The document discusses using the REA (Resources, Events, Agents) ontology to describe coordination services that connect users to real-world services. It proposes a generic language based on REA to represent the pre-conditions, effects, and semantics of web services and the real services they coordinate. The REA ontology models how services are exchanged between agents in return for money, produced and consumed in conversion processes, and how coordination objects like reservations and purchase orders facilitate exchanges. The goal is for this language to allow users to discover, compose, and prevent conflicts when combining multiple services to meet their needs.
The Business Behavior Model (BBM) captures how agents make decisions based on their motives and available economic and non-economic resources. It models this interaction at three levels - strategic, tactical, and operational. At the strategic level, the BBM represents agents' goals and how their decisions and resource allocations help achieve these goals. At the tactical level, specific decisions and their relationships to economic resources and properties are modeled. The operational level then represents the concrete actions and tasks. The BBM provides a way to understand and represent the link between organizational strategy and operations through the lens of agent behaviors and resource management.
1. Maintaining and evolving data warehouses is complex and time-consuming due to changing data sources and information needs over time. Anchor modeling is proposed as a technique that allows for non-destructive extensibility to flexibly manage changes.
2. With anchor modeling, changes only require extensions, not modifications, ensuring existing data warehouse applications are unaffected by model evolution.
3. The key concepts in anchor modeling are anchors, knots, attributes, and ties, which allow for a high degree of normalization and reuse while supporting the storage of historical data in the data warehouse.
The i* modeling technique focuses on an early-phase of requirements
engineering aiming at understanding how a system would meet organizational
goals, how it would fit within the organizational context, why would it be
needed and why should it be preferred among other possible alternatives.
Analysts are able to understand early the organizational context that bridges
system requirements to organizational goals. However, it is not clear how
uncertainty, potential threats and opportunities are taken into account both
when developing a strategic dependency model and a strategic rationale model,
to facilitate a continuous risk management. This paper proposes a set of
guidelines for refining i* models based on risk.
Practice research aims to generate knowledge that is useful for both local practices and general practices. It combines three types of pragmatism: functional pragmatism by contributing solutions to local and general practices; referential pragmatism by developing action-oriented theories; and methodological pragmatism by participating in organizational change. Practice research is conducted through collaborative inquiry within a local practice to empirically study issues and test solutions, with the goal of improving both the local practice and developing generally applicable knowledge.
1. Anchor modeling is a technique for maintaining and evolving data warehouses that offers non-destructive extensibility mechanisms. This allows changes to be implemented through extensions rather than modifications.
2. The key concepts in anchor modeling are anchors, knots, attributes, and ties. Anchors represent entities, knots represent shared properties, attributes capture properties of anchors, and ties associate anchors.
3. A benefit of anchor modeling is that changes only require extensions, not modifications, allowing existing applications to remain unaffected by changes to the data warehouse model. This improves flexibility and longevity of the data warehouse.
The document discusses enterprise modeling for analyzing the value of services. It introduces the REA ontology for modeling resource exchanges and conversions. The REA conceptual model represents economic events that affect resources. Services can be modeled as resources that are offered from one agent to another. A conceptual service model represents services as abstract resources governed by policies that encapsulate other resources used in their production. Marketing-oriented service design focuses on fulfilling basic human needs, wants, and demands. An example care taking scenario is presented to demonstrate applying these concepts.
The document discusses the four categories of resources or factors of production that economists use: land, labor, capital, and entrepreneurship. It defines each category and provides examples. Land includes all natural resources. Labor refers to human effort. Capital consists of manufactured goods that can be used for further production, such as machinery. Entrepreneurship is the special talent of developing new ideas and taking risks to start new businesses. The document also notes that resources are paid for through rent, wages, interest, and profit.
The document discusses using the REA (Resources, Events, Agents) ontology to describe coordination services that connect users to real-world services. It proposes a generic language based on REA to represent the pre-conditions, effects, and semantics of web services and the real services they coordinate. The REA ontology models how services are exchanged between agents in return for money, produced and consumed in conversion processes, and how coordination objects like reservations and purchase orders facilitate exchanges. The goal is for this language to allow users to discover, compose, and prevent conflicts when combining multiple services to meet their needs.
The Business Behavior Model (BBM) captures how agents make decisions based on their motives and available economic and non-economic resources. It models this interaction at three levels - strategic, tactical, and operational. At the strategic level, the BBM represents agents' goals and how their decisions and resource allocations help achieve these goals. At the tactical level, specific decisions and their relationships to economic resources and properties are modeled. The operational level then represents the concrete actions and tasks. The BBM provides a way to understand and represent the link between organizational strategy and operations through the lens of agent behaviors and resource management.
1. Maintaining and evolving data warehouses is complex and time-consuming due to changing data sources and information needs over time. Anchor modeling is proposed as a technique that allows for non-destructive extensibility to flexibly manage changes.
2. With anchor modeling, changes only require extensions, not modifications, ensuring existing data warehouse applications are unaffected by model evolution.
3. The key concepts in anchor modeling are anchors, knots, attributes, and ties, which allow for a high degree of normalization and reuse while supporting the storage of historical data in the data warehouse.
The i* modeling technique focuses on an early-phase of requirements
engineering aiming at understanding how a system would meet organizational
goals, how it would fit within the organizational context, why would it be
needed and why should it be preferred among other possible alternatives.
Analysts are able to understand early the organizational context that bridges
system requirements to organizational goals. However, it is not clear how
uncertainty, potential threats and opportunities are taken into account both
when developing a strategic dependency model and a strategic rationale model,
to facilitate a continuous risk management. This paper proposes a set of
guidelines for refining i* models based on risk.
Practice research aims to generate knowledge that is useful for both local practices and general practices. It combines three types of pragmatism: functional pragmatism by contributing solutions to local and general practices; referential pragmatism by developing action-oriented theories; and methodological pragmatism by participating in organizational change. Practice research is conducted through collaborative inquiry within a local practice to empirically study issues and test solutions, with the goal of improving both the local practice and developing generally applicable knowledge.
1. Anchor modeling is a technique for maintaining and evolving data warehouses that offers non-destructive extensibility mechanisms. This allows changes to be implemented through extensions rather than modifications.
2. The key concepts in anchor modeling are anchors, knots, attributes, and ties. Anchors represent entities, knots represent shared properties, attributes capture properties of anchors, and ties associate anchors.
3. A benefit of anchor modeling is that changes only require extensions, not modifications, allowing existing applications to remain unaffected by changes to the data warehouse model. This improves flexibility and longevity of the data warehouse.
The document discusses enterprise modeling for analyzing the value of services. It introduces the REA ontology for modeling resource exchanges and conversions. The REA conceptual model represents economic events that affect resources. Services can be modeled as resources that are offered from one agent to another. A conceptual service model represents services as abstract resources governed by policies that encapsulate other resources used in their production. Marketing-oriented service design focuses on fulfilling basic human needs, wants, and demands. An example care taking scenario is presented to demonstrate applying these concepts.
The document discusses the four categories of resources or factors of production that economists use: land, labor, capital, and entrepreneurship. It defines each category and provides examples. Land includes all natural resources. Labor refers to human effort. Capital consists of manufactured goods that can be used for further production, such as machinery. Entrepreneurship is the special talent of developing new ideas and taking risks to start new businesses. The document also notes that resources are paid for through rent, wages, interest, and profit.
This document describes AnchorModeling, an agile modeling technique that uses the sixth normal form for structurally and temporally evolving data. The key aspects of AnchorModeling are that it allows for the evolution of schemas over time while preserving prior versions, supports historization of attributes and ties, and enables high performance querying of temporal data through views and functions. Data loading into an AnchorModeling schema can be automated through generated scripts and templates.
The document discusses new features in SQL Server 2008 that improve data storage, analytics, performance, scalability, high availability, security, and manageability. Key highlights include:
- Storing and querying multiple data types like relational, documents, XML, and spatial data more efficiently
- Enhancements for analytics, reporting, and mixed queries using features like column sets and sparse columns
- Increased scalability through features such as resource governor, memory management improvements, and query optimization
- High availability options like database mirroring, failover clustering, and replication
- Security enhancements including encryption, auditing, and reduced attack surfaces
- Simplified administration using tools such as SQL Server Management
SQLFire is a memory-optimized distributed SQL database from VMware. SQLFire is built for applications that need higher speed and lower latency than traditional databases can offer, but also require strong support for querying and transactions.
This webinar introduces the basics of SQLFire, including a discussion of why traditional databases are not scalable enough to deal with the demands of modern applications. I cover some of the extensions SQLFire makes to the SQL standard in order to be a truly horizontally-scalable SQL database.
The demo presented with the webinar shows how SQLFire can transparently scale to processes requests faster. In the demo a number of inserts are made, but not before a complex validation processes is done on the data being inserted. As a result the inserts are very slow. With SQLFire though you can simply add or remove nodes at any time, so if you anticipate a period where you need more processing power you can add a node and process inserts faster. SQLFire is designed to be horizontally scalable in all features, so you can scale not only inserts but also queries, transactions, etc.
Full source code for the demo is available (see the slides for details).
This document discusses data binding and visualization techniques for D3.js including binding data to DOM elements, using a model-view pattern, and rendering collections. It provides an example of tracking interaction state by storing it in models and views and triggering events on state changes. The document promotes an approach where interactions are modeled as objects that can get and set state and register named interactions. It notes benefits like undo/redo support, a uniform representation, and persisting interaction state across sessions.
U-SQL is a language for big data processing that unifies SQL and C#/custom code. It allows for processing of both structured and unstructured data at scale. Some key benefits of U-SQL include its ability to natively support both declarative queries and imperative extensions, scale to large data volumes efficiently, and query data in place across different data sources. U-SQL scripts can be used for tasks like complex analytics, machine learning, and ETL workflows on big data.
The document discusses how the Entity Framework (EF) Code First model works. It describes how to define simple entities connected by IDs, add virtual properties for lazy loading, and preserve naming conventions. It also covers creating a DbContext, repositories, and using it similarly to a general EF model. By default, the database server is SQL Express and the database name can be changed via the connection string. Database initializers are used to initialize the database if it does not exist. Data annotations can configure the database structure.
This document provides an overview of Apache Cassandra including:
- What Cassandra is and how it differs from an RDBMS by not supporting joins, having an optional schema, and being transactionless.
- Cassandra's data model using keyspaces, column families, and static vs dynamic column families.
- How to integrate Cassandra with Java applications using the Hector client and ColumnFamilyTemplate for querying, updating, and deleting data.
- Additional topics covered include the CAP theorem, data storage and compaction, and using CQL via JDBC.
Building nTier Applications with Entity Framework Services (Part 1)David McCarter
Learn how to build real world nTier applications with the new Entity Framework and related services. With this new technology built into .NET, you can easily wrap an object model around your database and have all the data access automatically generated or use your own stored procedures and views. The session will demonstrate how to create and consume these new technologies from the ground up and focus on database modeling including views and stored procedures along with coding against the model via LINQ. Dynamic data website will also be demonstrated.
The document provides an overview of the SQL programming language. It describes SQL as a language used to manage and retrieve data from relational databases. It then covers SQL fundamentals including basic SQL commands, data types, operators, and expressions. Examples are provided throughout to illustrate concepts.
This document provides an overview of the SQL programming language. It defines SQL as a language used to manage and retrieve data from relational databases. It describes the basic SQL commands like SELECT, INSERT, UPDATE, DELETE, and explains the different data types that can be used in SQL like numeric, character, and date/time. It also gives examples of basic SQL statements and clauses.
This document discusses NoSQL databases and frameworks for using them with Java applications. It summarizes the advantages of NoSQL databases, different types including key-value, column-oriented, document and graph databases. It also discusses frameworks like NoSQL Endgame that aim to provide a common API for working with multiple NoSQL databases from Java code. However, it notes that fully supporting all NoSQL databases and scenarios is still a challenge for such frameworks.
The document provides an overview of Entity Framework and Code First approach. It discusses the key features of Entity Framework including object-relational mapping, support for various databases, and using LINQ queries. It also covers the advantages of Entity Framework like productivity, maintainability and performance. Furthermore, it explains the different domain modeling approaches in Entity Framework - Model First, Database First and Code First along with code examples.
The document provides an agenda and overview for a presentation on data access layer patterns and options. It discusses considerations for keeping data entities consistent or managing differences between objects and schemas. It also covers common patterns for each approach, including row and table data gateways, active record, domain models, data mappers, repositories, and unit of work. The presentation will assess data access technologies and discuss additional challenges like domain model responsibilities. Attendees can contact the presenter with any other questions.
Data Modeling, Normalization, and De-Normalization | PostgresOpen 2019 | Dimi...Citus Data
As a developer using PostgreSQL one of the most important tasks you have to deal with is modeling the database schema for your application. In order to achieve a solid design, it’s important to understand how the schema is then going to be used as well as the trade-offs it involves.
As Fred Brooks said: “Show me your flowcharts and conceal your tables, and I shall continue to be mystified. Show me your tables, and I won’t usually need your flowcharts; they’ll be obvious.”
In this talk we're going to see practical normalisation examples and their benefits, and also review some anti-patterns and their typical PostgreSQL solutions, including Denormalization techniques thanks to advanced Data Types.
This document provides an introduction and overview of Cassandra and NoSQL databases. It discusses the challenges faced by modern web applications that led to the development of NoSQL databases. It then describes Cassandra's data model, API, consistency model, and architecture including write path, read path, compactions, and more. Key features of Cassandra like tunable consistency levels and high availability are also highlighted.
Building nTier Applications with Entity Framework Services (Part 1)David McCarter
Learn how to build real world nTier applications with the new Entity Framework and related services. With this new technology built into .NET, you can easily wrap an object model around your database and have all the data access automatically generated or use your own stored procedures and views. The session will demonstrate how to create and consume these new technologies from the ground up and focus on database modeling including views and stored procedures along with coding against the model via LINQ. Dynamic data website will also be demonstrated. Lots of code! Make sure to attend Part 2.
U-SQL - Azure Data Lake Analytics for DevelopersMichael Rys
This document introduces U-SQL, a language for big data analytics on Azure Data Lake Analytics. U-SQL unifies SQL with imperative coding, allowing users to process both structured and unstructured data at scale. It provides benefits of both declarative SQL and custom code through an expression-based programming model. U-SQL queries can span multiple data sources and users can extend its capabilities through C# user-defined functions, aggregates, and custom extractors/outputters. The document demonstrates core U-SQL concepts like queries, joins, window functions, and the metadata model, highlighting how U-SQL brings together SQL and custom code for scalable big data analytics.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
This document describes AnchorModeling, an agile modeling technique that uses the sixth normal form for structurally and temporally evolving data. The key aspects of AnchorModeling are that it allows for the evolution of schemas over time while preserving prior versions, supports historization of attributes and ties, and enables high performance querying of temporal data through views and functions. Data loading into an AnchorModeling schema can be automated through generated scripts and templates.
The document discusses new features in SQL Server 2008 that improve data storage, analytics, performance, scalability, high availability, security, and manageability. Key highlights include:
- Storing and querying multiple data types like relational, documents, XML, and spatial data more efficiently
- Enhancements for analytics, reporting, and mixed queries using features like column sets and sparse columns
- Increased scalability through features such as resource governor, memory management improvements, and query optimization
- High availability options like database mirroring, failover clustering, and replication
- Security enhancements including encryption, auditing, and reduced attack surfaces
- Simplified administration using tools such as SQL Server Management
SQLFire is a memory-optimized distributed SQL database from VMware. SQLFire is built for applications that need higher speed and lower latency than traditional databases can offer, but also require strong support for querying and transactions.
This webinar introduces the basics of SQLFire, including a discussion of why traditional databases are not scalable enough to deal with the demands of modern applications. I cover some of the extensions SQLFire makes to the SQL standard in order to be a truly horizontally-scalable SQL database.
The demo presented with the webinar shows how SQLFire can transparently scale to processes requests faster. In the demo a number of inserts are made, but not before a complex validation processes is done on the data being inserted. As a result the inserts are very slow. With SQLFire though you can simply add or remove nodes at any time, so if you anticipate a period where you need more processing power you can add a node and process inserts faster. SQLFire is designed to be horizontally scalable in all features, so you can scale not only inserts but also queries, transactions, etc.
Full source code for the demo is available (see the slides for details).
This document discusses data binding and visualization techniques for D3.js including binding data to DOM elements, using a model-view pattern, and rendering collections. It provides an example of tracking interaction state by storing it in models and views and triggering events on state changes. The document promotes an approach where interactions are modeled as objects that can get and set state and register named interactions. It notes benefits like undo/redo support, a uniform representation, and persisting interaction state across sessions.
U-SQL is a language for big data processing that unifies SQL and C#/custom code. It allows for processing of both structured and unstructured data at scale. Some key benefits of U-SQL include its ability to natively support both declarative queries and imperative extensions, scale to large data volumes efficiently, and query data in place across different data sources. U-SQL scripts can be used for tasks like complex analytics, machine learning, and ETL workflows on big data.
The document discusses how the Entity Framework (EF) Code First model works. It describes how to define simple entities connected by IDs, add virtual properties for lazy loading, and preserve naming conventions. It also covers creating a DbContext, repositories, and using it similarly to a general EF model. By default, the database server is SQL Express and the database name can be changed via the connection string. Database initializers are used to initialize the database if it does not exist. Data annotations can configure the database structure.
This document provides an overview of Apache Cassandra including:
- What Cassandra is and how it differs from an RDBMS by not supporting joins, having an optional schema, and being transactionless.
- Cassandra's data model using keyspaces, column families, and static vs dynamic column families.
- How to integrate Cassandra with Java applications using the Hector client and ColumnFamilyTemplate for querying, updating, and deleting data.
- Additional topics covered include the CAP theorem, data storage and compaction, and using CQL via JDBC.
Building nTier Applications with Entity Framework Services (Part 1)David McCarter
Learn how to build real world nTier applications with the new Entity Framework and related services. With this new technology built into .NET, you can easily wrap an object model around your database and have all the data access automatically generated or use your own stored procedures and views. The session will demonstrate how to create and consume these new technologies from the ground up and focus on database modeling including views and stored procedures along with coding against the model via LINQ. Dynamic data website will also be demonstrated.
The document provides an overview of the SQL programming language. It describes SQL as a language used to manage and retrieve data from relational databases. It then covers SQL fundamentals including basic SQL commands, data types, operators, and expressions. Examples are provided throughout to illustrate concepts.
This document provides an overview of the SQL programming language. It defines SQL as a language used to manage and retrieve data from relational databases. It describes the basic SQL commands like SELECT, INSERT, UPDATE, DELETE, and explains the different data types that can be used in SQL like numeric, character, and date/time. It also gives examples of basic SQL statements and clauses.
This document discusses NoSQL databases and frameworks for using them with Java applications. It summarizes the advantages of NoSQL databases, different types including key-value, column-oriented, document and graph databases. It also discusses frameworks like NoSQL Endgame that aim to provide a common API for working with multiple NoSQL databases from Java code. However, it notes that fully supporting all NoSQL databases and scenarios is still a challenge for such frameworks.
The document provides an overview of Entity Framework and Code First approach. It discusses the key features of Entity Framework including object-relational mapping, support for various databases, and using LINQ queries. It also covers the advantages of Entity Framework like productivity, maintainability and performance. Furthermore, it explains the different domain modeling approaches in Entity Framework - Model First, Database First and Code First along with code examples.
The document provides an agenda and overview for a presentation on data access layer patterns and options. It discusses considerations for keeping data entities consistent or managing differences between objects and schemas. It also covers common patterns for each approach, including row and table data gateways, active record, domain models, data mappers, repositories, and unit of work. The presentation will assess data access technologies and discuss additional challenges like domain model responsibilities. Attendees can contact the presenter with any other questions.
Data Modeling, Normalization, and De-Normalization | PostgresOpen 2019 | Dimi...Citus Data
As a developer using PostgreSQL one of the most important tasks you have to deal with is modeling the database schema for your application. In order to achieve a solid design, it’s important to understand how the schema is then going to be used as well as the trade-offs it involves.
As Fred Brooks said: “Show me your flowcharts and conceal your tables, and I shall continue to be mystified. Show me your tables, and I won’t usually need your flowcharts; they’ll be obvious.”
In this talk we're going to see practical normalisation examples and their benefits, and also review some anti-patterns and their typical PostgreSQL solutions, including Denormalization techniques thanks to advanced Data Types.
This document provides an introduction and overview of Cassandra and NoSQL databases. It discusses the challenges faced by modern web applications that led to the development of NoSQL databases. It then describes Cassandra's data model, API, consistency model, and architecture including write path, read path, compactions, and more. Key features of Cassandra like tunable consistency levels and high availability are also highlighted.
Building nTier Applications with Entity Framework Services (Part 1)David McCarter
Learn how to build real world nTier applications with the new Entity Framework and related services. With this new technology built into .NET, you can easily wrap an object model around your database and have all the data access automatically generated or use your own stored procedures and views. The session will demonstrate how to create and consume these new technologies from the ground up and focus on database modeling including views and stored procedures along with coding against the model via LINQ. Dynamic data website will also be demonstrated. Lots of code! Make sure to attend Part 2.
U-SQL - Azure Data Lake Analytics for DevelopersMichael Rys
This document introduces U-SQL, a language for big data analytics on Azure Data Lake Analytics. U-SQL unifies SQL with imperative coding, allowing users to process both structured and unstructured data at scale. It provides benefits of both declarative SQL and custom code through an expression-based programming model. U-SQL queries can span multiple data sources and users can extend its capabilities through C# user-defined functions, aggregates, and custom extractors/outputters. The document demonstrates core U-SQL concepts like queries, joins, window functions, and the metadata model, highlighting how U-SQL brings together SQL and custom code for scalable big data analytics.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Trusted Execution Environment for Decentralized Process MiningLucaBarbaro3
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...alexjohnson7307
Predictive maintenance is a proactive approach that anticipates equipment failures before they happen. At the forefront of this innovative strategy is Artificial Intelligence (AI), which brings unprecedented precision and efficiency. AI in predictive maintenance is transforming industries by reducing downtime, minimizing costs, and enhancing productivity.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
4. Entity
Relationship
Modeling
Sixth
Normal
Form
Temporal
Databases
5. Customer Gender
Store CustomerClass
Purchase HouseholdOwner
Item VisitingFrequencyInterval
PriceList
Inventory
Customer_Address
Customer_Household
CustomerDateOfBirth Card_Customer
CustomerNumber
CustomerName Attributes and ties
CustomerGender come in four flavors,
historized or static
combined with knotted
6. select top 5 * from CU_Customer select top 5 * from GEN_Gender
CU_ID GEN_ID GEN_Gender
1 1 Male
2 2 Female
3
4
5
select top 5 * from CUDOB_CustomerDateOfBirth select top 5 * from CUHH_Customer_Household
CU_ID CUDOB_CustomerDateOfBirth CU_ID HH_ID HOW_ID CUHH_FromDate
1 1905-03-02 1 1 1 2009-02-13
2 1905-07-02 1 895 0 2009-09-21
3 1908-09-14 2 2 1 2006-10-17
4 1910-02-03 3 3 1 2002-08-20
5 1912-04-01 4 4 1 1993-08-29
7. 1 2 3
4 5
All previous versions of the
schema are present and
were never modified,
allowing extensions to be
made ”online”.
8. Joins all attributes and finds the
attribute row with the latest
FromDate earlier or on the given
timepoint if historized
Joins all attributes and finds
the attribute row with the
latest FromDate if historized
9. YearOfBirth Customers
1950 20615
1951 19282
1952 20003
1953 19782
1954 19249
The query execution plan shows
that only two tables are touched
(the anchor and the selected
attribute) despite of the fact that
several others are joined into the
view we are using.
10. The query optimizer will remove table T from the Support
execution plan of a query if the following two conditions Microsoft SQL Server
are fulfilled: Oracle
IBM DB2
i. no column from T is explicitly selected PostgreSQL
ii. the number of rows in the returned data set is not MariaDB (fork of MySQL)
affected by the join with T Teradata (partial)
11. The scripts for setting up
the database, including all
views and functions, can be
automatically generated
from a compact XML
description.
Pseudo loading code given ”wide” source data:
o Check if there already is an associated surrogate key for
each natural key
o For unknown individuals
o Create and associate surrogate keys
o Directly insert data into all relevant tables
(most tables including the anchor)
Data loading templates o For known individuals
can be made in which o If this is a delta file, directly insert data into all
only the names of the relevant tables
o If this is not a delta file, check if the value in
tables and the join with
the source differs from the latest value in the
the natural key have to destination and insert if the data is new
be changed. (few tables excluding the anchor)
12. Ease of Modeling Simplified Maintenance
Simple concepts and notation Ease of temporal querying
Historization by design Absence of null values
Iterative and incremental development Reusability and automation
Reduced translation logic Asynchronous arrival of data
High Performance
High run-time performance
Efficient storage
Parallelized physical media access
www.anchormodeling.com