Normalization

•Download as PPTX, PDF•

0 likes•103 views

N

A simple Presentation about Normalization

Normalizati
on

“
⊷ Group Members
2
1. P.P.P.Madhushani
2. G.G.A.R.U.Gunasekara
3. N.H.B.Pethiyagoda
4. Ayesha Vidyani

Normalization
⊷ Database Normalization is a technique of organizing
the data in the database. Normalization is a systematic
approach of decomposing tables to eliminate data
redundancy(repetition) and undesirable characteristics
like Insertion, Update and Deletion Anamolies. It is a
multi-step process that puts data into tabular form,
removing duplicated data from the relation tables.
Normalization is used for mainly two purposes,
⊷ Eliminating redundant (useless) data.
⊷ Ensuring data dependencies make sense i.e. data is
logically stored.
3

“
Data Redundancy occurs when the same data is entered
in to two or more fields of a database.
4
Difference Between Duplication and Redundancy
Data Duplication occurs when an exact copy of a
piece of data is created.

“
5
Aims of Normalization

Problems
Without
Normalization
6

There are 3 problems
that can occur without
Normalization
7
⊷ 1. Insert Anomaly
⊷ 2. Delete Anomaly
⊷ 3. Update Anomaly

Stages of Normalization
8
⊷ First Normal Form
⊷ Second Normal Form
⊷ Third Normal Form
⊷ BCNF
⊷ Fourth Normal Form

First Normal Form
9
A table is in it’s first normal form if
it contains no repeating attributes
or groups of attributes.

Second Normal Form
12
A table is in the second normal
form AND no column that is not
part of the primary key is
dependant only a portion of the
Primary Key.

Third Normal Form
15
A table is in the third normal
form if it is in the second
normal form. And there are
no non-key columns
dependant on other non-key
columns that could not act
as the primary key.

Thank You
18

More Related Content

What's hot

50120130406032

IAEME Publication

Data preprocessing

Data preprocessing

Data preprocessing

Genomic data provides clinical researchers with vast opportunities to study various patient ailments. Yet the same data contains revealing information, some of which a patient might want to remain concealed. The question then arises: how can an entity transact in full DNA data while concealing certain sensitive pieces of information in the genome sequence, and maintain DNA data utility? As a response to this question, we propose a codon frequency obfuscation heuristic, in which a redistribution of codon frequency values with highly expressed genes is done in the same amino acid group, generating an obfuscated DNA sequence. Our preliminary results show that it might be possible to publish an obfuscated DNA sequence with a desired level of similarity (utility) to the original DNA sequence. http://arxiv.org/abs/1405.5410

A Codon Frequency Obfuscation Heuristic for Raw Genomic Data Privacy

A Codon Frequency Obfuscation Heuristic for Raw Genomic Data Privacy

A Codon Frequency Obfuscation Heuristic for Raw Genomic Data Privacy

Data mining is a process which finds useful patterns from large amount of data. This paper is analyzing decision trees technique using the medicine data from central medical store, department of health. The results are support to best solution to share many type of medicine for manager at Central Medical store. This Central Medical store is supporting medicine to hospitals from upper Myanmar. Yin Yin Cho | Khin Htay | Win Myat Thuzar "Hospital Medicine Classification using Data Mining Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26774.pdfPaper URL: https://www.ijtsrd.com/computer-science/data-miining/26774/hospital-medicine-classification-using-data-mining-techniques/yin-yin-cho

Hospital Medicine Classification using Data Mining Techniques

Hospital Medicine Classification using Data Mining Techniques

Hospital Medicine Classification using Data Mining Techniques

IRJET- Medical Data Mining

IRJET- Medical Data Mining

IRJET- Medical Data Mining

Heart disease diagnosis requires more experience and it is a complex task. The Heart MRI, ECG and Stress Test etc are the numbers of medical tests are prescribed by the doctor for examining the heart disease and it is the way of tradition in the prediction of heart disease. Today world, the hidden information of the huge amount of health care data is contained by the health care industry. The effective decisions are made by means of this hidden information. For appropriate results, the advanced data mining techniques with the information which is based on the computer are used. In any empirical sciences, for the inference and categorisation, the new mathematical techniques to be used called Artificial neural networks (ANNs) it also be used to the modelling of the real neural networks. Acting, Wanting, knowing, remembering, perceiving, thinking and inferring are the nature of mental phenomena and these can be understand by using the theory of ANN. The problem of probability and induction can be arised for the inference and classification because these are the powerful instruments of ANN. In this paper, the classification techniques like Naive Bayes Classification algorithm and Artificial Neural Networks are used to classify the attributes in the given data set. The attribute filtering techniques like PCA (Principle Component Analysis) filtering and Information Gain Attribute Subset Evaluation technique for feature selection in the given data set to predict the heart disease symptoms. A new framework is proposed which is based on the above techniques, the framework will take the input dataset and fed into the feature selection techniques block, which selects any one techniques that gives the least number of attributes and then classification task is done using two algorithms, the same attributes that are selected by two classification task is taken for the prediction of heart disease. This framework consumes the time for predicting the symptoms of heart disease which make the user to know the important attributes based on the proposed framework.

Propose a Enhanced Framework for Prediction of Heart Disease

Propose a Enhanced Framework for Prediction of Heart Disease

Propose a Enhanced Framework for Prediction of Heart Disease

IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology

Clustering of medline documents using semi supervised spectral clustering

Clustering of medline documents using semi supervised spectral clustering

Clustering of medline documents using semi supervised spectral clustering

eSAT Publishing House

Normalization

PratibhaRashmiSingh

IRJET- A Review of Data Cleaning and its Current Approaches

IRJET- A Review of Data Cleaning and its Current Approaches

IRJET- A Review of Data Cleaning and its Current Approaches

Pemrograman komputer 10 (database)

Pemrograman komputer 10 (database)

Pemrograman komputer 10 (database)

Data base design

Data base design

Data base design

IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.

Data slicing technique to privacy preserving and data

Data slicing technique to privacy preserving and data

Data slicing technique to privacy preserving and data

eSAT Publishing House

Abstract Many techniques have been designed for privacy preserving and micro data publishing, such as generalization and bucketization. Several works showed that generalization loses some amount of information especially for high dimensional data. So it’s not efficient for high dimensional data. In case of Bucketization, it does not prevents membership disclosure and also does not applicable for data that do not have a clear separation between Quasi-identifying attributes and sensitive attributes. In this paper, we presenting an innovative technique called data slicing which partitions the data. An efficient algorithm is developed for computing sliced data that obeys l-diversity requirement. we also show how data slicing is better than generalization and bucketization. Data slicing preserves better utility than generalization and also does not requires clear separation between Quasi-identifying and sensitive attributes. Data slicing is also used to prevent attribute disclosure and develop an efficient algorithm for computing the sliced data that obeys l-diversity requirement. Experimental results confirm that data slicing preserves data utility than generalization and more effective than bucketization involving sensitive attributes. Experimental results demonstrate the effectiveness of this method. Keywords –Privacy preserving, Data Security, Data Publishing, Microdata

Data slicing technique to privacy preserving and data publishing

Data slicing technique to privacy preserving and data publishing

Data slicing technique to privacy preserving and data publishing

Suppose Alice owns a k-anonymous database and needs to determine whether her database, when inserted with a tuple owned by Bob, is still k-anonymous. Also, suppose that access to the database is strictly controlled, because for example data are used for certain experiments that need to be maintained confidential. Clearly, allowing Alice to directly read the contents of the tuple breaks the privacy of Bob (e.g., a patientâ€™s medical record); on the other hand, the confidentiality of the database managed by Alice is violated once Bob has access to the contents of the database. Thus, the problem is to check whether the database inserted with the tuple is still k-anonymous, without letting Alice and Bob know the contents of the tuple and the database, respectively. In this paper, we propose two protocols solving this problem on suppression-based and generalization-based k-anonymous and confidential databases. The protocols rely on well-known cryptographic assumptions, and we provide theoretical analyses to proof their soundness and experimental results to illustrate their efficiency.

Gene Selection Based on Rough Set Applications of Rough Set on Computational ...

Gene Selection Based on Rough Set Applications of Rough Set on Computational ...

Gene Selection Based on Rough Set Applications of Rough Set on Computational ...

ICTer conference2014extendedabstract

ICTer conference2014extendedabstract

ICTer conference2014extendedabstract

University of Moratuwa

Data mining techniques play very important role in health care industry. Liver disease is one of the growing diseases these days due to the changed life style of people. Various authors have worked in the field of classification of data and they have used various classification techniques like Decision Tree, Support Vector Machine, Naïve Bayes, Artificial Neural Network (ANN) etc. These techniques can be very useful in timely and accurate classification and prediction of diseases and better care of patients. The main focus of this work is to analyze the use of data mining techniques by different authors for the prediction and classification of liver patient.

[IJET-V2I3P22] Authors: Harsha Pakhale,Deepak Kumar Xaxa

[IJET-V2I3P22] Authors: Harsha Pakhale,Deepak Kumar Xaxa

[IJET-V2I3P22] Authors: Harsha Pakhale,Deepak Kumar Xaxa

IJET - International Journal of Engineering and Techniques

Ijarcet vol-2-issue-4-1393-1397

Ijarcet vol-2-issue-4-1393-1397

Ijarcet vol-2-issue-4-1393-1397

International Journal of Computational Engineering Research(IJCER)

International Journal of Computational Engineering Research(IJCER)

International Journal of Computational Engineering Research(IJCER)

IRJET- A Survey on Prediction of Heart Disease Presence using Data Mining and...

IRJET- A Survey on Prediction of Heart Disease Presence using Data Mining and...

IRJET- A Survey on Prediction of Heart Disease Presence using Data Mining and...

What's hot (19)

50120130406032

Data preprocessing

Data preprocessing

Data preprocessing

A Codon Frequency Obfuscation Heuristic for Raw Genomic Data Privacy

A Codon Frequency Obfuscation Heuristic for Raw Genomic Data Privacy

A Codon Frequency Obfuscation Heuristic for Raw Genomic Data Privacy

Hospital Medicine Classification using Data Mining Techniques

Hospital Medicine Classification using Data Mining Techniques

Hospital Medicine Classification using Data Mining Techniques

IRJET- Medical Data Mining

IRJET- Medical Data Mining

IRJET- Medical Data Mining

Propose a Enhanced Framework for Prediction of Heart Disease

Propose a Enhanced Framework for Prediction of Heart Disease

Propose a Enhanced Framework for Prediction of Heart Disease

Clustering of medline documents using semi supervised spectral clustering

Clustering of medline documents using semi supervised spectral clustering

Clustering of medline documents using semi supervised spectral clustering

Normalization

IRJET- A Review of Data Cleaning and its Current Approaches

IRJET- A Review of Data Cleaning and its Current Approaches

IRJET- A Review of Data Cleaning and its Current Approaches

Pemrograman komputer 10 (database)

Pemrograman komputer 10 (database)

Pemrograman komputer 10 (database)

Data base design

Data base design

Data base design

Data slicing technique to privacy preserving and data

Data slicing technique to privacy preserving and data

Data slicing technique to privacy preserving and data

Data slicing technique to privacy preserving and data publishing

Data slicing technique to privacy preserving and data publishing

Data slicing technique to privacy preserving and data publishing

Gene Selection Based on Rough Set Applications of Rough Set on Computational ...

Gene Selection Based on Rough Set Applications of Rough Set on Computational ...

Gene Selection Based on Rough Set Applications of Rough Set on Computational ...

ICTer conference2014extendedabstract

ICTer conference2014extendedabstract

ICTer conference2014extendedabstract

[IJET-V2I3P22] Authors: Harsha Pakhale,Deepak Kumar Xaxa

[IJET-V2I3P22] Authors: Harsha Pakhale,Deepak Kumar Xaxa

[IJET-V2I3P22] Authors: Harsha Pakhale,Deepak Kumar Xaxa

Ijarcet vol-2-issue-4-1393-1397

Ijarcet vol-2-issue-4-1393-1397

Ijarcet vol-2-issue-4-1393-1397

International Journal of Computational Engineering Research(IJCER)

International Journal of Computational Engineering Research(IJCER)

International Journal of Computational Engineering Research(IJCER)

IRJET- A Survey on Prediction of Heart Disease Presence using Data Mining and...

IRJET- A Survey on Prediction of Heart Disease Presence using Data Mining and...

IRJET- A Survey on Prediction of Heart Disease Presence using Data Mining and...

Similar to Normalization

B0930610

DataPreprocessing.pptx

DataPreprocessing.pptx

DataPreprocessing.pptx

Dr-Dipali Meher

Class imbalance exists in many classification problems, and since the data is designed for accuracy, imbalance in data classes can lead to classification challenges with a few classes having higher misclassification costs. The Backblaze dataset, a widely used dataset related to hard discs, has a small amount of failure data and a large amount of health data, which exhibits a serious class imbalance. This paper provides a comprehensive overview of research in the field of imbalanced data classification. The discussion is organized into three main aspects: data-level methods, algorithmic-level methods, and hybrid methods. For each type of method, we summarize and analyze the existing problems, algorithmic ideas, strengths, and weaknesses. Additionally, the challenges of unbalanced data classification are discussed, along with strategies to address them. It is convenient for researchers to choose the appropriate method according to their needs.

A SURVEY OF METHODS FOR HANDLING DISK DATA IMBALANCE

A SURVEY OF METHODS FOR HANDLING DISK DATA IMBALANCE

A SURVEY OF METHODS FOR HANDLING DISK DATA IMBALANCE

17.INTRODUCTION TO SCHEMA REFINEMENT.pptx

17.INTRODUCTION TO SCHEMA REFINEMENT.pptx

17.INTRODUCTION TO SCHEMA REFINEMENT.pptx

AshokRachapalli1

CIS 515 discussion post responses. There are two discussions here that need to be responded to thoroughly. Responses must be on APA format 150+words 1-2 legitimate verifiable sources per response. Respond to the colleagues posts regarding: • Many legacy systems require normalization. Identify at least two factors that should be considered in order to produce an optimal normalized set of tables when performing normalization. Include in your discussion a detailed example on how each factor would eliminate data redundancy. • Optimal database design recognizes proper organization of table structures and relationships. Suggest at least two methods that can be used to improve the design of a database system. JM post states the following: Factors to Consider for an Optimal Normalization Normalization refers to the process of organizing data on a database to reduce redundancy when designing a database. One of the factors to consider during normalization is naming conventions. The names used should describe the type of information contained in the database for easy data identification. Abbreviations and obscure acronyms should be avoided for names because they can easily obfuscate the meaning and can as well be challenging to remember. The naming system used across the entire database should be consistent and memorable. It should as well provide information on users, filenames, and other related objects. Another factor to consider is the nature of the database. Tables should incur divided to ensure that data are well isolated to allow additions, deletion, and modifications without interfering with the entire database. Each field should have different information, which should be independent of the information on other grounds. It will reduce redundancy by eliminating the possibility of data duplication (Dennis et al. 12). Method of improving the design of the database system A properly designed database system enhance easy access to recent and accurate information. The method process of strengthening the design of database design includes normalization and storing binary data externally. Standardization ensures that data engage appropriately organized within the database. Normalization can incur achieved by using primary keys to ensure that each raw within the database system is unique. Using external data storage is also another method of improving database system design. It enhances the performance of the data and ensures easy access to the data. Refining primary keys as required for data granularity is also another method of improving database system design. The entity of using the granularity of low keys, atomic value ensures that the database is more detailed and specific (Coronel, 2016). Coronel, Carlos, and Steven Morris. Database systems: design, implementation, & management. Cengage Learning, 2016. Dennis, Alan, Barbara Haley Wixom, and Roberta M. Roth. Systems analysis and design. John Wiley & sons, 2018 LP.

CIS 515 discussion post responses.There are two discussions he.docx

CIS 515 discussion post responses.There are two discussions he.docx

CIS 515 discussion post responses.There are two discussions he.docx

UNIT 2: Part 2: Data Warehousing and Data Mining

UNIT 2: Part 2: Data Warehousing and Data Mining

UNIT 2: Part 2: Data Warehousing and Data Mining

International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.

G045033841

Dwh lecture-07-denormalization

Dwh lecture-07-denormalization

Dwh lecture-07-denormalization

Data Cleaning Best Practices.pdf

Data Cleaning Best Practices.pdf

Data Cleaning Best Practices.pdf

Dmblog

veeralakshmi pandi

Data pre processing

Data pre processing

Data pre processing

Importance of Normalization

Importance of Normalization

Importance of Normalization

IDS Presentation.pptx

IDS Presentation.pptx

IDS Presentation.pptx

Data mining is a task in which data is extracted from the large database to make itin an understandable form or structure so that it can be used for further use. In this paper we present an approach by which the concept of hierarchal clustering applied over the horizontally partitioned data set. We also explain the desired algorithm like hierarichal clustering, algorithms for finding the minimum closest cluster. In this paper wealso explain the two party computations. Privacy of any data is the most important thing in these days hence we present an approach by which we can apply privacy preservation over the two party which are distributing their data horizontally. We also explain about the hierarichal clustering which we are going to apply in our present method.

TWO PARTY HIERARICHAL CLUSTERING OVER HORIZONTALLY PARTITIONED DATA SET

TWO PARTY HIERARICHAL CLUSTERING OVER HORIZONTALLY PARTITIONED DATA SET

TWO PARTY HIERARICHAL CLUSTERING OVER HORIZONTALLY PARTITIONED DATA SET

02 Related Concepts

02 Related Concepts

02 Related Concepts

Valerii Klymchuk

Knowledge discovery is the process of adding knowledge from a large amount of data. The quality of knowledge generated from the process of knowledge discovery greatly affects the results of the decisions obtained. Existing data must be qualified and tested to ensure knowledge discovery processes can produce knowledge or information that is useful and feasible. It deals with strategic decision making for an organization. Combining multiple operational databases and external data create data warehouse. This treatment is very vulnerable to incomplete, inconsistent, and noisy data. Data mining provides a mechanism to clear this deficiency before finally stored in the data warehouse. This research tries to give technique to improve the quality of information in the data warehouse.

Quality Assurance in Knowledge Data Warehouse

Quality Assurance in Knowledge Data Warehouse

Quality Assurance in Knowledge Data Warehouse

Universitas Pembangunan Panca Budi

DM_Notes.pptx

Dwh lecture 07-denormalization

Dwh lecture 07-denormalization

Dwh lecture 07-denormalization

Data Preparation.pptx

Data Preparation.pptx

Data Preparation.pptx

DrAbhishekKumarSingh3

Lecture 7

Similar to Normalization (20)

B0930610

DataPreprocessing.pptx

DataPreprocessing.pptx

DataPreprocessing.pptx

A SURVEY OF METHODS FOR HANDLING DISK DATA IMBALANCE

A SURVEY OF METHODS FOR HANDLING DISK DATA IMBALANCE

A SURVEY OF METHODS FOR HANDLING DISK DATA IMBALANCE

17.INTRODUCTION TO SCHEMA REFINEMENT.pptx

17.INTRODUCTION TO SCHEMA REFINEMENT.pptx

17.INTRODUCTION TO SCHEMA REFINEMENT.pptx

CIS 515 discussion post responses.There are two discussions he.docx

CIS 515 discussion post responses.There are two discussions he.docx

CIS 515 discussion post responses.There are two discussions he.docx

UNIT 2: Part 2: Data Warehousing and Data Mining

UNIT 2: Part 2: Data Warehousing and Data Mining

UNIT 2: Part 2: Data Warehousing and Data Mining

G045033841

Dwh lecture-07-denormalization

Dwh lecture-07-denormalization

Dwh lecture-07-denormalization

Data Cleaning Best Practices.pdf

Data Cleaning Best Practices.pdf

Data Cleaning Best Practices.pdf

Dmblog

Data pre processing

Data pre processing

Data pre processing

Importance of Normalization

Importance of Normalization

Importance of Normalization

IDS Presentation.pptx

IDS Presentation.pptx

IDS Presentation.pptx

TWO PARTY HIERARICHAL CLUSTERING OVER HORIZONTALLY PARTITIONED DATA SET

TWO PARTY HIERARICHAL CLUSTERING OVER HORIZONTALLY PARTITIONED DATA SET

TWO PARTY HIERARICHAL CLUSTERING OVER HORIZONTALLY PARTITIONED DATA SET

02 Related Concepts

02 Related Concepts

02 Related Concepts

Quality Assurance in Knowledge Data Warehouse

Quality Assurance in Knowledge Data Warehouse

Quality Assurance in Knowledge Data Warehouse

DM_Notes.pptx

Dwh lecture 07-denormalization

Dwh lecture 07-denormalization

Dwh lecture 07-denormalization

Data Preparation.pptx

Data Preparation.pptx

Data Preparation.pptx

Lecture 7

Recently uploaded

Abortion Clinic In Pretoria ](+27832195400*)[ 🏥 Safe Abortion Pills in Pretor...

Abortion Clinic In Pretoria ](+27832195400*)[ 🏥 Safe Abortion Pills in Pretor...

Abortion Clinic In Pretoria ](+27832195400*)[ 🏥 Safe Abortion Pills in Pretor...

Medical / Health Care (+971588192166) Mifepristone and Misoprostol tablets 200mg

Wired_2.0_CREATE YOUR ULTIMATE LEARNING ENVIRONMENT_JCON_16052024

Wired_2.0_CREATE YOUR ULTIMATE LEARNING ENVIRONMENT_JCON_16052024

Wired_2.0_CREATE YOUR ULTIMATE LEARNING ENVIRONMENT_JCON_16052024

Talk given at NewCrafts Paris Conference 2024 Abstract: Have you ever observed quality problems with what your team is delivering? Have you ever felt your team is learning about the actual status quo late, too late to include these insights in your next steps? Have you ever wondered how to influence change when you’re “just” a specialist on the team, maybe even felt powerless? I’ve mostly worked with people who never experienced effective collaboration across roles and specialties. How to get such a team to move toward testing throughout the delivery workflow from idea to production, on all kinds of levels, for all parts of the product, by the whole team? How to consider quality from the start and have it continuously inform our decision-making? Over the years, I’ve built a repertoire of tactics to help teams transform toward holistic testing and quality. They range from meeting people where they are to creating guidelines, pairing and many others. It’s a toolbox of approaches to try out and find the sweet spot where people start moving toward better directions together. These tactics are fallible, not all of them work in all contexts, and yet they have helped my teams get to a better place. Join this talk to get inspired to take things into your hands. Learn what you can try yourself in your context to help your team make the first steps on your journey towards holistic testing and quality. Key learnings: - Learn how you can influence team culture, no matter your role or experience level - Add team transformation tactics to your toolbox of approaches to try - Understand the many ways we can move towards holistic testing and quality

Team Transformation Tactics for Holistic Testing and Quality (NewCrafts Paris...

Team Transformation Tactics for Holistic Testing and Quality (NewCrafts Paris...

Team Transformation Tactics for Holistic Testing and Quality (NewCrafts Paris...

Abortion Pill Prices Jane Furse ](+27832195400*)[🏥Women's Abortion Clinic in Jane Furse ● Abortion Pills For Sale in Jane Furse ● Jane Furse 🏥🚑!! Abortion Clinic Near Me Cost, Price, Women's Clinic Near Me, Abortion Clinic Near, Abortion Doctors Near me, Abortion Services Near Me, Abortion Pills Over The Counter, Abortion Pill Doctors' Offices, Abortion Clinics, Abortion Places Near Me, Cheap Abortion Places Near Me, Medical Abortion & Surgical Abortion, approved cyctotec pills and womb cleaning pills too plus all the instructions needed This Discrete women’s Termination Clinic offers same day services that are safe and pain free, we use approved pills and we clean the womb so that no side effects are present. Our main goal is that of preventing unintended pregnancies and unwanted births every day to enable more women to have children by choice, not chance. We offer Terminations by Pill and The Morning After Pill.” Our Private VIP Abortion Service offers the ultimate in privacy, efficiency and discretion. we do safe and same day termination and we do also womb cleaning as well its done from 1 week up to 28 weeks. We do delivery of our services world wide SAFE ABORTION CLINICS/PILLS ON SALE WE DO DELIVERY OF PILLS ALSO Abortion clinic at very low costs, 100% Guaranteed and it’s safe, pain free and a same day service. It Is A 45 Minutes Procedure, we use tested abortion pills and we do womb cleaning as well. Alternatively the medical abortion pill and womb cleansing !!

Abortion Pill Prices Jane Furse ](+27832195400*)[🏥Women's Abortion Clinic in ...

Abortion Pill Prices Jane Furse ](+27832195400*)[🏥Women's Abortion Clinic in ...

Abortion Pill Prices Jane Furse ](+27832195400*)[🏥Women's Abortion Clinic in ...

Medical / Health Care (+971588192166) Mifepristone and Misoprostol tablets 200mg

Azure Native Qumulo scales elastically for common High Performance Compute (HPC) workloads based on application requirements for: Financial Services, Automotive, Genomics / Life Sciences, Media and Entertainment, Energy, Oil and Gas, and more. Performance can be increased (and elastically decreased) much higher than the examples shown here. These slides offer a glimpse into ANQ's HPC capabilities, although at a smaller scale. We invite YOU to do your own testing (with a free ANQ trial) and work with us to test your HPC workloads in Azure.

AzureNativeQumulo_HPC_Cloud_Native_Benchmarks.pdf

AzureNativeQumulo_HPC_Cloud_Native_Benchmarks.pdf

AzureNativeQumulo_HPC_Cloud_Native_Benchmarks.pdf

Evolving Data Governance for the Real-time Streaming and AI Era

Evolving Data Governance for the Real-time Streaming and AI Era

Evolving Data Governance for the Real-time Streaming and AI Era

GraphSummit Milan - Visione e roadmap del prodotto Neo4j

GraphSummit Milan - Visione e roadmap del prodotto Neo4j

GraphSummit Milan - Visione e roadmap del prodotto Neo4j

Abortion Pill Prices Polokwane ](+27832195400*)[ 🏥 Women's Abortion Clinic in...

Abortion Pill Prices Polokwane ](+27832195400*)[ 🏥 Women's Abortion Clinic in...

Abortion Pill Prices Polokwane ](+27832195400*)[ 🏥 Women's Abortion Clinic in...

Medical / Health Care (+971588192166) Mifepristone and Misoprostol tablets 200mg

Weeding your micro service landscape.pdf

Weeding your micro service landscape.pdf

Weeding your micro service landscape.pdf

Alluxio Monthly Webinar May. 14, 2024 For more Alluxio Events: https://www.alluxio.io/events/ Speaker: - ChanChan Mao (Developer Advocate, Alluxio) - Bin Fan (VP of Technology, Alluxio) Running AI/ML workloads in different clouds present unique challenges. The key to a manageable multi-cloud architecture is the ability to seamlessly access data across environments with high performance and low cost. This webinar is designed for data platform engineers, data infra engineers, data engineers, and ML engineers who work with multiple data sources in hybrid or multi-cloud environments. Chanchan and Bin will guide the audience through using Alluxio to greatly simplify data access and make model training and serving more efficient in these environments. You will learn: - How to access data in multi-region, hybrid, and multi-cloud like accessing a local file system - How to run PyTorch to read datasets and write checkpoints to remote storage with Alluxio as the distributed data access layer - Real-world examples and insights from tech giants like Uber, AliPay and more

Alluxio Monthly Webinar | Simplify Data Access for AI in Multi-Cloud

Alluxio Monthly Webinar | Simplify Data Access for AI in Multi-Cloud

Alluxio Monthly Webinar | Simplify Data Access for AI in Multi-Cloud

Building a notification campaign might seem easy and it is easy to get started with a simple set up. But once the scale kicks in, it becomes every important to have a resilient architecture that can handle hundreds of thousands of recipients. This talk will focus on the Serverless services consumed in building the architecture and the various architectural decisions. The talk covers the various challenges in building an architecture of this sorts and how we overcame them using Serverless services.

Lessons Learned from Building a Serverless Notifications System.pdf

Lessons Learned from Building a Serverless Notifications System.pdf

Lessons Learned from Building a Serverless Notifications System.pdf

Srushith Repakula

QUICCK 100% in Gauteng/Western Cape *[☎️+27737758557]]@ @# SOWETO@+27737758557 ABORTION PILLS FOR SALE IN STELLENBOSCH CLINIC/WESTERN CAPE cape … CAPE TOWN CLINIC/WESTERN CAPE BELLVILLE LANGA PAROW cape town bellville cape town bellville langa parow khayelitsha gugulethu elies river kraaifontein good wood capetown DR.SINDY +27737758557// abortion clinics// pills WOMEN ABORTION CLINICS PAINFREE,SAFE,QUICCK 100% in western cape +27737758557 Sindy @ABORTION PILLS FOR SALE IN STELLENBOSCH CLINIC/WESTERN CAPE cape … CAPE TOWN CLINIC/WESTERN CAPE BELLVILLE LANGA PAROW cape town bellville cape town bellville langa parow khayelitsha gugulethu elies river kraaifontein good wood capetown bellville.maitland.belhar. aarl, Wellington, Betty’s Bay, Atlantis, Blue Down, Brackenfell, Crossroads, Eerste Rivier, Elsie’s River, Fish Hoek, Goodwood, Gordon’s Bay, Gugulethu,DR EVE +27737758557 // abortion clinics// pills WOMEN ABORTION CLINICS PAINFREE,SAFE,QUICCK 100% in western cape +27737758557 JAULANI@ABORTION PILLS FOR SALE IN STELLENBOSCH CLINIC/WESTERN CAPE cape … CAPE TOWN CLINIC/WESTERN CAPE BELLVILLE LANGA PAROW cape town bellville cape town bellville langa parow khayelitsha gugulethu elies river kraaifontein good wood capetown bellville.maitland.belhar. aarl, Wellington, Betty’s Bay, Atlantis, Blue Down, Brackenfell, Crossroads, Eerste Rivier, Elsie’s River, Fish Hoek, Goodwood, Gordon’s Bay, Gugulethu, Hout Bay, Khayelitsha, Kraainfontein, Kuils River, Langa, Melkbosstrand, Mfuleni, Milnerton, Mitchell’s Plain, Noordhoek, Nyanga, Parow, Kleinmond, Simon’s town, Somerset west, stellenbosch, Ashton Bonnievale Ceres De Doorns Denneburg Franschhoek Gouda Kayamandi Klapmuts Kylemore Languedo cMcGregor Montagu Op-die-Berg Paarl Pniel Prince Alfred Hamlet Rawsonville Robertson Robertsvlei Rozendal Saron Stellenbosch Touws River Tulbagh Wellington Wemmershoek Wolseley Worcester langa parow khayelitsha gugulethu elies river kraaifontein good wood capetown bellville. Ashton Bonnievale Ceres De Doorns Denneburg Franschhoek Gouda Kayamandi Klapmuts Kylemore Languedoc McGregor Montagu Op-die-Berg Paarl Pniel Prince Alfred Hamlet Rawsonville Robertson Robertsvlei Rozendal Saron Stellenbosch Touws River Tulbagh Wellington Alexandra · Diepsloot · Ennerdale ; Alberton · Bedfordview · Benoni ; Atteridgeville · Bronberg · Mogapeng · Mogodumo · Mogwadi · Mohlake · Mohlarekoma · Mohlatsengwane · Mohlopi · Mohlopi · Mohlakeng · Mohwelere · Mokgoatsane · Mokopane. Makhado · Bela-Bela · Hoedspruit · Haenertsburg · Lephalale (Ellisras) · Phalaborwa · Polokwane (Pietersburg) · Tzaneen.Hoedspruit · Hoedspruit. #1 – Hoedspruit ; Haenertsburg · Haenertsburg. #2 – Haenertsburg ; Tzaneen · Tzaneen. Polokwane, Louis Trichardt, Mahwelereng, Giyani, Limpopo,

Abortion Pills For Sale WhatsApp[[+27737758557]] In Birch Acres, Abortion Pil...

Abortion Pills For Sale WhatsApp[[+27737758557]] In Birch Acres, Abortion Pil...

Abortion Pills For Sale WhatsApp[[+27737758557]] In Birch Acres, Abortion Pil...

Test Automation Design Patterns_ A Comprehensive Guide.pdf

Test Automation Design Patterns_ A Comprehensive Guide.pdf

Test Automation Design Patterns_ A Comprehensive Guide.pdf

kalichargn70th171

Workshop 1. Architecting Innovative Graph Applications Join this hands-on workshop for beginners led by Neo4j experts guiding you to systematically uncover contextual intelligence. Using a real-life dataset we will build step-by-step a graph solution; from building the graph data model to running queries and data visualization. The approach will be applicable across multiple use cases and industries.

Workshop - Architecting Innovative Graph Applications- GraphSummit Milan

Workshop - Architecting Innovative Graph Applications- GraphSummit Milan

Workshop - Architecting Innovative Graph Applications- GraphSummit Milan

Transformer Neural Network Use Cases with Links

Transformer Neural Network Use Cases with Links

Transformer Neural Network Use Cases with Links

Abortion Clinic in Midrand [(+27832195400*)]🏥Safe Abortion Pills In Midrand | Abortions Clinic | Quality & Affordable Healthcare Services !! Abortion Clinic Near Me Cost, Price, Women's Clinic Near Me, Abortion Clinic Near, Abortion Doctors Near me, Abortion Services Near Me, Abortion Pills Over The Counter, Abortion Pill Doctors' Offices, Abortion Clinics, Abortion Places Near Me, Cheap Abortion Places Near Me, Medical Abortion & Surgical Abortion, approved cyctotec pills and womb cleaning pills too plus all the instructions needed This Discrete women’s Termination Clinic offers same day services that are safe and pain free, we use approved pills and we clean the womb so that no side effects are present. Our main goal is that of preventing unintended pregnancies and unwanted births every day to enable more women to have children by choice, not chance. We offer Terminations by Pill and The Morning After Pill.” Our Private VIP Abortion Service offers the ultimate in privacy, efficiency and discretion. we do safe and same day termination and we do also womb cleaning as well its done from 1 week up to 28 weeks. We do delivery of our services world wide SAFE ABORTION CLINICS/PILLS ON SALE WE DO DELIVERY OF PILLS ALSO Abortion clinic at very low costs, 100% Guaranteed and it’s safe, pain free and a same day service. It Is A 45 Minutes Procedure, we use tested abortion pills and we do womb cleaning as well. Alternatively the medical abortion pill and womb cleansing !!!

Abortion Clinic in Midrand [(+27832195400*)]🏥Safe Abortion Pills In Midrand |...

Abortion Clinic in Midrand [(+27832195400*)]🏥Safe Abortion Pills In Midrand |...

Abortion Clinic in Midrand [(+27832195400*)]🏥Safe Abortion Pills In Midrand |...

Medical / Health Care (+971588192166) Mifepristone and Misoprostol tablets 200mg

Modern binary build systems - PyCon 2024

Modern binary build systems - PyCon 2024

Modern binary build systems - PyCon 2024

Henry Schreiner

Abortion Clinic In Johannesburg ](+27832195400*)[ 🏥 Safe Abortion Pills in Jo...

Abortion Clinic In Johannesburg ](+27832195400*)[ 🏥 Safe Abortion Pills in Jo...

Abortion Clinic In Johannesburg ](+27832195400*)[ 🏥 Safe Abortion Pills in Jo...

Medical / Health Care (+971588192166) Mifepristone and Misoprostol tablets 200mg

These are the slides of my OpenSIPS Summit 2024 presentation about automating your test calls. It dives into why automated call testing is crucial, how to integrate it into your CI/CD pipeline and how to extend testing of single calls into load testing and testing of other protocols. The presentation also provides details how open source components such as sipp, asterisk and rtpengine are used to implement agents to generate test calls for SIP, Fax and WebRTC at scale.

Automate your OpenSIPS config tests - OpenSIPS Summit 2024

Automate your OpenSIPS config tests - OpenSIPS Summit 2024

Automate your OpenSIPS config tests - OpenSIPS Summit 2024

Abortion Pill Prices Mthatha (@](+27832195400*)[ 🏥 Women's Abortion Clinic In...

Abortion Pill Prices Mthatha (@](+27832195400*)[ 🏥 Women's Abortion Clinic In...

Abortion Pill Prices Mthatha (@](+27832195400*)[ 🏥 Women's Abortion Clinic In...

Medical / Health Care (+971588192166) Mifepristone and Misoprostol tablets 200mg

Recently uploaded (20)

Abortion Clinic In Pretoria ](+27832195400*)[ 🏥 Safe Abortion Pills in Pretor...

Abortion Clinic In Pretoria ](+27832195400*)[ 🏥 Safe Abortion Pills in Pretor...

Abortion Clinic In Pretoria ](+27832195400*)[ 🏥 Safe Abortion Pills in Pretor...

Wired_2.0_CREATE YOUR ULTIMATE LEARNING ENVIRONMENT_JCON_16052024

Wired_2.0_CREATE YOUR ULTIMATE LEARNING ENVIRONMENT_JCON_16052024

Wired_2.0_CREATE YOUR ULTIMATE LEARNING ENVIRONMENT_JCON_16052024

Team Transformation Tactics for Holistic Testing and Quality (NewCrafts Paris...

Team Transformation Tactics for Holistic Testing and Quality (NewCrafts Paris...

Team Transformation Tactics for Holistic Testing and Quality (NewCrafts Paris...

Abortion Pill Prices Jane Furse ](+27832195400*)[🏥Women's Abortion Clinic in ...

Abortion Pill Prices Jane Furse ](+27832195400*)[🏥Women's Abortion Clinic in ...

Abortion Pill Prices Jane Furse ](+27832195400*)[🏥Women's Abortion Clinic in ...

AzureNativeQumulo_HPC_Cloud_Native_Benchmarks.pdf

AzureNativeQumulo_HPC_Cloud_Native_Benchmarks.pdf

AzureNativeQumulo_HPC_Cloud_Native_Benchmarks.pdf

Evolving Data Governance for the Real-time Streaming and AI Era

Evolving Data Governance for the Real-time Streaming and AI Era

Evolving Data Governance for the Real-time Streaming and AI Era

GraphSummit Milan - Visione e roadmap del prodotto Neo4j

GraphSummit Milan - Visione e roadmap del prodotto Neo4j

GraphSummit Milan - Visione e roadmap del prodotto Neo4j

Abortion Pill Prices Polokwane ](+27832195400*)[ 🏥 Women's Abortion Clinic in...

Abortion Pill Prices Polokwane ](+27832195400*)[ 🏥 Women's Abortion Clinic in...

Abortion Pill Prices Polokwane ](+27832195400*)[ 🏥 Women's Abortion Clinic in...

Weeding your micro service landscape.pdf

Weeding your micro service landscape.pdf

Weeding your micro service landscape.pdf

Alluxio Monthly Webinar | Simplify Data Access for AI in Multi-Cloud

Alluxio Monthly Webinar | Simplify Data Access for AI in Multi-Cloud

Alluxio Monthly Webinar | Simplify Data Access for AI in Multi-Cloud

Lessons Learned from Building a Serverless Notifications System.pdf

Lessons Learned from Building a Serverless Notifications System.pdf

Lessons Learned from Building a Serverless Notifications System.pdf

Abortion Pills For Sale WhatsApp[[+27737758557]] In Birch Acres, Abortion Pil...

Abortion Pills For Sale WhatsApp[[+27737758557]] In Birch Acres, Abortion Pil...

Abortion Pills For Sale WhatsApp[[+27737758557]] In Birch Acres, Abortion Pil...

Test Automation Design Patterns_ A Comprehensive Guide.pdf

Test Automation Design Patterns_ A Comprehensive Guide.pdf

Test Automation Design Patterns_ A Comprehensive Guide.pdf

Workshop - Architecting Innovative Graph Applications- GraphSummit Milan

Workshop - Architecting Innovative Graph Applications- GraphSummit Milan

Workshop - Architecting Innovative Graph Applications- GraphSummit Milan

Transformer Neural Network Use Cases with Links

Transformer Neural Network Use Cases with Links

Transformer Neural Network Use Cases with Links

Abortion Clinic in Midrand [(+27832195400*)]🏥Safe Abortion Pills In Midrand |...

Abortion Clinic in Midrand [(+27832195400*)]🏥Safe Abortion Pills In Midrand |...

Abortion Clinic in Midrand [(+27832195400*)]🏥Safe Abortion Pills In Midrand |...

Modern binary build systems - PyCon 2024

Modern binary build systems - PyCon 2024

Modern binary build systems - PyCon 2024

Abortion Clinic In Johannesburg ](+27832195400*)[ 🏥 Safe Abortion Pills in Jo...

Abortion Clinic In Johannesburg ](+27832195400*)[ 🏥 Safe Abortion Pills in Jo...

Abortion Clinic In Johannesburg ](+27832195400*)[ 🏥 Safe Abortion Pills in Jo...

Automate your OpenSIPS config tests - OpenSIPS Summit 2024

Automate your OpenSIPS config tests - OpenSIPS Summit 2024

Automate your OpenSIPS config tests - OpenSIPS Summit 2024

Abortion Pill Prices Mthatha (@](+27832195400*)[ 🏥 Women's Abortion Clinic In...

Abortion Pill Prices Mthatha (@](+27832195400*)[ 🏥 Women's Abortion Clinic In...

Abortion Pill Prices Mthatha (@](+27832195400*)[ 🏥 Women's Abortion Clinic In...

Normalization

1. Normalizati on

2. “ ⊷ Group Members 2 1. P.P.P.Madhushani 2. G.G.A.R.U.Gunasekara 3. N.H.B.Pethiyagoda 4. Ayesha Vidyani

3. Normalization ⊷ Database Normalization is a technique of organizing the data in the database. Normalization is a systematic approach of decomposing tables to eliminate data redundancy(repetition) and undesirable characteristics like Insertion, Update and Deletion Anamolies. It is a multi-step process that puts data into tabular form, removing duplicated data from the relation tables. Normalization is used for mainly two purposes, ⊷ Eliminating redundant (useless) data. ⊷ Ensuring data dependencies make sense i.e. data is logically stored. 3

4. “ Data Redundancy occurs when the same data is entered in to two or more fields of a database. 4 Difference Between Duplication and Redundancy Data Duplication occurs when an exact copy of a piece of data is created.

5. “ 5 Aims of Normalization

6. Problems Without Normalization 6

7. There are 3 problems that can occur without Normalization 7 ⊷ 1. Insert Anomaly ⊷ 2. Delete Anomaly ⊷ 3. Update Anomaly

8. Stages of Normalization 8 ⊷ First Normal Form ⊷ Second Normal Form ⊷ Third Normal Form ⊷ BCNF ⊷ Fourth Normal Form

9. First Normal Form 9 A table is in it’s first normal form if it contains no repeating attributes or groups of attributes.

12. Second Normal Form 12 A table is in the second normal form AND no column that is not part of the primary key is dependant only a portion of the Primary Key.

15. Third Normal Form 15 A table is in the third normal form if it is in the second normal form. And there are no non-key columns dependant on other non-key columns that could not act as the primary key.

18. Thank You 18