Many complex applications scale up by using several different databases, i.e. selecting the best DBMS for each use case. This tends to complicate modern architecture with many products by different vendors, no standards, and a lot of ETL which ultimately causes unpredictable results and a lot of headaches. Multi-Model DBMSs were created to make your life easier, giving you the option of using one NoSQL product with powerful multi-purpose engines capable of handling complex domains. Could one DBMS handle all your needs including speed and scalability in the times of Big Data? Luca will walk you through the benefits and trade-offs of multi-model DBMSs and will show you how easy it is to setup one open source database to handle many different use cases, saving you time and money.
Presented at Data Day Texas - Austin (TX) - USA
Know different types of tips about Importance of dataware housing, Data Cleansing and Extracting etc . For more details visit: http://www.skylinecollege.com/business-analytics-course
Data warehouse implementation design for a Retail businessArsalan Qadri
The document contains an end to end data warehouse design - from SKU procurement to SKU Sale. Additionally, a BI dashboard has been created in Tableau, to mine the warehouse, with SKU as the grain. The data can be aggregated at levels of Supplier/Store/Location/Inventory/Sale Date/Time in Warehouse etc.
Data Warehousing is a data architecture that separates reporting and analytics needs from operational transaction systems. This presentation is an introduction into traditional data warehousing architectures and how to determine if your environment requires a data warehouse.
TekSlate is the leader in Tableau tutorials and other business intelligence tutorials emphasis on delivering complete knowledge through self-paced learning. Tableau Free Tutorials tech to create highly interactive dashboards using actions.
To Learn More Click On Below Link:
http://bit.ly/1zKKnPm
Implemented Data warehouse on “Retail Stores of five states of USA” by using 3 different data sources including structured and unstructured using SSIS, SSAS and Power BI.
Know different types of tips about Importance of dataware housing, Data Cleansing and Extracting etc . For more details visit: http://www.skylinecollege.com/business-analytics-course
Data warehouse implementation design for a Retail businessArsalan Qadri
The document contains an end to end data warehouse design - from SKU procurement to SKU Sale. Additionally, a BI dashboard has been created in Tableau, to mine the warehouse, with SKU as the grain. The data can be aggregated at levels of Supplier/Store/Location/Inventory/Sale Date/Time in Warehouse etc.
Data Warehousing is a data architecture that separates reporting and analytics needs from operational transaction systems. This presentation is an introduction into traditional data warehousing architectures and how to determine if your environment requires a data warehouse.
TekSlate is the leader in Tableau tutorials and other business intelligence tutorials emphasis on delivering complete knowledge through self-paced learning. Tableau Free Tutorials tech to create highly interactive dashboards using actions.
To Learn More Click On Below Link:
http://bit.ly/1zKKnPm
Implemented Data warehouse on “Retail Stores of five states of USA” by using 3 different data sources including structured and unstructured using SSIS, SSAS and Power BI.
Fundamentals of Database Systems Questions and AnswersOXUS 20
Fundamentals of Database Systems questions and answers with explanation for fresher's and experienced for interview, competitive examination and entrance test.
A 30 day plan to start ending your data struggle with SnowflakeSnowflake Computing
Organizations everywhere are struggling to load, integrate, analyze and collaborate with data. This is largely thanks to their antiquated data platform, designed in a time when few people had the desire or need to interact with the database. Snowflake, the data warehouse built for the cloud, can help.
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...Edureka!
This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial:
1. What Is The Need For BI?
2. What Is Data Warehousing?
3. Key Terminologies Related To Data Warehouse Architecture:
a. OLTP Vs OLAP
b. ETL
c. Data Mart
d. Metadata
4. Data Warehouse Architecture
5. Demo: Creating A Data Warehouse
Very basic Introduction to Big Data. Touches on what it is, characteristics, some examples of Big Data frameworks. Hadoop 2.0 example - Yarn, HDFS and Map-Reduce with Zookeeper.
Power BI & SAP - Integration Options and possible PifallsJJDE
Dein Unternehmen setzt als ERP/BI-System auf SAP? Und du suchst nach den besten Möglichkeiten, um alle SAP BW / HANA-Daten in Microsoft Power BI zu integrieren und das Beste aus beiden Welten zu nutzen? Dann ist diese Session für dich! Du erhältst einen Überblick über die verschiedenen Integrationsoptionen und -Überlegungen, die du berücksichtigen solltest.
English Version:
Your Company's ERP and/or BI-System is SAP? And you are looking for the best options to get all your SAP BW/HANA Data to Microsoft (Power) BI and leverage the best of both worlds? Then this session is for you! You will get an overview of the several integration options and considerations you should be aware. The session will be hold in german language but of course we can switch to English as needed.
The right architecture is key for any IT project. This is especially the case for big data projects, where there are no standard architectures which have proven their suitability over years. This session discusses the different Big Data Architectures which have evolved over time, including traditional Big Data Architecture, Streaming Analytics architecture as well as Lambda and Kappa architecture and presents the mapping of components from both Open Source as well as the Oracle stack onto these architectures.
The rise of NoSQL is characterized with confusion and ambiguity; very much like any fast-emerging organic movement in the absence of well-defined standards and adequate software solutions. Whether you are a developer or an architect, many questions come to mind when faced with the decision of where your data should be stored and how it should be managed. The following are some of these questions: What does the rise of all these NoSQL technologies mean to my enterprise? What is NoSQL to begin with? Does it mean "No SQL"? Could this be just another fad? Is it a good idea to bet the future of my enterprise on these new exotic technologies and simply abandon proven mature Relational DataBase Management Systems (RDBMS)? How scalable is scalable? Assuming that I am sold, how do I choose the one that fit my needs best? Is there a middle ground somewhere? What is this Polyglot Persistence I hear about? The answers to these questions and many more is the subject of this talk along with a survey of the most popular of NoSQL technologies. Be there or be square.
Fundamentals of Database Systems Questions and AnswersOXUS 20
Fundamentals of Database Systems questions and answers with explanation for fresher's and experienced for interview, competitive examination and entrance test.
A 30 day plan to start ending your data struggle with SnowflakeSnowflake Computing
Organizations everywhere are struggling to load, integrate, analyze and collaborate with data. This is largely thanks to their antiquated data platform, designed in a time when few people had the desire or need to interact with the database. Snowflake, the data warehouse built for the cloud, can help.
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...Edureka!
This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial:
1. What Is The Need For BI?
2. What Is Data Warehousing?
3. Key Terminologies Related To Data Warehouse Architecture:
a. OLTP Vs OLAP
b. ETL
c. Data Mart
d. Metadata
4. Data Warehouse Architecture
5. Demo: Creating A Data Warehouse
Very basic Introduction to Big Data. Touches on what it is, characteristics, some examples of Big Data frameworks. Hadoop 2.0 example - Yarn, HDFS and Map-Reduce with Zookeeper.
Power BI & SAP - Integration Options and possible PifallsJJDE
Dein Unternehmen setzt als ERP/BI-System auf SAP? Und du suchst nach den besten Möglichkeiten, um alle SAP BW / HANA-Daten in Microsoft Power BI zu integrieren und das Beste aus beiden Welten zu nutzen? Dann ist diese Session für dich! Du erhältst einen Überblick über die verschiedenen Integrationsoptionen und -Überlegungen, die du berücksichtigen solltest.
English Version:
Your Company's ERP and/or BI-System is SAP? And you are looking for the best options to get all your SAP BW/HANA Data to Microsoft (Power) BI and leverage the best of both worlds? Then this session is for you! You will get an overview of the several integration options and considerations you should be aware. The session will be hold in german language but of course we can switch to English as needed.
The right architecture is key for any IT project. This is especially the case for big data projects, where there are no standard architectures which have proven their suitability over years. This session discusses the different Big Data Architectures which have evolved over time, including traditional Big Data Architecture, Streaming Analytics architecture as well as Lambda and Kappa architecture and presents the mapping of components from both Open Source as well as the Oracle stack onto these architectures.
The rise of NoSQL is characterized with confusion and ambiguity; very much like any fast-emerging organic movement in the absence of well-defined standards and adequate software solutions. Whether you are a developer or an architect, many questions come to mind when faced with the decision of where your data should be stored and how it should be managed. The following are some of these questions: What does the rise of all these NoSQL technologies mean to my enterprise? What is NoSQL to begin with? Does it mean "No SQL"? Could this be just another fad? Is it a good idea to bet the future of my enterprise on these new exotic technologies and simply abandon proven mature Relational DataBase Management Systems (RDBMS)? How scalable is scalable? Assuming that I am sold, how do I choose the one that fit my needs best? Is there a middle ground somewhere? What is this Polyglot Persistence I hear about? The answers to these questions and many more is the subject of this talk along with a survey of the most popular of NoSQL technologies. Be there or be square.
Slides: Polyglot Persistence for the MongoDB, MySQL & PostgreSQL DBASeveralnines
Polyglot Persistence for the MongoDB, PostgreSQL & MySQL DBA
The introduction of DevOps in organisations has changed the development process, and perhaps introduced some challenges. Developers, in addition to their own preferred programming languages, also have their own preference for backend storage.The former is often referred to as polyglot languages and the latter as polyglot persistence.
Having multiple storage backends means your organization will become more agile on the development side and allows choice to the developers but it also imposes additional knowledge on the operations side. Extending your infrastructure from only MySQL, to deploying other storage backends like MongoDB and PostgreSQL, implies you have to also monitor, manage and scale them. As every storage backend excels at different use cases, this also means you have to reinvent the wheel for every one of them.
This webinar covers the four major operational challenges for MySQL, MongoDB & PostgreSQL:
Deployment
Management
Monitoring
Scaling
And how to deal with them
SPEAKER
Art van Scheppingen is a Senior Support Engineer at Severalnines. He’s a pragmatic MySQL and Database expert with over 15 years experience in web development. He previously worked at Spil Games as Head of Database Engineering, where he kept a broad vision upon the whole database environment: from MySQL to Couchbase, Vertica to Hadoop and from Sphinx Search to SOLR. He regularly presents his work and projects at various conferences (Percona Live, FOSDEM) and related meetups.
This webinar is based upon the experience Art had while writing our How to become a ClusterControl DBA blog series and implementing multiple storage backends to ClusterControl. To view all the blogs of the ‘Become a ClusterControl DBA’ series visit: http://severalnines.com/blog-categories/clustercontrol
Data storage is one of the most crucial parts of any applications, and we use many different tools and tricks to keep it in a good shape. We frequently use both old school relational systems with new approaches commonly known as NoSQL. We write sophisticated queries and use optimization techniques to give our end users the greatest possible experience.
So why is persistence very often skipped in the testing efforts? Is it really that complex and painful to setup? During this talk we will have a closer look at Arquillian Persistence Extension together with NoSQLUnit. These tools remove that burden and boilerplate to make you a happy and productive programmer again! Join this session and see for yourself that writing tests for your data storage logic is as easy as writing normal unit tests!
Polyglot Persistence - Two Great Tastes That Taste Great TogetherJohn Wood
The days of the relational database being a one-stop-shop for all of your persistence needs are over. Although NoSQL databases address some issues that can’t be addressed by relational databases, the opposite is true as well. The relational database offers an unparalleled feature set and rock solid stability. One cannot underestimate the importance of using the right tool for the job, and for some jobs, one tool is not enough. This talk focuses on the strength and weaknesses of both relational and NoSQL databases, the benefits and challenges of polyglot persistence, and examples of polyglot persistence in the wild.
These slides were presented at WindyCityDB 2010.
This is 30 minute GlueCon 2013 version of a much longer talk. See http://plainoldobjects.com/presentations/developing-polyglot-persistence-applications/ for other versions and the example code.
NoSQL databases such as Redis, MongoDB and Cassandra are emerging as a compelling choice for many applications. They can simplify the persistence of complex data models and offer significantly better scalability and performance. However, using a NoSQL database means giving up the benefits of the relational model such as SQL, constraints and ACID transactions. For some applications, the solution is polyglot persistence: using SQL and NoSQL databases together.
In this talk, you will learn about the benefits and drawbacks of polyglot persistence and how to design applications that use this approach. We will explore the architecture and implementation of an example application that uses MySQL as the system of record and Redis as a very high-performance database that handles queries from the front-end. You will learn about mechanisms for maintaining consistency across the various databases.
Graphs, Edges & Nodes - Untangling the Social WebJoël Perras
Many of the most popular web applications today deal with highly organized and structured data that represent entities, and the relationships between these entities. LinkedIn can tell you how many degrees of separation there are between yourself and the CEO of Samsung, Facebook can figure out people that you might already know, Digg can recommend article submissions that you might like, and LastFM suggests music based on your current listening habits.
We’ll take a look at the basic theory behind how some of these features can be implemented (no computer science degree required!), and then dig in to a few practical implementations using PHP & and a relational database, as well as with Redis. Lastly, we’ll take a quick look at the current landscape of graph-based datastores that simplify many of these operations.
Jenkins Pipeline is a game changing way to write automation jobs with Jenkins. Pipeline supports from simple one-step hello-world type jobs to the most complex parallel pipelines or Docker operations like creation or publication of images. Best of all, they support manual/automated intervention and also an extension mechanism to avoid the DRY effect on your build pipeline. Combining Jenkins Pipeline with Docker can seriously reduce friction in your DevOps efforts.
But Jenkins Pipeline is not the only new thing that are in Jenkins 2.0, there is also UX improvements better out-of-the-box experience and a new website.
Come to this session to learn what’s new in Jenkins 2.0 and how you can improve your Continuous Delivery Pipeline with Jenkins Pipeline as well as see what is coming after Jenkins 2.0.
As more businesses realised that data, in all forms and sizes, is critical to making the best possible decisions, we see the continued growth of systems that support massive volume of non-relational or unstructured forms of data. Nothing shows the picture more starkly than the Gartner Magic quadrant for operational database management systems, which assumes that, by 2017, all leading operational DBMSs will offer multiple data models, relational and NoSQL, in a single DBMS platform. Having a single data platform for managing both well-structured data and NoSQL data is beneficial to users; this approach reduces significantly integration, migration, development, maintenance, and operational issues. Therefore, a challenging research work is how to develop efficient consolidated single data management platform covering both relational data and NoSQL to reduce integration issues, simplify operations, and eliminate migration issues.
In this tutorial, we review the previous work on multi-model data management and provide the insights on the research challenges and directions for future work.
Papers and more materials on this tutorial can be found at: http://udbms.cs.helsinki.fi/?tutorials
Imagine that self-driving cars now exist and are becoming widespread around the world. To facilitate the transition, it's necessary to set up central service to monitor traffic conditions nationwide, deploy sensors throughout the interstate system that monitor traffic conditions including car speeds, pavement and weather conditions, as well as accidents, construction, and other sources of traffic tie ups.
MongoDB has been selected as the database for this application. In this webinar, we will walk through designing the application’s schema that will both support the high update and read volumes as well as the data aggregation and analytics queries.
Webinar: Working with Graph Data in MongoDBMongoDB
With the release of MongoDB 3.4, the number of applications that can take advantage of MongoDB has expanded. In this session we will look at using MongoDB for representing graphs and how graph relationships can be modeled in MongoDB.
We will also look at a new aggregation operation that we recently implemented for graph traversal and computing transitive closure. We will include an overview of the new operator and provide examples of how you can exploit this new feature in your MongoDB applications.
Data Virtualization Journey: How to Grow from Single Project and to Enterpris...Denodo
In this presentation, Intel presents their journey, starting small and growing Data Virtualization to an Enterprise IT enabling use cases such as samples management, cloud, and big data for sales and marketing.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/jiYOHw.
Why Data Virtualization? An Introduction by DenodoJusto Hidalgo
Data Virtualization means Real-time Data Access and Integration. But why do I need it? This presentation tries to answer it in a simple yet clear way.
By Alberto Pan, CTO of Denodo, and Justo Hidalgo, VP Product Management.
"We can all agree that streaming is super cool. And for a while now, the adoption conversation has been largely led with an all-in mentality. But that’s silly. The only concerns end users have are:
-The freshness of their data
-Latency they require to meet their SLAs from source to consumption
-All while maintaining data quality and governance.
Luckily, the industry has realized this and we have seen a shift of streaming capabilities surfacing as an in-database technology, via objects as trivial to analytics engineers as views - materialized that is. With this convergence of streaming capabilities and batch level accessibility, this is when ELT tools like dbt can join in and expand out the adoption story.
dbt is the T in ELT, Extract Load and Transform. In dbt, analytics engineers design models - SQL (and occasional python) statements that encapsulate business logic. At runtime, dbt will wrap that logic in a DDL statement and send it over to the data platform to execute.
In this session, we’ll discuss how we see streaming at dbt Labs. We will dive into how we are extending dbt to support low-latency scenarios and the recent additions we have made to make batch and streaming allies in a DAG rather than archenemies."
http://www.opitz-consulting.com/go/3-5-898
Smartphones haben unsere Welt im Schnellgang erobert. Die Tablets folgen nicht minder schnell nach. Was fasziniert uns so daran? Welche neuen Möglichkeiten bieten sich für das Business? Welchen Einfluss wird das allgegenwärtige HTML5 haben? Wie bekomme ich mobile Lösungen architektonisch optimal in meine SOA-Landschaft integriert, und welche Vorteile gewinne ich bei der Prozessautomatisierung? Diese Session liefert sowohl einen Überblick als auch Antworten für eine neue Klasse von Architekturfragen.
Die SOA-Experten Torsten Winterberg und Guido Schmutz hielten diesen Fachvortrag bei der DOAG Konferenz und Ausstellung am 20.11.2013 in Nürnberg.
--
Über uns:
Als führender Projektspezialist für ganzheitliche IT-Lösungen tragen wir zur Wertsteigerung der Organisationen unserer Kunden bei und bringen IT und Business in Einklang. Mit OPITZ CONSULTING als zuverlässigem Partner können sich unsere Kunden auf ihr Kerngeschäft konzentrieren und ihre Wettbewerbsvorteile nachhaltig absichern und ausbauen.
Über unsere IT-Beratung: http://www.opitz-consulting.com/go/3-8-10
Unser Leistungsangebot: http://www.opitz-consulting.com/go/3-8-874
Karriere bei OPITZ CONSULTING: http://www.opitz-consulting.com/go/3-8-5
http://www.opitz-consulting.com/go/3-5-898
Smartphones and tablets conquered our world. Which new opportunities are there for our businesses? Which influence has the omnipresent HTML5? How can I integrate mobile solutions in an optimal architectural way in my SOA landscapes and which kind of advantages do I gain for business process automation? This session delivers answers and puts current buzzwords like Big Data, Cloud, internet of things, HTML5 and mobile in the context of BPM and integration. Thereby we derive a reference architecture for Oracle SOA Suite, OSB, BPM Suite, Enterprise Gateway, Webcenter, ADF Mobile, etc., which makes all the buzzwords easily manageable in our daily IT work and prevents you from making mistakes others already did.
Torsten Winterberg und Guido Schmutz, both well-respected SOA Experts, presented this session at German Oracle User Communities’s Conference (DOAG Konferenz) at nov 20th 2013 in Nuremberg, Germany.
--
- - -
About us:
OPITZ CONSULTING is a leading project specialist for custom-build applications and individual business intelligence solutions in the German market. The company's ambition is to help organizations to be better than their competitors. To achieve this OPITZ CONSULTING analyses the individual competitive edge the customer has, optimizes business processes for process automation and IT-support, chooses and designs appropriate system architectures, develops and implements solutions and guarantees a 24/7 support and application maintenance. To ensure the necessary skill and qualification OPITZ CONSULTING has established a training center for customers and the internal staff.
Since 1990 over 600 customers have a long lasting and successful business relationship with OPITZ CONSULTING. Over 2/3 of the German stock index (DAX) companies rely on services from the 400+ OPITZ CONSULTING consultants. OPITZ CONSULTING maintains offices in Bad Homburg, Berlin, Essen, Gummersbach, Hamburg, Munich, Nuremberg and Kraków and Warsawa (Poland).
About us: http://www.opitz-consulting.com/en/about_us
Services: http://www.opitz-consulting.com/en/leistungsangebot
Career: http://www.opitz-consulting.com/en/career
Presented at Richmond SQL Server Users group, this presentation provides an introduction to Continuous Delivery principles, practices, tools and how to apply these to SQL Server Database. It also presents a case study and lessons learned from adopting these practices on a real project.
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...DATAVERSITY
Thirty years is a long time for a technology foundation to be as active as relational databases. Are their replacements here?
In this webinar, we look at this foundational technology for modern Data Management and show how it evolved to meet the workloads of today, as well as when other platforms make sense for enterprise data.
Polyglot persistence for enterprise cloud applicationsLars Lemos
Presentantion for the thesis of Master of Computer Applications.
Describes the problems faced by developing an enterprise applicaition taking into consideration the cap theorem and the resources provided by cloud computing.
Denodo Partner Connect: Business Value Demo with Denodo Demo LiteDenodo
Watch full webinar here: https://buff.ly/3OCQvGk
In this session, Denodo Sales Engineer, Yik Chuan Tan, will guide you through the art of delivering a compelling demo of the Denodo Platform with Denodo Demo Lite. Watch to uncover the significant functionalities that set Denodo apart and learn how to effectively win over potential customers.
In this session, we will cover:
Understanding the Denodo Platform & Tailoring Your Demo to Prospect Needs: By gaining a comprehensive understanding of the Denodo Platform, its architecture, and how it addresses data management challenges, you can customize your demo to align with the specific needs and pain points of your prospects, including:
- seamless data integration with real-time access
- data security and governance
- self-service data discovery
- advanced analytics and reporting
- performance optimization scalability and deployment
Watch this Denodo demo session and acquire the skills and knowledge necessary to captivate your prospects. Whether you're a seasoned technical professional or new to the field, this session will equip you with the skills to deliver compelling demos that lead to successful conversions.
Organizations generally take on of two approaches to multi-model databases : Polyglot persistence with multiple database engines or single data store that introduces the data model at a higher level of the architecture
View the companion webinar at: http://embt.co/1L8V6dI
Some claim that, in the age of Big Data, data modeling is less important or even not needed. However, with the increased complexity of the data landscape, it is actually more important to incorporate data modeling in order to understand the nature of the data and how they are interrelated. In order to do this effectively, the way that we do data modeling needs to adapt to this complex environment.
One of the key data modeling issues is how to foster collaboration between new groups, such as data scientists, and traditional data management groups. There are often different paradigms, and yet it is critical to have a common understanding of data and semantics between different parts of an organization. In this presentation, Len Silverston will discuss:
+ How Big Data has changed our landscape and affected data modeling
+ How to conduct data modeling in a more ‘agile’ way for Big Data environments
+ How we can collaborate effectively within an organization, even with differing perspectives
About the Presenter:
Len Silverston is a best-selling author, consultant, and a fun and top rated speaker in the field of data modeling, data governance, as well as human behavior in the data management industry, where he has pioneered new approaches to effectively tackle enterprise data management. He has helped many organizations world-wide to integrate their data, systems and even their people. He is well known for his work on "Universal Data Models", which are described in The Data Model Resource Book series (Volumes 1, 2, and 3).
Canadian Experts Discuss Modern Data Stacks and Cloud Computing for 5 Years o...Daniel Zivkovic
Two #ModernDataStack talks and one DevOps talk: https://youtu.be/4R--iLnjCmU
1. "From Data-driven Business to Business-driven Data: Hands-on #DataModelling exercise" by Jacob Frackson of Montreal Analytics
2. "Trends in the #DataEngineering Consulting Landscape" by Nadji Bessa of Infostrux Solutions
3. "Building Secure #Serverless Delivery Pipelines on #GCP" by Ugo Udokporo of Google Cloud Canada
We ran out of time for the 4th presenter, so the event will CONTINUE in March... stay tuned! Compliments of #ServerlessTO.
Modern Data Management for Federal ModernizationDenodo
Watch full webinar here: https://bit.ly/2QaVfE7
Faster, more agile data management is at the heart of government modernization. However, Traditional data delivery systems are limited in realizing a modernized and future-proof data architecture.
This webinar will address how data virtualization can modernize existing systems and enable new data strategies. Join this session to learn how government agencies can use data virtualization to:
- Enable governed, inter-agency data sharing
- Simplify data acquisition, search and tagging
- Streamline data delivery for transition to cloud, data science initiatives, and more
Interleaving, Evaluation to Self-learning Search @904LabsJohn T. Kane
Presented at Open Source Connections Haystack Relevance Conference on 904Labs' "Interleaving: from Evaluation to Self-Learning". 904Labs is the first to commercialize "Online Learning to Rank" as a state-of-art for technical Self-learning Search Ranking that automatically takes into account your customers human behaviors for personalized search results.
Similar to Polyglot Persistence vs Multi-Model Databases (20)
Why relationships are cool but "join" sucksLuca Garulli
Relational DBMS and Document Databases use the "JOIN" operation to connect records and documents. Is there a better way to connect things? This presentation illustrates how OrientDB manages relationships by using the same technique of Graph Databases for super fast traversal.
Switching from the Relational to the Graph modelLuca Garulli
One of the main resistences of RDBMS users to pass to a NoSQL product are related to the complexity of the model: Ok, NoSQL products are super for BigData and BigScale but what about the model?
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Launch Your Streaming Platforms in MinutesRoshan Dwivedi
The claim of launching a streaming platform in minutes might be a bit of an exaggeration, but there are services that can significantly streamline the process. Here's a breakdown:
Pros of Speedy Streaming Platform Launch Services:
No coding required: These services often use drag-and-drop interfaces or pre-built templates, eliminating the need for programming knowledge.
Faster setup: Compared to building from scratch, these platforms can get you up and running much quicker.
All-in-one solutions: Many services offer features like content management systems (CMS), video players, and monetization tools, reducing the need for multiple integrations.
Things to Consider:
Limited customization: These platforms may offer less flexibility in design and functionality compared to custom-built solutions.
Scalability: As your audience grows, you might need to upgrade to a more robust platform or encounter limitations with the "quick launch" option.
Features: Carefully evaluate which features are included and if they meet your specific needs (e.g., live streaming, subscription options).
Examples of Services for Launching Streaming Platforms:
Muvi [muvi com]
Uscreen [usencreen tv]
Alternatives to Consider:
Existing Streaming platforms: Platforms like YouTube or Twitch might be suitable for basic streaming needs, though monetization options might be limited.
Custom Development: While more time-consuming, custom development offers the most control and flexibility for your platform.
Overall, launching a streaming platform in minutes might not be entirely realistic, but these services can significantly speed up the process compared to building from scratch. Carefully consider your needs and budget when choosing the best option for you.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
3. Structured Data
Small Datasets
Few Relationships
Waterfall Approach
Scale Up
CIO
The World Has Changed
Unstructured Data
Large Volume
Connected Data
Agile Approach
Scale Out
Developers
Relational NoSQL
1970 2009
A NoSQL database provides a mechanism for storage and retrieval of
data that is modeled in means other than the tabular relations
used in relational databases. Motivations for this approach include:
simplicity of design, "horizontal" scaling, which is a problem for
relational databases, and finer control over availability
What s Next?
5. Polyglot Persistence
Polyglot Persistence is a fancy term to
describe that when storing data, it is best to use
multiple data storage technologies, chosen
based upon the way data is being used by
individual applications or components.
http://www.jamesserra.com/archive/2015/07/what-is-polyglot-persistence/
6.
7. Multi-Model
A multi-model database is designed to support
multiple data models against a single, integrated
backend.
Multi-model databases are intended to offer the
data modeling advantages of polyglot
persistence without its disadvantages. Complexity,
in particular, is reduced.
https://en.wikipedia.org/wiki/Multi-model_database
8. What s a Multi-Model DBMS?
GraphDocument
Object
Key/Value
Multi-Model represents the
intersection
of multiple models in just one
product
Full-Text
Spatial
12. OrientDB
• First Multi-Model DBMS with a Graph-Engine
• Open Source Apache2 license
• Data Models are built into the core engine
• The Graph Database engine allows O(1) performance on
traversing relationships, against O(LogN) of RDBMS and
any other Multi-Model DBMS built as layers
• Schema-less, Schema-full and Schema-mixed
• Use of Apache Lucene for Full-Text and Spatial
• Written in Java (runs on every platform)
• Zero-config HA
19. Polyglot Persistence in Action
DOCUMENTKEY/VALUE GRAPH RELATIONAL
User Sessions
Rapid Access for
reads and writes.
No need to be
durable.
Financial Data
Needs transactional
updates. It will
manage orders and
payments.
Recommendations
Rapidly traverse
links between
friends, product
purchases, and
ratings.
Product Catalog
Lots of reads,
infrequent writes.
Products make
natural aggregates.
Example: Hotel Booking Application
SEARCH
Search Engine
Full-Text Search.
Support for faceted
search and
suggestions.
21. Multi-Model in Action
Example: Hotel Booking Application
User Sessions
Rapid Access for
reads and writes.
No need to be
durable.
Financial Data
Needs transactional
updates. It will
manage orders and
payments.
Recommendations
Rapidly traverse
links between
friends, product
purchases, and
ratings.
Product Catalog
Lots of reads,
infrequent writes.
Products make
natural aggregates.
Search Engine
Full-Text Search.
Support for faceted
search and
suggestions
23. Deployment
Multi-ModelPolyglot
• Only 1 product to learn
• Only 1 server to configure and deploy
• Only 1 vendor in case of support
• 5 products to learn
• 5 servers to configure and deploy
• 5 vendors in case of support
24. Polyglot Deployment
• 5 PRODUCTS TO LEARN
No standard, all products are different. Even in the same category, they
have different APIs (ex. MongoDB and CouchDB). Every developer has to
learn multiple products or you should hire multiple developers with specific
skills for every product.
• 5 SERVERS TO CONFIGURE AND DEPLOY
Usually it’s a bad idea to put more databases on the same machine due to
the aggressive use of resources such as RAM and DISK.
• 5 VENDORS IN CASE OF SUPPORT
This means 5 contracts with 5 different vendors.
29. Domain Design
Multi-ModelPolyglot
• The entire domain is represented in
just one model in the same database
• All data is interconnected and easy
to access
• Easy to refactor
• Design of 5 different ways to reproduce
part of the data on each product
• Management of Application level
relationship between data in different
datasets represented in different way
• Hard to refactor
31. Polyglot: Sequence Diagram
APPLICATION
(2) Get Product Details
(3) Get Recommendation for
the current product
(5) Get orders to
check availability
(6) Check concurrent
user activity on the
same product
(7) Update current
user activity (in
background)
(4) Get basic information for each
recommended product
(1) Request Product Detail Page
32. Polyglot: Performance
APPLICATION
(4) Get orders to
check availability
(1) Request Product Detail Page
(5) Check concurrent
user activity on the
same product
= 10ms
= 50ms
= 200ms
= 150ms
= 20ms
= 10ms
Total Time = 530ms
(6) Update current
user activity (in
background)
(2) Get Product Details
(3) Get Recommendation for
the current product
(4) Get basic information for each
recommended product
= 100ms
33. Multi-Model: Sequence Diagram
APPLICATION
(1) Request Product Detail Page
(2) Get Product Details
(3) Get Recommendation for
the current product
(5) Get orders to check availability
(7) Update concurrent user activity
(in background)
(6) Check concurrent users activity
on the same product
(4) Get basic information for
each recommended product
34. Multi-Model: Performance
APPLICATION
(1) Request Product Detail Page = 10ms
Total Time = 300ms
APPLICATION
= 290ms
(2) Get Product Details
(3) Get Recommendation for
the current product
(5) Get orders to check availability
(7) Update concurrent user activity
(in background)
(6) Check concurrent users activity
on the same product
(4) Get basic information for
each recommended product
35. Caching to the Rescue
(2) Get Product Details
(3) Get Recommendation for
the current product
(4) Get basic information for each
recommended product
(1) Request Product Detail Page
(6) Check concurrent users
activity on the same product
= 200ms
(7) Update current
user activity (in background)
= 10ms
= 50ms
= 150ms
= 20ms
= 10ms
If products description don’t change
very often, they can be cached
Caching recommendation means
loosing the ability to recommend per
use, but only per products
(5) Get orders to check availability
= 100ms If products description don’t change
very often, they can be cached
36. Polyglot: Parallel Async Execution
(2) Get Product Details
(3) Get Recommendation for the current product
(5) Get orders to check
availability
(1) Request Product Detail Page
(6) Check concurrent users activity on the same product
= 200ms
(7) Update current user activity
= 10ms
= 50ms
= 150ms
= 20ms
= 10ms
= 310ms
APPLICATION
(4) Get basic information for each recommended product
= 100ms
37. Performance
But when the
domain is simple,
using specific products
could give you better
performance
With complex
domains, Multi-Model is
faster then Polyglot
38. Performance continued...
• With OrientDB, we have many stories about users that
switched from a pure Graph Database to OrientDB. In
all the cases, they had comparable or better
performance.
• From the other side, we don t have many stories about
users that switched from a Key-Value to OrientDB.
• Performance depends on the Multi-Model product.
• With Multi-Model it s very important having the models
built in the engine. If they are just layers, you ll have a lot
of compromises in term of flexibility and performance.
40. Features
Multi-ModelPolyglot
Even if Multi-Model are feature-rich
products, it’s possible to not find the
feature you need.
You can choose from 300 products,
giving you access to all the available
features.
43. Polyglot: Synchronization by ETL
DOCUMENT
GRAPH
RELATIONAL
In order to use the Recommendation engine, you
have to develop the ETL to pump data into the
Graph Database every hour/day, mixing data of
products and sales. The Search Engine, instead,
only needs data from the Product Catalog.
ETL
ETL
ETL
44. Polyglot: Synchronization by App
DOCUMENT
GRAPH
RELATIONAL
You can avoid ETL
is the application is
responsible to
populate all the
DBMS and keep
them in synch.
APPLICATION
45. Let s put everything
in
High Availability
(HA)
47. Redis in HA
Server A
Sentinel A
Server B
Sentinel B
Server C
Sentinel C
Suggested Configuration:
Deploy at least 3 Redis Server
+ Redis Sentinel on 3 separate Boxes
http://redis.io/topics/sentinel
48. Neo4j in HA
Suggested Configuration:
Deploy at least 3 Neo4j Servers
http://neo4j.com/docs/stable/ha-architecture.html
49. MongoDB in HA
Secondary 1
Suggested Configuration:
Deploy at least 3 MongoDB Servers
(1 Primary and 2 Secondary Servers)
Primary
Secondary 2
https://docs.mongodb.org/manual/core/replica-set-members/
50. ElasticSearch in HA
Suggested Configuration:
Deploy at least 2 ElasticSearch Servers
https://www.elastic.co/guide/en/elasticsearch/guide/current/_add_failover.html
51. MySQL in HA
Sorry, but the ways to put MySQL in HA are too many…
I found this configuration with 2 master servers that should be
the minimum for HA.
55. Multi-Model in HA
APPLICATION
OrientDB supports Multi-Master
replication with flexible sharding
Zero-config cluster deployment allows
to create a cluster of servers in a few
minutes
When a new server connects to the
cluster, the database is automatically
shared
All the clients are always notified
about new servers, so in case of a
crash, the client can automatically
switch to another available server with
no failure at application level
Servers = 3
58. Confidential
OrientDB At a Glance
70,000
Downloads per month
from 200+ countries
100+
Code contributors on
Github and 15,000+
commits
1,000s
Users from SMBs to
Fortune 10 Companies
17+
Years of
Product
Research
Global Coverage and 24x7 Support
59. Awards and Press Coverage
2015 Bossie Award Winner
OrientDB is an interesting hybrid in the NoSQL world,
combining features from a document database and a graph
database.
A new breed of database hopes to blend the best
of NoSQL and RDBMS
Multi-model databases may help tame the growing
complexity of enterprise data.
11 cutting-edge databases worth exploring now
OrientDB packages itself as a "second-generation graph
database." In other words, the nodes in the graphs are
documents waiting for arbitrary key-value pairs.
60. A Bright Future
Graph DBMS increased their popularity
by 500% within the last 2 years.
Document DBMS are the 3rd fastest
growing category.
Forrester estimates that over 25 percent of enterprises will
use graph databases by 2017.
Among the top 50, OrientDB is the technology with the
largest year-on-year growth (+22 positions).
61. Don t miss my presentation
Tomorrow, at GraphDay
10:00am:
Working Towards an
Unbreakable Graph Database
that Scales