The document discusses different approaches to data management and persistence in applications, including:
1) Storing objects directly in files or using a database management system (DBMS) to store data in tables while hiding physical storage details.
2) Design questions around persistence such as whether to use files, a relational or object DBMS, and how to structure the logical and physical layers.
3) Common techniques for mapping objects to relational databases like normalization, handling inheritance and associations.
4) Alternatives for designing data management classes like adding persistence methods to classes or using broker classes.
Introducing Multi Valued Vectors Fields in Apache LuceneSease
Since the introduction of native vector-based search in Apache Lucene happened, many features have been developed, but the support for multiple vectors in a dedicated KNN vector field remained to explore. Having the possibility of indexing (and searching) multiple values per field unlocks the possibility of working with long textual documents, splitting them in paragraphs and encoding each paragraph as a separate vector: scenario that is often encountered by many businesses. This talk explores the challenges, the technical design and the implementation activities happened during the work for this contribution to the Apache Lucene project. The audience is expected to get an understanding of how multi-valued fields can work in a vector-based search use-case and how this feature has been implemented.
This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
A simplified version of my presentation:
- PowerBI solution architecture
- Key steps to visualize data in PowerBI
- PowerBI Demo
- R in PowerBI
- Custom Visuals
- PowerBI Report Server
- Azure services and Power BI
Business Intelligence (BI) and Data Management Basics amorshed
A one-day training course on the Concepts of Data Management and Business Intelligence (BI) in the DX age
A Basic Review of BI and DM
How to Implement BI
A review of BI Tools and 2022 Gartner Quadrant Magic
Basics of Data warehouse (DWH)
An introductions to Power BI
Components of Power BI
Steps for BI Implementation
Data Culture
Intro to ETL and ELT
OLAP files and Architecture
Digital transformation or DX review
A glance at DMBOK2.0 framework
BI Challenges
Data Governance
Data Integration
Data Security and Privacy in DMBOK2.0
Data-Driven Organization
Data and BI Maturity Model
Traditional BI
Self-service BI
who is DMP
who is BI developer
what is Metadata
what is Master data
Data Quality
Data Literacy
Benefits of BI
BI features
How does BI Works?
Modern BI
Data Analytics
BI Architecture
Data Types
Data Lake
Data Mart
Data Silo
Data Visualization
Power BI Architecture and components
Below are the topics covered in this tutorial:
What is Data Visualization?
What is Tableau?
Why Tableau?
Tableau Job Trends
Companies using Tableau
Who should go for Tableau?
Tableau Architecture
Tableau Visualizations
Real time Use Case
Data Visualization Techniques in Power BIAngel Abundez
A progression from fundamental charts to more advanced ways to look at data. We end with Custom Visuals and R Visuals that extend this visualization platform.
Power BI has become a product with a ton of exciting features. This presentation will give an overview of some of them, including Power BI Desktop, Power BI service, what’s new, integration with other services, Power BI premium, and administration.
Introducing Multi Valued Vectors Fields in Apache LuceneSease
Since the introduction of native vector-based search in Apache Lucene happened, many features have been developed, but the support for multiple vectors in a dedicated KNN vector field remained to explore. Having the possibility of indexing (and searching) multiple values per field unlocks the possibility of working with long textual documents, splitting them in paragraphs and encoding each paragraph as a separate vector: scenario that is often encountered by many businesses. This talk explores the challenges, the technical design and the implementation activities happened during the work for this contribution to the Apache Lucene project. The audience is expected to get an understanding of how multi-valued fields can work in a vector-based search use-case and how this feature has been implemented.
This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
A simplified version of my presentation:
- PowerBI solution architecture
- Key steps to visualize data in PowerBI
- PowerBI Demo
- R in PowerBI
- Custom Visuals
- PowerBI Report Server
- Azure services and Power BI
Business Intelligence (BI) and Data Management Basics amorshed
A one-day training course on the Concepts of Data Management and Business Intelligence (BI) in the DX age
A Basic Review of BI and DM
How to Implement BI
A review of BI Tools and 2022 Gartner Quadrant Magic
Basics of Data warehouse (DWH)
An introductions to Power BI
Components of Power BI
Steps for BI Implementation
Data Culture
Intro to ETL and ELT
OLAP files and Architecture
Digital transformation or DX review
A glance at DMBOK2.0 framework
BI Challenges
Data Governance
Data Integration
Data Security and Privacy in DMBOK2.0
Data-Driven Organization
Data and BI Maturity Model
Traditional BI
Self-service BI
who is DMP
who is BI developer
what is Metadata
what is Master data
Data Quality
Data Literacy
Benefits of BI
BI features
How does BI Works?
Modern BI
Data Analytics
BI Architecture
Data Types
Data Lake
Data Mart
Data Silo
Data Visualization
Power BI Architecture and components
Below are the topics covered in this tutorial:
What is Data Visualization?
What is Tableau?
Why Tableau?
Tableau Job Trends
Companies using Tableau
Who should go for Tableau?
Tableau Architecture
Tableau Visualizations
Real time Use Case
Data Visualization Techniques in Power BIAngel Abundez
A progression from fundamental charts to more advanced ways to look at data. We end with Custom Visuals and R Visuals that extend this visualization platform.
Power BI has become a product with a ton of exciting features. This presentation will give an overview of some of them, including Power BI Desktop, Power BI service, what’s new, integration with other services, Power BI premium, and administration.
The data lake has become extremely popular, but there is still confusion on how it should be used. In this presentation I will cover common big data architectures that use the data lake, the characteristics and benefits of a data lake, and how it works in conjunction with a relational data warehouse. Then I’ll go into details on using Azure Data Lake Store Gen2 as your data lake, and various typical use cases of the data lake. As a bonus I’ll talk about how to organize a data lake and discuss the various products that can be used in a modern data warehouse.
Data visualizations make huge amounts of data more accessible and understandable. Data visualization, or "data viz," is becoming largely important as the amount of data generated is increasing and big data tools are helping to create meaning behind all of that data.
This SlideShare presentation takes you through more details around data visualization and includes examples of some great data visualization pieces.
Five Things to Consider About Data Mesh and Data GovernanceDATAVERSITY
Data mesh was among the most discussed and controversial enterprise data management topics of 2021. One of the reasons people struggle with data mesh concepts is we still have a lot of open questions that we are not thinking about:
Are you thinking beyond analytics? Are you thinking about all possible stakeholders? Are you thinking about how to be agile? Are you thinking about standardization and policies? Are you thinking about organizational structures and roles?
Join data.world VP of Product Tim Gasper and Principal Scientist Juan Sequeda for an honest, no-bs discussion about data mesh and its role in data governance.
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
Data Lakehouse, Data Mesh, and Data Fabric (r2)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I'll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I'll discuss Microsoft version of the data mesh.
Watch full webinar here: https://bit.ly/2N1Ndz9
How is a logical data fabric different from a physical data fabric? What are the advantages of one type of fabric over the other? Attend this session to firm up your understanding of a logical data fabric.
Quick iteration and reusability of metric calculations for powerful data exploration.
At Looker, we want to make it easier for data analysts to service the needs of the data-hungry users in their organizations. We believe too much of their time is spent responding to ad hoc data requests and not enough time is spent building, experimenting, and embellishing a robust model of the business. Worse yet, business users are starving for data, but are forced to make important decisions without access to data that could guide them in the right direction. Looker addresses both of these problems with a YAML-based modeling language called LookML.
This paper walks through a number of data modeling examples, demonstrating how to use LookML to generate, alter, and update reports—without the need to rewrite any SQL. With LookML, you build your business logic, defining your important metrics once and then reusing them throughout a model—allowing quick, rapid iteration of data exploration, while also ensuring the accuracy of the SQL that’s generated. Small updates are quick and can be made immediately available to business users to manipulate, iterate, and transform in any way they see fit.
The data lake has become extremely popular, but there is still confusion on how it should be used. In this presentation I will cover common big data architectures that use the data lake, the characteristics and benefits of a data lake, and how it works in conjunction with a relational data warehouse. Then I’ll go into details on using Azure Data Lake Store Gen2 as your data lake, and various typical use cases of the data lake. As a bonus I’ll talk about how to organize a data lake and discuss the various products that can be used in a modern data warehouse.
Data visualizations make huge amounts of data more accessible and understandable. Data visualization, or "data viz," is becoming largely important as the amount of data generated is increasing and big data tools are helping to create meaning behind all of that data.
This SlideShare presentation takes you through more details around data visualization and includes examples of some great data visualization pieces.
Five Things to Consider About Data Mesh and Data GovernanceDATAVERSITY
Data mesh was among the most discussed and controversial enterprise data management topics of 2021. One of the reasons people struggle with data mesh concepts is we still have a lot of open questions that we are not thinking about:
Are you thinking beyond analytics? Are you thinking about all possible stakeholders? Are you thinking about how to be agile? Are you thinking about standardization and policies? Are you thinking about organizational structures and roles?
Join data.world VP of Product Tim Gasper and Principal Scientist Juan Sequeda for an honest, no-bs discussion about data mesh and its role in data governance.
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
Data Lakehouse, Data Mesh, and Data Fabric (r2)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I'll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I'll discuss Microsoft version of the data mesh.
Watch full webinar here: https://bit.ly/2N1Ndz9
How is a logical data fabric different from a physical data fabric? What are the advantages of one type of fabric over the other? Attend this session to firm up your understanding of a logical data fabric.
Quick iteration and reusability of metric calculations for powerful data exploration.
At Looker, we want to make it easier for data analysts to service the needs of the data-hungry users in their organizations. We believe too much of their time is spent responding to ad hoc data requests and not enough time is spent building, experimenting, and embellishing a robust model of the business. Worse yet, business users are starving for data, but are forced to make important decisions without access to data that could guide them in the right direction. Looker addresses both of these problems with a YAML-based modeling language called LookML.
This paper walks through a number of data modeling examples, demonstrating how to use LookML to generate, alter, and update reports—without the need to rewrite any SQL. With LookML, you build your business logic, defining your important metrics once and then reusing them throughout a model—allowing quick, rapid iteration of data exploration, while also ensuring the accuracy of the SQL that’s generated. Small updates are quick and can be made immediately available to business users to manipulate, iterate, and transform in any way they see fit.
Object-Relational Database Systems(ORDBMSs) can successfully deal with very large data volumes with great complexity. At present the vendors of all the major DBMS products have supported object-relational database management systems, but still its industrial adoption rate is relatively low.
Database management system full theory portion is covered. It's helpful to students who are in any management courses.all the best to all of you, this ppt might be helpful for you.Database management system full theory portion is covered. It's helpful to students who are in any management courses.all the best to all of you, this ppt might be helpful for you.Database management system full theory portion is covered. It's helpful to students who are in any management courses.all the best to all of you, this ppt might be helpful for you.Database management system full theory portion is covered. It's helpful to students who are in any management courses.all the best to all of you, this ppt might be helpful for you.
Database Systems
DBMS
Database System Environment
Traditional File Systems
Advantages of DBMS over File Systems
Disadvantages of DBMS
DBMS
Describing and Storing data in DBMS
Three Schema Architecture
Data Independence
Queries
Transactions
Structure of DBMS
Users of DBMS
Steps in database Design Process
ER Concepts and Notations
Class Hierarchies
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Examples of transient objects include instances of boundary and control classes and the objects used in applications like on-screen calculators. (Note for computer science students, the objects in a calculator may include things like stacks and registers, not just digits or floating point numbers.) Persistent objects include the books, borrowers and loans in a library system. A loan of a book to a borrower may be created on one occasion on one machine, and is accessed from another machine on another occasion, for example to send out overdue book reminders.
Ask what kind of design trade-offs might have to be made with these different kinds of file record structures. Fixed length (padded) – easy to process, but wastes storage Variable length (delimited) – more difficult to process (looking for delimiters), but saves storage space Header and detail – allows for structure in data, may need line type and line no. Tagged data (XML) – self-describing, but storage overhead for tags.
![Content ,[object Object],[object Object],[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)