Data modeling dbms
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Conceptual model, Think of the conceptual model as an architects conceptual drawing of a house. It provides a good idea of what is required with very little additional detail; Data modelling is a technique for defining business油requirements油for a油database. It is sometimes called database modelling油because a油data model油is eventually implemented in a database
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Karen Lopez will share tips and insights on working through the data challenges for business analysts and Josh Buckner will share a solution to address those concerns.3._DWH_Architecture__Components.ppt
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This document discusses the components and architecture of a data warehouse. It describes the major components as the source data component, data staging component, information delivery component, metadata component, and management/control component. It then discusses each of these components in more detail, specifically covering source data types, the extract-transform-load process in data staging, the data storage repository, and authentication/monitoring in information delivery. Dimensional modeling is also introduced as the preferred approach for data warehouse design compared to entity-relationship modeling.Recently uploaded (20)
Chapter 4. Environmental Scanning and Industry Analysis.pdf
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This course provides students with a comprehensive understanding of strategic management principles, frameworks, and applications in business. It explores strategic planning, environmental analysis, corporate governance, business ethics, and sustainability. Pests of Cruciferous Crops, their Damage Symptoms and Management Practices.pptx
Pests of Cruciferous Crops, their Damage Symptoms and Management Practices.pptxDeepali Shid
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Quiz Questions of Preliminary Round, Shibpur BE (IIEST) Tech fest of Mechanical Engineering Dept.
By Rudra Chakraborty
Q-Factor General Quiz-2nd March 2025, Quiz Club NITW
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National Policy On Education-1986 (Objectives And Major Recommendations)
Introduction of secondary metabolities.pptx
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PHARMACOGNOSY & Phytochemistry-I (BP405T)Unit-IVPart-2INTRODUCTION OF SECONDARY METABOLITE
PRIMARY AND SECONDARY METABOLITE
Alkaloids: GENERAL PROPERTIES OF THE ALKALOIDS CHEMICAL PROPERTIES
CLASSIFICATION OF ALKALOIDS
Biosynthetic Classification:
Pharmacological Classification
Taxonomic Classification
Chemical Classification
Identification test of alkaloids
Mayers reagents
Wagners reagents
Dragendorffs reagent
Hagers reagent
GENERAL METHODS OF EXTRACTION AND ISOLATION OF ALKALOIDS FUNCTIONS OF ALKALOIDS IN PLANT Pharmacological activity and uses
GLYCOSIDES:Physical properties Chemical properties
Classification
On the basis of the type of the sugar or the glycone part
Glycosides are classified on the basis of the pharmacological action
Glycosides are also classified on the basis of linkage between glycone and aglycone part
Identification test of glycosides
ISOLATION-(STAS-OTTO METHOD
TANNINS:Physical Properties
Chemical Properties
Classification of Tannin
Identification test of TanninHow to Manage Reporting in Events of Odoo 18
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For more information about my speaking and training work, visit: https://www.pookyknightsmith.com/speaking/
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Upcoming webinar slides - here's the Session overview:
How Can We Support Neurodivergent Learners Executive Function Skills?
This webinar equips educators with the understanding and tools to support neurodivergent learners in overcoming executive function challenges. With a focus on practical, classroom-ready strategies, attendees will learn how to foster independence, improve task management, and create environments where neurodivergent students can thrive. Rooted in empathy and understanding, the session highlights the key barriers to executive function and provides actionable approaches to address these in ways that benefit all learners. Staff will leave with ideas they can implement the very next day to make a tangible difference.
By the end of this session, participants will be able to:
1. Identify key executive function challenges and their impact on learning & behaviour
2. Understand the lived experiences of neurodivergent learners to foster empathy
3. Implement practical strategies to support organisation, focus, & task completion
4. Adapt communication & environments to reduce cognitive load & support self-regulation
5. Equip students with tools to build independence and self-advocacy
Unit 3_Hash function and MD5 working.pdf
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Cryptographic Hash Function, Requirements of Cryptographic Hash Function, Applications of Cryptographic Hash Function, Two Simple Hash Functions, Message Digest Algorithm, MD5 working, MD5 Solved Example, Birthday AttackPrimary metabolites(Carbohydrates Acacia, Agar, Tragacanth, Honey).pptx
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PHARMACOGNOSY & Phytochemistry-I (BP405T) Unit-VPart-2Primary metabolites:(Carbohydrates: Acacia, Agar, Tragacanth, Honey)
Carbohydrate: Properties, classification Chemical test
Tragacanth
Synonyms
Biological Source
Geographical Source Method of Collection & Preparation Description:
Chemical Constituent Chemical test uses
Adulterant and Substitutes
Acacia
Synonyms
Biological Source
Geographical Source Method of Collection & Preparation Description:
Chemical Constituent Chemical test uses
Adulterant and Substitutes
Agar
Synonyms
Biological Source
Geographical Source Method of Collection & Preparation Description:
Chemical Constituent Chemical test uses
Adulterant and Substitutes
Honey
Synonyms
Biological Source
Geographical Source Method of Collection & Preparation Description:
Chemical Constituent Chemical test uses
Adulterant and Substitutes
The Paradox of Perfection - Publecture (EOS VU Amsterdam)
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"The Paradox of Perfection: Why Does Performance Pressure Hold Us Back?" with Wico Mulder, a youth doctor for adolescents and public health physician (Arts M&G). 咋
Gain valuable insights into how perfectionism and performance pressure impact personal growth and how to navigate them effectively. https://eosvu.nl/blogs/publecturestudy - 17 maart 2025.pdf
Abigail Sageev presents at the OECD webinar 'Improving skills outcomes throug...
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Abigail Sageev, Policy Analyst at the OECD Centre for Skills, presents at the OECD webinar 'Improving skills outcomes through stronger coordination and stakeholder engagement' on 18 March 2025. The recording can be found on the webpage - https://oecdedutoday.com/webinars/ where we were joined by speakers Ina Progonati, Sustainability &Social Impact Partnerships and Programs Worldwide Lead, HP, Liene Voronenko, Expert of Education, Employers Confederation of Latvia, Johan Enfeldt, Research Officer, Department for Social Policy Issues, Swedish Trade Union Confederation, Marius Busemeyer, Professor of Political Science, University of Konstanz, Andrew Bell, Deputy Head of the OECD Centre for Skills and Head of OECD Skills Strategy and Laura Reznikova, Policy Analyst, OECD Centre for Skills. You can check out the work of the Centre for Skills here - OECD Centre for Skills
https://www.oecd.org/skills/centre-for-skillsFillable Strategies for Understanding and Supporting Neurodivergent Multiling...
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This is the PDF Fillable Electronic Workbook needed for the upcoming webinar/ workshop on Strategies for Neurodivergent Multilingual Learners.How to Add Notes, Sections & Catalog in Odoo 18
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In this slide, well discuss how to add notes, sections, and catalogs in Odoo 18. You can add detailed notes to records for better context and tracking. Custom sections can be created to organize and categorize information effectively.Pharmacognosy in various systems of medicine.pptx
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PHARMACOGNOSY & Phytochemistry-I (BP405T)Unit-IVPart-1Pharmacognosy in various systems of medicine
Role of Pharmacognosy in allopathy and traditional systems of medicine
Ayurveda systems of medicine
Siddha systems of medicine
Homeopathy systems of medicine
Unani systems of medicine
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Pests of Horticultural Crops
Pests of Cucurbitaceous Vegetables, Colocasia and Moringa like Fruit fly, Aphids, Leaf miner, Whitefly, Thrips, Pumpkin beetle, Blister beetle, Leaf eating caterpillar, Stem borer, Aphid
Subscription plan in odoo 17 - Odoo 際際滷s
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This slide will show the subscription plan in Odoo 17. A subscription plan can be used as a template for creating a new subscription for the customers. And using the subscription plan, we create a new subscription for the customers.Mayo, DG March 8-Emory AI Systems and society conference slides.pdf
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Are Controversies in Statistics Relevant for Responsible AI/ML?
A central debate in statistics concerns probabilitys role: is it to control error rates (frequentist) or express belief (Bayesian)? Frequentists prioritize error control, ensuring rare false rejections and strong power to detect falsity. For Bayesians, by contrast, evidence from the data resides in the likelihood ratios, ignoring error probabilities. The replication crisis fueled criticism of statistical significance tests, which are blamed for irreproducibility. Yet, selection biasesp-hacking, optional stoppingare the real issue. Ironically, Bayesian alternatives (e.g., Bayes factors) fail to guard against these biases, leading to misguided reforms that discard crucial error control. The same data-dredged hypothesis can occur in Bayes factors, and Bayesian updatingbut without direct grounds to criticize flouting of error statistical control.
AI/ML shifts the focus away from understanding data generation to optimizing prediction. But when it comes to problems of checking if AI/ML outputs are responsible and trustworthy, I argue, error statistical considerations become relevant. Fairness hacking, and explanation (justification) hacking in XAI, like p-hacking and BF hacking, can make it easy to obtain misleading interpretations of data. Reforms from error statistics: preregistration and adjustment of error rates, are relevant for critically appraising them. I put forward a general requirement that is operable in both fields: A claim lacks warrant if little if anything has been done to detect its flawsit fails a severe test.Data modeling dbms
- 1. DBMS Zaheer uddin soomro Data Modeling
- 2. Data Model Graphical documentation of Data requirement is called data model. It is used to confirm understanding of data requirement A data model is a graphical means of documenting data requirements and defining database design specifications.
- 3. Types of data model Conceptual model, Think of the conceptual model as an architects conceptual drawing of a house. It provides a good idea of what is required with very little additional detail; Enterprise data model /Global Business Model Enterprise Data Modeling is the practice of creating a graphical model of the data used by an enterprise or company. Logical model, detailed representation of some or all of an organization's data; Dimensional Model, techniques and concepts used in data warehouse design. dimensions are groups of hierarchies and descriptors that define the facts. For example, sales amount is a fact; timestamp, product, register#, store#, etc. are elements of dimensions Physical Model, is the final representation of the data base structures that will be generated from the model. It contains the detailed specifications for the database design and, in a model driven environment, the modeling tool will generate the data definition language (DDL) that is used to create the database structure.