The document discusses database management systems (DBMS) and the relational data model. It defines a database and DBMS, describes the purpose of a DBMS in reducing data redundancy and inconsistencies. It also explains the three levels of database abstraction as internal, conceptual, and external levels and the concept of data independence. The relational and other data models like network and hierarchical are described along with their terminology. The document compares the different data models based on usability, implementability and performance.
Course Title: Database Programming with SQL
Course Code: DEE 431
TOPICS COVER:
Database Terminologies
Drawbacks of Traditional System
Data processing Modes
Application of DBMS
Types of Database
Histroy of Database
Characteristics of Database
Advantages and Disadvantages of Database
Types of database architecture: 1 Tier, 2 Tier, 3 Tier
Course Title: Database Programming with SQL
Course Code: DEE 431
TOPICS COVER:
Database Terminologies
Drawbacks of Traditional System
Data processing Modes
Application of DBMS
Types of Database
Histroy of Database
Characteristics of Database
Advantages and Disadvantages of Database
Types of database architecture: 1 Tier, 2 Tier, 3 Tier
Data:
– Raw facts; building blocks of information
– Unprocessed information
Information:
– Data processed to reveal meaning
• Accurate, relevant, and timely information is key
to good decision making.
Data
Data is a collection of facts, such as numbers, words, measurements, observations or even just descriptions of things.
Data can be qualitative or quantitative.
Information
Information is data that has been processed in such a way as to be meaningful to the person who receives it.
it is any thing that is communicated.
Data & Information, Drawbacks of File system, What is Database Management Systems, What is the need of DBMS, Examples of DBMS, Database Types, Applications of DBMS, Advantage of DBMS over file system, Disadvantages of DBMS, DBMS vs. File System
Database Models, Client-Server Architecture, Distributed Database and Classif...Rubal Sagwal
Introduction to Data Models
-Hierarchical Model
-Network Model
-Relational Model
-Client/Server Architecture
Introduction to Distributed Database
Classification of DBMS
Data:
– Raw facts; building blocks of information
– Unprocessed information
Information:
– Data processed to reveal meaning
• Accurate, relevant, and timely information is key
to good decision making.
Data
Data is a collection of facts, such as numbers, words, measurements, observations or even just descriptions of things.
Data can be qualitative or quantitative.
Information
Information is data that has been processed in such a way as to be meaningful to the person who receives it.
it is any thing that is communicated.
Data & Information, Drawbacks of File system, What is Database Management Systems, What is the need of DBMS, Examples of DBMS, Database Types, Applications of DBMS, Advantage of DBMS over file system, Disadvantages of DBMS, DBMS vs. File System
Database Models, Client-Server Architecture, Distributed Database and Classif...Rubal Sagwal
Introduction to Data Models
-Hierarchical Model
-Network Model
-Relational Model
-Client/Server Architecture
Introduction to Distributed Database
Classification of DBMS
https://www.learntek.org/blog/types-of-databases/
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses.
Muhammad Sharif database administrator SKMCHRC Lahore, Pakistan
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DBA Muhammad Sharif database systems
#MUHAMMAD SHARIF DATABASE SYSTEMS HANDBOOK DBA
Muhammad Sharif database administrator SKMCHRC Lahore, Pakistan
I'm writing this book. I'm Muhammad Sharif write a Database systems handbook about dbms, rdbms database management system abrivations.
I have core knowledge of database systems and its structure and database system administration too.
I thanks to all my reader who ack.
#MUHAMMAD SHARIF DATABASE SYSTEMS HANDBOOK DBA
Muhammad Sharif database administrator SKMCHRC Lahore, Pakistan
I'm writing this book. I'm Muhammad Sharif write a Database systems handbook about dbms, rdbms database management system abrivations.
I have core knowledge of database systems and its structure and database system administration too.
I thanks to all my reader who ack.
#MUHAMMAD SHARIF DATABASE SYSTEMS HANDBOOK DBA
Muhammad Sharif database administrator SKMCHRC Lahore, Pakistan
I'm writing this book. I'm Muhammad Sharif write a Database systems handbook about dbms, rdbms database management system abrivations.
I have core knowledge of database systems and its structure and database system administration too.
I thanks to all my reader who ack.
A database model refers to the structure of a database and determines how the data within the database can be organized and manipulated. Let’s explore some common types of database models:
Relational Model: The most popular example, the relational model, organizes data into tables (also known as relations). Each table contains rows representing records and columns representing attributes. Relationships between tables are established using keys.
Hierarchical Model: Developed by IBM for IMS (Information Management System), this model arranges data in a tree-like structure. Each record is a tree node, and relationships follow a one-to-many pattern. It’s predictable and efficient for data access.
Network Model: This model allows many-to-many relationships between records. It’s more flexible than the hierarchical model but less common.
Entity–Relationship Model (ER Model): It represents entities, their attributes, and the relationships between them. ER diagrams visually depict these components.
Object Model: Used in object-oriented databases, it treats data as objects with properties and methods. It’s suitable for complex data structures.
Document Model: Commonly used in NoSQL databases, it stores data as documents (e.g., JSON or XML). Each document can have varying attributes.
Entity–Attribute–Value (EAV) Model: A flexible model where data is stored in a sparse matrix. It’s useful for handling dynamic attributes.
Star Schema: Primarily used in data warehousing, it simplifies complex data structures into a central fact table connected to dimension tables.
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DATABASE SYSTEMS HANDBOOK BY MUHAMMAD SHARIF
Complete book Database management systems Handbook 3rd edition by Muhammad Sharif
#DBMS
#RDBMS
#DATABASE MANAGEMENT SYSTEMS HANDBOOK
#DATABASE COMPLETE BOOK HANDBOOK
DATABASE SYSTEMS BY MUHAMMAD SHARIF
DATABASE SYSTEMS HANDBOOK BY MUHAMMAD SHARIF
Full book Database system Handbook 3rd edition by Muhammad Sharif
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Complete Full book Database system Handbook 3rd edition by Muhammad Sharif
I'm DBA in SKMCHRC and I have did this book by title: Database systems handbook.
Its other names are: Database management systems, Database systems basic conecpts
Database services and Relational Database management systems handbook:
Author name is Muhammad Sharif.
#Database_systems_handbook
#Database_Management_Systems
#Relational Database_management systems
#DBMS
#RDBMS
Complete book Database management systems Handbook 3rd edition by Muhammad Sharif
#DBMS
#RDBMS
#DATABASE MANAGEMENT SYSTEMS HANDBOOK
#DATABASE COMPLETE BOOK HANDBOOK
DATABASE SYSTEMS BY MUHAMMAD SHARIF
DATABASE SYSTEMS HANDBOOK BY MUHAMMAD SHARIF
TITLE: DATABASE SYSTEMS HANDBOOK
Database systems Handbook by Muhammad Sharif dba
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Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
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/
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
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.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
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.
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.
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
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
DBMS basics
1. PRANVEER SINGH INSTITUTE
OF TECHNOLOGY
NH-2 BHAUTI, KANPUR
PROFESSIONAL COMMUNICATION
PROJECT WORK
Presentation by:- Under Guidance of
Praveen Srivastava Mrs. Raavee Tripathi
CS - 1 A
Roll No:1116410111
1
4. 4
INTRODUCTION
A database may be defined as a
collection of interrelated data stored
together to serve multiple applications
A database system is basically a computer based
record keeping system. The collection of data,
usually referred to ac the database, contains
information about one particular enterprise. It
maintains any information that may be necessary
to the decision-making processes involved in the
management of that organization.
5. 5
Purpose of DBMS
• Database reduce the data redundancy to
a large extent.
• Databases can control data inconsistency
to a large extent.
• Database facilitate sharing of data.
• Database enforce standards.
• Database can ensure data security.
• Integrity can be maintained through
database.
6. 6
DATABASE ABSTRACTION
• Levels of Database Implementation.
1. Internal Level
2 . Conceptual Level
3 . External Level
• Data Independency.
The ability to modify a scheme definition in one level without
affecting a scheme definition in the next higher level is called
Data independency.
7. 7
DATA MODELS
• The Relational Data Model.
In relational data model, the data is organized into tables {i.e., rows $
column}
• The Network Data Model.
In network model, data is represented by collections of record $
relationships among data are represented by links.
• The Hierarchical Data Model.
The only difference between hierarchical $ relational data
model is that, records are organized as trees rather
than arbitrary graph.
8. 8
THE RELATIONAL
MODEL
1. Terminology
• Relation : It is a table i.e., data is arranged in rows
and columns.
• Domain : It is a pool of values from which the actual
values appearing in a given column are drawn.
• Tuple : The rows of tables (relation) are generally
referred to as Tuple.
• Attribute : The columns of a table (relation) are
generally referred to as attribute.
• Degree : The number of attributes in a relation.
• Cardinality : The number of tuples in a relation.
9. 9
2. VIEWS
A view is a (virtual) table that does not really exist
in its own right but is instead derived from one or
more underlying base table(s).
3. Structure of Relational
Databases
• Keys
a)Primary key: It is a set of one or more attributes
that can uniquely identify tuples within the relation.
b)Canditate key: All attribute combinations inside a
relation that can serve as primary key are candidate
keys as they are candidates for the primary key
position.
10. 10
c) Alternate key : A candidate key that is not the
primary key is called an alternate key.
d) Foreign key : A non-key attribute, whose values are
derived from the primary key of some other table, is
known as foreign-key in its current table.
• Referential integrity
It is a system of rules that a DBMS uses to ensure
that relationships between records in related tables are
valid, and that users don’t accidentally delete or change
related data.
11. 11
Comparison of Data Models
Data models can be evaluated on the basis of usability,
implementability and performance.
Data experts have been debating for some time which
DBMS data model is ‘best’. The answer depends, in part,
on philosophical orientation. The hierarchical model is
the oldest model and has long been the most popular on
mainframes. People who think the user should be able to
have some control over the details of storage allocation
and search paths often prefer network systems.
However, few database systems are fully relational.
Instead they graft relational features on a basic
hierarchical or network structure.
12. 12
Information plays an important
role in management of the
building systems and the DBMS
is providing information and
updates and supplies relevant
multi-user information to the
concerned users. Based on the
statistics the DBMS will provide,
through out the year major
planning could be done and that
could lead deriving parameters
for AI Techniques and fuzzy logic
which could make the building
system more efficient and
responsive to the human needs
and comfort.