s Best of Open Source Software Awards. In this talk, Brian Hsieh & Marin Dimitrov will share more details on Uber’s open source journey, program and best practices, and how Uber enables open innovation by fostering a healthy and collaborative open source culture
Trust - the Key Success Factor for Teams & OrganisationsMarin Dimitrov
>>> Most leaders agree that trust is a key factor for the success o the team and the organisation and that they are actively working to build trust. And yet, various studies imply that almost half of the teams and organisations worldwide experience lower trust levels with their managers, teammates and the rest of the organisation, which leads to decreased engagement, productivity and success.
>>> In this talk we will discuss why trust is a key success factor for every team and every organisation, some good practices for building, sustaining and rebuilding trust, as well as the most common mistakes related to trust building
talk @ the Computer Science department of Sofia University - practical advice for career growth for students
DEV.BG event http://dev.bg/%D1%81%D1%8A%D0%B1%D0%B8%D1%82%D0%B8%D0%B5/fmi-club-%D0%BF%D1%80%D0%B0%D0%BA%D1%82%D0%B8%D1%87%D0%BD%D0%B8-%D1%81%D1%8A%D0%B2%D0%B5%D1%82%D0%B8-%D0%B7%D0%B0-%D0%BA%D0%B0%D1%80%D0%B8%D0%B5%D1%80%D0%BD%D0%BE-%D1%80%D0%B0%D0%B7%D0%B2%D0%B8%D1%82/
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Assuring Contact Center Experiences for Your Customers With ThousandEyes
Low-cost Open Data As-a-Service
1. Low-cost Open Data As-a-Service
Marin Dimitrov, Alex Simov, Yavor Petkov
May 31st, 2015
Low-cost Open Data as-a-Service / SemDev’2015 #1May 2015
2. • Use cases & requirements
• Cloud architecture for a RDF DBaaS
• Lessons learned
Contents
#2May 2015Low-cost Open Data as-a-Service / SemDev’2015
3. Use Cases & Requirements
#3May 2015Low-cost Open Data as-a-Service / SemDev’2015
4. Why an RDF DBaaS?
#4May 2015Low-cost Open Data as-a-Service / SemDev’2015
Grafter Grafterizer
RDF DBaaSOpen Data Portal
• Transform tabular data into RDF
• Publish (Linked) data services,
instead of static datasets
• Lower-cost & easier data
publishing process
5. Why an RDF DBaaS?
#5May 2015Low-cost Open Data as-a-Service / SemDev’2015
• Transform textual data into RDF
• Linked data services
• Low-cost & easy to use
6. • Elastic
– dynamically adapt to growing data & query volumes
• High availability & resilience
– no SPFs, “graceful degradation” upon failures
• Cost efficient
• Host a large number of data services (databases)
– But probably of low/moderate data & query volume
• Isolation of the multi-tenant databases
DBaaS requirements
#6May 2015Low-cost Open Data as-a-Service / SemDev’2015
Not easy to
achieve all three!
8. • AWS based
– Network storage, compute & autoscaling, load
balancing, integration services, …
• Ontotext GraphDB as the RDF DB engine
– OpenRDF REST API
• Docker for containerisation
• An RDF DBaaS is…
– A GraphDB instance…
– Running within a Docker container…
– Storing its data on a private NAS volume
DBaaS architecture on AWS
#8May 2015Low-cost Open Data as-a-Service / SemDev’2015
9. DBaaS architecture on AWS
#9May 2015Low-cost Open Data as-a-Service / SemDev’2015
Elasticity vs
High Availability vs
Cost Efficiency
10. Dealing with failures
#10May 2015Low-cost Open Data as-a-Service / SemDev’2015
our responsibility
CSP responsibility
11. • Elastic
– Routing nodes, data nodes + NAS storage grow as usage
grows
• High availability & resilience
– Strategies for dealing with failures in data, routing,
Coordinator nodes
– Planned: multi-DC deployment with replication
• Cost efficient
– Cloud native architecture -> cost savings
– Multi-tenant model -> cost savings
– Elastic: return underutilised or unused resources back
to CSP
Evaluation
#11May 2015Low-cost Open Data as-a-Service / SemDev’2015
13. • Cloud-native architecture
– Improved scalability, reliability, cost savings
• A microservice architecture will continuously
evolve
• Assume that failures will happen on all levels
– Design for “graceful degradation”
• A good DevOps process is essential
Lessons Learned
#13May 2015Low-cost Open Data as-a-Service / SemDev’2015
15. • Use it for free!
– http://s4.ontotext.com (available NOW)
– http://dapaas.eu (end of June)
• Send us questions, comments, criticism,
suggestions for improvements, …
Help us improve it!
#15May 2015Low-cost Open Data as-a-Service / SemDev’2015
16. • Are you measuring the TCO of your on-premise
RDF databases?
– Important for many Open Data scenarios
• What is your #1 concern for using an RDF DBaaS
• Do you have use cases where your productivity
will increase by using an RDF DBaaS
– Experiment & prototype faster; focus on building apps,
don’t worry about infrastructure; provision new DBs
instantly…
– Real world example: training courses by Ontotext
switching from local deployments to the RDF DBaaS
Discussion topics
#16May 2015Low-cost Open Data as-a-Service / SemDev’2015