RavenDB intro, what it is and how it works plus take a trip inside finstat.sk development kitchen to find out how to solve a practical problem the impractical way.
The document discusses reasons why someone might want to learn Clojure, a functional programming language. It addresses both obvious reasons like curiosity about new technologies as well as less obvious reasons like stepping out of one's comfort zone. It acknowledges doubts about functional programming and discusses how adopting Clojure offers benefits like easier refactoring. While learning a new language takes time, functional programming techniques can be rewarding to learn. The document provides resources for learning Clojure.
A talk on Data Science in Piano, contains the following:
1. Tips on how to make sure your data are analysis-friendly
2. A short introduction into how to do data science with a for loop (partially stolen from https://goo.gl/wHwZKv)
3. A brief look on output evolution for paywall health check for our clients (publishers)
4. A sneak peek into challenges we face currently
Partying with PHP (…and the Microsoft Platform)goodfriday
Learn how to spice up PHP using the unique features of the Microsoft platform. PHP is the center of attention as you learn to build and run a PHP application on Microsoft Internet Information Services 7, and also mingle with the Microsoft AJAX library.
Using Spark Streaming and NiFi for the next generation of ETL in the enterpriseDataWorks Summit
On paper, combining Apache NiFi, Kafka, and Spark Streaming provides a compelling architecture option for building your next generation ETL data pipeline in near real time. What does this look like in enterprise production environment to deploy and operationalized?
The newer Spark Structured Streaming provides fast, scalable, fault-tolerant, end-to-end exactly-once stream processing with elegant code samples, but is that the whole story? This session will cover the Royal Bank of Canada’s (RBC) journey of moving away from traditional ETL batch processing with Teradata towards using the Hadoop ecosystem for ingesting data. One of the first systems to leverage this new approach was the Event Standardization Service (ESS). This service provides a centralized “client event” ingestion point for the bank’s internal systems through either a web service or text file daily batch feed. ESS allows down stream reporting applications and end users to query these centralized events.
We discuss the drivers and expected benefits of changing the existing event processing. In presenting the integrated solution, we will explore the key components of using NiFi, Kafka, and Spark, then share the good, the bad, and the ugly when trying to adopt these technologies into the enterprise. This session is targeted toward architects and other senior IT staff looking to continue their adoption of open source technology and modernize ingest/ETL processing. Attendees will take away lessons learned and experience in deploying these technologies to make their journey easier.
Speakers
Darryl Sutton, T4G, Principal Consultant
Kenneth Poon, RBC, Director, Data Engineering
PHP, LAMP, Windows, ASP.NET ?????? Sometimes you can't choose just one.
In this session, long time PHP developer and Microsoft MisfitGeek with explore the plethora of ways you can make PHP and ASP.NET interoperate.
Big Data & NoSQL - EFS'11 (Pavlo Baron)Pavlo Baron
That's the slides of my half day workshop at the EFS'11 in Stuttgart where I covered some theoretical aspects of NoSQL data stores relevant for dealing with large data amounts
Dean Wampler, O’Reilly author and Big Data Strategist in the office of the CTO at Lightbend discusses practical tips for architecting stream-processing applications and explains how you can tame some of the complexity in moving from data at rest to data in motion.
The document discusses reasons why someone might want to learn Clojure, a functional programming language. It addresses both obvious reasons like curiosity about new technologies as well as less obvious reasons like stepping out of one's comfort zone. It acknowledges doubts about functional programming and discusses how adopting Clojure offers benefits like easier refactoring. While learning a new language takes time, functional programming techniques can be rewarding to learn. The document provides resources for learning Clojure.
A talk on Data Science in Piano, contains the following:
1. Tips on how to make sure your data are analysis-friendly
2. A short introduction into how to do data science with a for loop (partially stolen from https://goo.gl/wHwZKv)
3. A brief look on output evolution for paywall health check for our clients (publishers)
4. A sneak peek into challenges we face currently
Partying with PHP (…and the Microsoft Platform)goodfriday
Learn how to spice up PHP using the unique features of the Microsoft platform. PHP is the center of attention as you learn to build and run a PHP application on Microsoft Internet Information Services 7, and also mingle with the Microsoft AJAX library.
Using Spark Streaming and NiFi for the next generation of ETL in the enterpriseDataWorks Summit
On paper, combining Apache NiFi, Kafka, and Spark Streaming provides a compelling architecture option for building your next generation ETL data pipeline in near real time. What does this look like in enterprise production environment to deploy and operationalized?
The newer Spark Structured Streaming provides fast, scalable, fault-tolerant, end-to-end exactly-once stream processing with elegant code samples, but is that the whole story? This session will cover the Royal Bank of Canada’s (RBC) journey of moving away from traditional ETL batch processing with Teradata towards using the Hadoop ecosystem for ingesting data. One of the first systems to leverage this new approach was the Event Standardization Service (ESS). This service provides a centralized “client event” ingestion point for the bank’s internal systems through either a web service or text file daily batch feed. ESS allows down stream reporting applications and end users to query these centralized events.
We discuss the drivers and expected benefits of changing the existing event processing. In presenting the integrated solution, we will explore the key components of using NiFi, Kafka, and Spark, then share the good, the bad, and the ugly when trying to adopt these technologies into the enterprise. This session is targeted toward architects and other senior IT staff looking to continue their adoption of open source technology and modernize ingest/ETL processing. Attendees will take away lessons learned and experience in deploying these technologies to make their journey easier.
Speakers
Darryl Sutton, T4G, Principal Consultant
Kenneth Poon, RBC, Director, Data Engineering
PHP, LAMP, Windows, ASP.NET ?????? Sometimes you can't choose just one.
In this session, long time PHP developer and Microsoft MisfitGeek with explore the plethora of ways you can make PHP and ASP.NET interoperate.
Big Data & NoSQL - EFS'11 (Pavlo Baron)Pavlo Baron
That's the slides of my half day workshop at the EFS'11 in Stuttgart where I covered some theoretical aspects of NoSQL data stores relevant for dealing with large data amounts
Dean Wampler, O’Reilly author and Big Data Strategist in the office of the CTO at Lightbend discusses practical tips for architecting stream-processing applications and explains how you can tame some of the complexity in moving from data at rest to data in motion.
This document discusses using Apache Spark and Amazon DSSTNE to generate product recommendations at scale. It summarizes that Amazon uses Spark and Zeppelin notebooks to allow data scientists to develop queries in an agile manner. Deep learning jobs are run on GPUs using Amazon ECS, while CPU jobs run on Amazon EMR. DSSTNE is optimized for large sparse neural networks and allows defining networks in a human-readable JSON format to efficiently handle Amazon's large recommendation problems.
Lightbend Fast Data Platform - A Technical Overview
Dean Wampler, O’Reilly author and Big Data Strategist in the office of the CTO at Lightbend discusses practical tips for architecting stream-processing applications and explains how you can tame some of the complexity in moving from data at rest to data in motion.
For the first time in 15 years, Microsoft introduces a new way for building modern cloud-based Web applications using ASP.NET. Branded as ASP.NET Core 1.0, the new platform, redesigned from the ground, provides an optimized development framework for apps that span from on-premises to cloud based solutions. In this session, we will highlight the changes and walk through the new concepts.
Jilles van Gurp discusses logging and monitoring trends and introduces the ELK stack as a solution. The ELK stack consists of Elasticsearch for storage and search, Logstash for transport and processing, and Kibana for visualization. Proper logging is important - log enough but not too much. Logstash is used to ingest logs into Elasticsearch. An Inbot demo shows logging various services and visualizing logs in Kibana. Mapped diagnostic context and application metrics are discussed as ways to add useful context to logs.
From Raghu Ramakrishnan's presentation "Key Challenges in Cloud Computing and How Yahoo! is Approaching Them" at the 2009 Cloud Computing Expo in Santa Clara, CA, USA. Here's the talk description on the Expo's site: http://cloudcomputingexpo.com/event/session/510
Millions of internet packets are sent each day to connect devices and route traffic on the global network. The internet relies on protocols like BGP to exchange routing information between nodes. Hadoop and HDFS provide a scalable way to store and process large amounts of unstructured data across clusters of machines. Users can launch Hadoop clusters in AWS using tools like Whirr to run analytics jobs without managing hardware.
The document provides an overview of the Microsoft database stack, including the various SQL Server products that make up the stack. It discusses some of the hard problems databases help solve, such as query plan generation and ensuring data consistency. It also covers file layouts and I/O patterns for different SQL Server file types.
DynamoDB is a NoSQL database service built for fast, scalable, consistent performance. This presentation introduces DynamoDB and discusses how to get started, provision throughput, design for the DynamoDB data model, query and scan tables and scale reads and writes without downtime.
This document discusses different API options for databases: REST, gRPC, and GraphQL. It begins with an overview of Apache Cassandra and its key features as a distributed database. It then covers an API design methodology, including conceptual and logical data modeling, mapping queries to tables, and creating the physical schema. The document presents criteria for evaluating API choices and provides pros and cons of REST, gRPC, and GraphQL. It concludes that REST is best for CRUD operations, gRPC for high performance services, and GraphQL for discoverability and flexible payloads.
Fast and Simplified Streaming, Ad-Hoc and Batch Analytics with FiloDB and Spa...Helena Edelson
O'Reilly Webcast with Myself and Evan Chan on the new SNACK Stack (playoff of SMACK) with FIloDB: Scala, Spark Streaming, Akka, Cassandra, FiloDB and Kafka.
Webinar - Big Data: Let's SMACK - Jorg SchadCodemotion
The document discusses big data processing and the SMACK stack. It introduces Mesosphere and Apache Mesos as enabling distributed applications by multiplexing workloads across servers. It then covers components of the SMACK stack - including Apache Kafka for ingestion, Apache Spark for storage and analysis, Apache Cassandra for analytics, and Akka for acting on data. It discusses choosing messaging and stream processing systems and highlights Mesos support.
Designing big data analytics solutions on azureMohamed Tawfik
This document discusses designing big data analytics solutions on Azure. It provides an overview of Azure's data landscape and common architectural patterns and scenarios for building analytics solutions using various Azure data and analytics services. These include Azure SQL Data Warehouse, Azure Data Lake Store, Azure Data Factory, Azure Machine Learning, and Power BI for reporting and visualization. The document also discusses using these services to build solutions for scenarios like data warehousing, data lakes, ETL/ELT, machine learning, streaming analytics and more.
Apache Spark is a fast, general-purpose, and easy-to-use cluster computing system for large-scale data processing. It provides APIs in Scala, Java, Python, and R. Spark is versatile and can run on YARN/HDFS, standalone, or Mesos. It leverages in-memory computing to be faster than Hadoop MapReduce. Resilient Distributed Datasets (RDDs) are Spark's abstraction for distributed data. RDDs support transformations like map and filter, which are lazily evaluated, and actions like count and collect, which trigger computation. Caching RDDs in memory improves performance of subsequent jobs on the same data.
The document discusses Microsoft's Entity Framework ORM technology. It provides an overview of Entity Framework and how it compares to other ORM technologies like LINQ to SQL. It also outlines Microsoft's strategy of promoting Entity Framework as the preferred .NET ORM going forward.
The document is an agenda for an AWS Cloud School in London. It outlines that the event will cover cloud concepts, building blocks, application lifecycle, high availability web services, and have two hands-on sessions. It will also include deep dive sessions on various AWS services like compute, databases, storage, and tools & support. The agenda notes that they are currently in the first hands-on session.
Microsoft provides an AI platform and tools for developers to build, train, and deploy intelligent applications and services. Key elements of Microsoft's AI offerings include:
- A unified AI platform spanning infrastructure, tools, and services to make AI accessible and useful for every developer.
- Powerful tools for AI development including deep learning frameworks, coding and management tools, and AI services for tasks like computer vision, natural language processing, and more.
- Capabilities for training models at scale using GPU accelerated compute on Azure and deploying trained models as web APIs, mobile apps, or other applications.
- A focus on trusted, responsible, and inclusive AI that puts users in control and augments rather than replaces human
The document discusses different NoSQL databases including Cassandra, CouchDB, MongoDB, Neo4J, and Redis. It explains some of the key concepts of NoSQL databases like being non-relational, schema-less, and emphasizing availability and partition tolerance. It provides brief overviews of the data models and architectures of different NoSQL databases and how they handle concepts like distribution, replication, and querying.
Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdfVALiNTRY360
Salesforce Healthcare CRM, implemented by VALiNTRY360, revolutionizes patient management by enhancing patient engagement, streamlining administrative processes, and improving care coordination. Its advanced analytics, robust security, and seamless integration with telehealth services ensure that healthcare providers can deliver personalized, efficient, and secure patient care. By automating routine tasks and providing actionable insights, Salesforce Healthcare CRM enables healthcare providers to focus on delivering high-quality care, leading to better patient outcomes and higher satisfaction. VALiNTRY360's expertise ensures a tailored solution that meets the unique needs of any healthcare practice, from small clinics to large hospital systems.
For more info visit us https://valintry360.com/solutions/health-life-sciences
This document discusses using Apache Spark and Amazon DSSTNE to generate product recommendations at scale. It summarizes that Amazon uses Spark and Zeppelin notebooks to allow data scientists to develop queries in an agile manner. Deep learning jobs are run on GPUs using Amazon ECS, while CPU jobs run on Amazon EMR. DSSTNE is optimized for large sparse neural networks and allows defining networks in a human-readable JSON format to efficiently handle Amazon's large recommendation problems.
Lightbend Fast Data Platform - A Technical Overview
Dean Wampler, O’Reilly author and Big Data Strategist in the office of the CTO at Lightbend discusses practical tips for architecting stream-processing applications and explains how you can tame some of the complexity in moving from data at rest to data in motion.
For the first time in 15 years, Microsoft introduces a new way for building modern cloud-based Web applications using ASP.NET. Branded as ASP.NET Core 1.0, the new platform, redesigned from the ground, provides an optimized development framework for apps that span from on-premises to cloud based solutions. In this session, we will highlight the changes and walk through the new concepts.
Jilles van Gurp discusses logging and monitoring trends and introduces the ELK stack as a solution. The ELK stack consists of Elasticsearch for storage and search, Logstash for transport and processing, and Kibana for visualization. Proper logging is important - log enough but not too much. Logstash is used to ingest logs into Elasticsearch. An Inbot demo shows logging various services and visualizing logs in Kibana. Mapped diagnostic context and application metrics are discussed as ways to add useful context to logs.
From Raghu Ramakrishnan's presentation "Key Challenges in Cloud Computing and How Yahoo! is Approaching Them" at the 2009 Cloud Computing Expo in Santa Clara, CA, USA. Here's the talk description on the Expo's site: http://cloudcomputingexpo.com/event/session/510
Millions of internet packets are sent each day to connect devices and route traffic on the global network. The internet relies on protocols like BGP to exchange routing information between nodes. Hadoop and HDFS provide a scalable way to store and process large amounts of unstructured data across clusters of machines. Users can launch Hadoop clusters in AWS using tools like Whirr to run analytics jobs without managing hardware.
The document provides an overview of the Microsoft database stack, including the various SQL Server products that make up the stack. It discusses some of the hard problems databases help solve, such as query plan generation and ensuring data consistency. It also covers file layouts and I/O patterns for different SQL Server file types.
DynamoDB is a NoSQL database service built for fast, scalable, consistent performance. This presentation introduces DynamoDB and discusses how to get started, provision throughput, design for the DynamoDB data model, query and scan tables and scale reads and writes without downtime.
This document discusses different API options for databases: REST, gRPC, and GraphQL. It begins with an overview of Apache Cassandra and its key features as a distributed database. It then covers an API design methodology, including conceptual and logical data modeling, mapping queries to tables, and creating the physical schema. The document presents criteria for evaluating API choices and provides pros and cons of REST, gRPC, and GraphQL. It concludes that REST is best for CRUD operations, gRPC for high performance services, and GraphQL for discoverability and flexible payloads.
Fast and Simplified Streaming, Ad-Hoc and Batch Analytics with FiloDB and Spa...Helena Edelson
O'Reilly Webcast with Myself and Evan Chan on the new SNACK Stack (playoff of SMACK) with FIloDB: Scala, Spark Streaming, Akka, Cassandra, FiloDB and Kafka.
Webinar - Big Data: Let's SMACK - Jorg SchadCodemotion
The document discusses big data processing and the SMACK stack. It introduces Mesosphere and Apache Mesos as enabling distributed applications by multiplexing workloads across servers. It then covers components of the SMACK stack - including Apache Kafka for ingestion, Apache Spark for storage and analysis, Apache Cassandra for analytics, and Akka for acting on data. It discusses choosing messaging and stream processing systems and highlights Mesos support.
Designing big data analytics solutions on azureMohamed Tawfik
This document discusses designing big data analytics solutions on Azure. It provides an overview of Azure's data landscape and common architectural patterns and scenarios for building analytics solutions using various Azure data and analytics services. These include Azure SQL Data Warehouse, Azure Data Lake Store, Azure Data Factory, Azure Machine Learning, and Power BI for reporting and visualization. The document also discusses using these services to build solutions for scenarios like data warehousing, data lakes, ETL/ELT, machine learning, streaming analytics and more.
Apache Spark is a fast, general-purpose, and easy-to-use cluster computing system for large-scale data processing. It provides APIs in Scala, Java, Python, and R. Spark is versatile and can run on YARN/HDFS, standalone, or Mesos. It leverages in-memory computing to be faster than Hadoop MapReduce. Resilient Distributed Datasets (RDDs) are Spark's abstraction for distributed data. RDDs support transformations like map and filter, which are lazily evaluated, and actions like count and collect, which trigger computation. Caching RDDs in memory improves performance of subsequent jobs on the same data.
The document discusses Microsoft's Entity Framework ORM technology. It provides an overview of Entity Framework and how it compares to other ORM technologies like LINQ to SQL. It also outlines Microsoft's strategy of promoting Entity Framework as the preferred .NET ORM going forward.
The document is an agenda for an AWS Cloud School in London. It outlines that the event will cover cloud concepts, building blocks, application lifecycle, high availability web services, and have two hands-on sessions. It will also include deep dive sessions on various AWS services like compute, databases, storage, and tools & support. The agenda notes that they are currently in the first hands-on session.
Microsoft provides an AI platform and tools for developers to build, train, and deploy intelligent applications and services. Key elements of Microsoft's AI offerings include:
- A unified AI platform spanning infrastructure, tools, and services to make AI accessible and useful for every developer.
- Powerful tools for AI development including deep learning frameworks, coding and management tools, and AI services for tasks like computer vision, natural language processing, and more.
- Capabilities for training models at scale using GPU accelerated compute on Azure and deploying trained models as web APIs, mobile apps, or other applications.
- A focus on trusted, responsible, and inclusive AI that puts users in control and augments rather than replaces human
The document discusses different NoSQL databases including Cassandra, CouchDB, MongoDB, Neo4J, and Redis. It explains some of the key concepts of NoSQL databases like being non-relational, schema-less, and emphasizing availability and partition tolerance. It provides brief overviews of the data models and architectures of different NoSQL databases and how they handle concepts like distribution, replication, and querying.
Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdfVALiNTRY360
Salesforce Healthcare CRM, implemented by VALiNTRY360, revolutionizes patient management by enhancing patient engagement, streamlining administrative processes, and improving care coordination. Its advanced analytics, robust security, and seamless integration with telehealth services ensure that healthcare providers can deliver personalized, efficient, and secure patient care. By automating routine tasks and providing actionable insights, Salesforce Healthcare CRM enables healthcare providers to focus on delivering high-quality care, leading to better patient outcomes and higher satisfaction. VALiNTRY360's expertise ensures a tailored solution that meets the unique needs of any healthcare practice, from small clinics to large hospital systems.
For more info visit us https://valintry360.com/solutions/health-life-sciences
Artificia Intellicence and XPath Extension FunctionsOctavian Nadolu
The purpose of this presentation is to provide an overview of how you can use AI from XSLT, XQuery, Schematron, or XML Refactoring operations, the potential benefits of using AI, and some of the challenges we face.
UI5con 2024 - Bring Your Own Design SystemPeter Muessig
How do you combine the OpenUI5/SAPUI5 programming model with a design system that makes its controls available as Web Components? Since OpenUI5/SAPUI5 1.120, the framework supports the integration of any Web Components. This makes it possible, for example, to natively embed own Web Components of your design system which are created with Stencil. The integration embeds the Web Components in a way that they can be used naturally in XMLViews, like with standard UI5 controls, and can be bound with data binding. Learn how you can also make use of the Web Components base class in OpenUI5/SAPUI5 to also integrate your Web Components and get inspired by the solution to generate a custom UI5 library providing the Web Components control wrappers for the native ones.
Mobile App Development Company In Noida | Drona InfotechDrona Infotech
Drona Infotech is a premier mobile app development company in Noida, providing cutting-edge solutions for businesses.
Visit Us For : https://www.dronainfotech.com/mobile-application-development/
Everything You Need to Know About X-Sign: The eSign Functionality of XfilesPr...XfilesPro
Wondering how X-Sign gained popularity in a quick time span? This eSign functionality of XfilesPro DocuPrime has many advancements to offer for Salesforce users. Explore them now!
Project Management: The Role of Project Dashboards.pdfKarya Keeper
Project management is a crucial aspect of any organization, ensuring that projects are completed efficiently and effectively. One of the key tools used in project management is the project dashboard, which provides a comprehensive view of project progress and performance. In this article, we will explore the role of project dashboards in project management, highlighting their key features and benefits.
The Key to Digital Success_ A Comprehensive Guide to Continuous Testing Integ...kalichargn70th171
In today's business landscape, digital integration is ubiquitous, demanding swift innovation as a necessity rather than a luxury. In a fiercely competitive market with heightened customer expectations, the timely launch of flawless digital products is crucial for both acquisition and retention—any delay risks ceding market share to competitors.
Consistent toolbox talks are critical for maintaining workplace safety, as they provide regular opportunities to address specific hazards and reinforce safe practices.
These brief, focused sessions ensure that safety is a continual conversation rather than a one-time event, which helps keep safety protocols fresh in employees' minds. Studies have shown that shorter, more frequent training sessions are more effective for retention and behavior change compared to longer, infrequent sessions.
Engaging workers regularly, toolbox talks promote a culture of safety, empower employees to voice concerns, and ultimately reduce the likelihood of accidents and injuries on site.
The traditional method of conducting safety talks with paper documents and lengthy meetings is not only time-consuming but also less effective. Manual tracking of attendance and compliance is prone to errors and inconsistencies, leading to gaps in safety communication and potential non-compliance with OSHA regulations. Switching to a digital solution like Safelyio offers significant advantages.
Safelyio automates the delivery and documentation of safety talks, ensuring consistency and accessibility. The microlearning approach breaks down complex safety protocols into manageable, bite-sized pieces, making it easier for employees to absorb and retain information.
This method minimizes disruptions to work schedules, eliminates the hassle of paperwork, and ensures that all safety communications are tracked and recorded accurately. Ultimately, using a digital platform like Safelyio enhances engagement, compliance, and overall safety performance on site. https://safelyio.com/
Unveiling the Advantages of Agile Software Development.pdfbrainerhub1
Learn about Agile Software Development's advantages. Simplify your workflow to spur quicker innovation. Jump right in! We have also discussed the advantages.
Liberarsi dai framework con i Web Component.pptxMassimo Artizzu
In Italian
Presentazione sulle feature e l'utilizzo dei Web Component nell sviluppo di pagine e applicazioni web. Racconto delle ragioni storiche dell'avvento dei Web Component. Evidenziazione dei vantaggi e delle sfide poste, indicazione delle best practices, con particolare accento sulla possibilità di usare web component per facilitare la migrazione delle proprie applicazioni verso nuovi stack tecnologici.
2. I am …
I have MS OS, MS PC, MS Keyboard, MS mouse, MS headphones,
?MS phone?
even this font is MS designed
So when I found out, that there is pure managed NoSQL solution
there was no other choice
3. So finstat.sk was born
Aggregates multiple external sources
Data processing/monitoring
200k unique users from Slovakia per month
5. THIS IS RAVENDB
But in reality
CAP theorem problem
CQRS
ESENT/JET
key/value store
LUCENE.NET
indexing engine
DATA QUERY
by id
All others
QUERIES
7. Will it scale?
Replication
Master-Master, Master-Slave, all other
Client side sharding
Auto-failure switch
8. Developer is a customer - Client API
LINQ (type support)
Caching
Aggressive caching
Multi-get
Transactions
Bulk insert
Data subscription
Patching
Transformers
Even more
9. We love Ops
Built-in studio
Previously Silverlight now HTML5 (DurandalJS based)
10. Personal experience
Earlier 0.x versions – freezing/performance problems
2.x – “locate your own bug in source”
Stable enough 3.0.35xx
Real performance gain 3.0.36xx (30-40%)
New versions on the way out