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Introduction to data mining and architecture  in hindi
 
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#datamining #datawarehouse #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 211764 Last moment tuitions
Last Minute Tutorials | Data mining | Introduction | Examples
 
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Views: 44411 Last Minute Tutorials
KDD ( knowledge data discovery )  in data mining in hindi
 
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#kdd #datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 71741 Last moment tuitions
How data mining works
 
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In this video we describe data mining, in the context of knowledge discovery in databases. More videos on classification algorithms can be found at https://www.youtube.com/playlist?list=PLXMKI02h3_qjYoX-f8uKrcGqYmaqdAtq5 Please subscribe to my channel, and share this video with your peers!
Views: 228925 Thales Sehn Körting
Introduction to Datawarehouse in hindi | Data warehouse and data mining Lectures
 
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#datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 283951 Last moment tuitions
INTRODUCTION TO DATA MINING IN HINDI
 
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Views: 110961 LearnEveryone
INTRODUCTION TO DATA MINING
 
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INTRODUCTION TO DATA MINING
Views: 17470 LearnEveryone
What is Data Mining?
 
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NJIT School of Management professor Stephan P Kudyba describes what data mining is and how it is being used in the business world.
Views: 415633 YouTube NJIT
Part 1.3 | Olap vs Oltp in hindi | online analytical processing online transaction processing
 
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DBMS olap vs oltp,olap vs oltp with example,olap vs oltp in hindi,olap vs oltp in data warehouse,olap vs oltp difference,olap vs oltp databases,olap vs oltp in sql server,olap vs oltp youtube,online analytical processing in hindi,online analytical processing definition,online analytical processing example,online transaction processing in hindi,online transaction processing example,online transaction processing steps olap vs oltp,olap vs oltp with example,olap vs oltp in hindi,olap vs oltp in data warehouse,olap vs oltp difference,olap vs oltp databases,olap vs oltp in sql server,olap vs oltp youtube,online analytical processing in hindi,online analytical processing definition,online analytical processing example,online transaction processing in hindi,online transaction processing example,online transaction processing steps olap vs oltp,olap vs oltp with example,olap vs oltp in hindi,olap vs oltp in data warehouse,olap vs oltp difference,olap vs oltp databases,olap vs oltp in sql server,olap vs oltp youtube,online analytical processing in hindi,online analytical processing definition,online analytical processing example,online transaction processing in hindi,online transaction processing example,online transaction processing stepsolap vs oltp,olap vs oltp with example,olap vs oltp in hindi,olap vs oltp in data warehouse,olap vs oltp difference,olap vs oltp databases,olap vs oltp in sql server,olap vs oltp youtube,online analytical processing in hindi,online analytical processing definition,online analytical processing example,online transaction processing in hindi,online transaction processing example,online transaction processing stepsolap vs oltp,olap vs oltp with example,olap vs oltp in hindi,olap vs oltp in data warehouse,olap vs oltp difference,olap vs oltp databases,olap vs oltp in sql server,olap vs oltp youtube,online analytical processing in hindi,online analytical processing definition,online analytical processing example,online transaction processing in hindi,online transaction processing example,online transaction processing stepsolap vs oltp,olap vs oltp with example,olap vs oltp in hindi,olap vs oltp in data warehouse,olap vs oltp difference,olap vs oltp databases,olap vs oltp in sql server,olap vs oltp youtube,online analytical processing in hindi,online analytical processing definition,online analytical processing example,online transaction processing in hindi,online transaction processing example,online transaction processing stepsolap vs oltp,olap vs oltp with example,olap vs oltp in hindi,olap vs oltp in data warehouse,olap vs oltp difference,olap vs oltp databases,olap vs oltp in sql server,olap vs oltp youtube,online analytical processing in hindi,online analytical processing definition,online analytical processing example,online transaction processing in hindi,online transaction processing example,online transaction processing steps
Views: 69927 KNOWLEDGE GATE
What is DATA MINING? What does DATA MINING mean? DATA MINING meaning, definition & explanation
 
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What is DATA MINING? What does DATA MINING mean? DATA MINING meaning - DATA MINING definition - DATA MINING explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. Data mining is an interdisciplinary subfield of computer science. It is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD. The term is a misnomer, because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction (mining) of data itself. It also is a buzzword and is frequently applied to any form of large-scale data or information processing (collection, extraction, warehousing, analysis, and statistics) as well as any application of computer decision support system, including artificial intelligence, machine learning, and business intelligence. The book Data mining: Practical machine learning tools and techniques with Java (which covers mostly machine learning material) was originally to be named just Practical machine learning, and the term data mining was only added for marketing reasons. Often the more general terms (large scale) data analysis and analytics – or, when referring to actual methods, artificial intelligence and machine learning – are more appropriate. The actual data mining task is the automatic or semi-automatic analysis of large quantities of data to extract previously unknown, interesting patterns such as groups of data records (cluster analysis), unusual records (anomaly detection), and dependencies (association rule mining). This usually involves using database techniques such as spatial indices. These patterns can then be seen as a kind of summary of the input data, and may be used in further analysis or, for example, in machine learning and predictive analytics. For example, the data mining step might identify multiple groups in the data, which can then be used to obtain more accurate prediction results by a decision support system. Neither the data collection, data preparation, nor result interpretation and reporting is part of the data mining step, but do belong to the overall KDD process as additional steps. The related terms data dredging, data fishing, and data snooping refer to the use of data mining methods to sample parts of a larger population data set that are (or may be) too small for reliable statistical inferences to be made about the validity of any patterns discovered. These methods can, however, be used in creating new hypotheses to test against the larger data populations.
Views: 7529 The Audiopedia
DATA MINING EXPLAINED IN HINDI | "ITNA SARA DATA??"
 
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नमस्कार दोस्तों,आज की वीडियो में में आप सभी को DATA MINING के बारे में बताने जा रहा हूँ की आखिर DATA MINING क्या होती है और क्या ये हमारे किसी काम आती हैं या नहीं और आखिर हमारे ज़िन्दगी में इसकी कितनी जरुरत है। आशा करता हूँ आपको ये वीडियो पसंद आएगी अगर आपको वीडियो पसंद आये तो वीडियो को LIKE SHARE और चैनल को SUBSCRIBE जरूर से करे। धन्यवाद। जय हिन्द वन्दे मातरम subscribe our channel on youtube: https://www.youtube.com/channel/UCR_kAPwG59SxWRaUfzk3qoQ facebook: https://www.facebook.com/dropouttechnical/ twitter: https://twitter.com/dropoutechnical google+: https://plus.google.com/u/0/103031877017890269380 -~-~~-~~~-~~-~- Please watch: "MOTO X4 my opinion |"Best phone??"|"worth buy at 21000"🔥" https://www.youtube.com/watch?v=r54C6_667uU -~-~~-~~~-~~-~-
Views: 12347 Dropout Technical
What is INFORMATION RETRIEVAL? What does INFORMATION RETRIEVAL mean? INFORMATION RETRIEVAL meaning
 
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✪✪✪✪✪ WORK FROM HOME! Looking for WORKERS for simple Internet data entry JOBS. $15-20 per hour. SIGN UP here - http://jobs.theaudiopedia.com ✪✪✪✪✪ ✪✪✪✪✪ The Audiopedia Android application, INSTALL NOW - https://play.google.com/store/apps/details?id=com.wTheAudiopedia_8069473 ✪✪✪✪✪ What is INFORMATION RETRIEVAL? What does INFORMATION RETRIEVAL mean? INFORMATION RETRIEVAL meaning - INFORMATION RETRIEVAL definition - INFORMATION RETRIEVAL explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. Information retrieval (IR) is the activity of obtaining information resources relevant to an information need from a collection of information resources. Searches can be based on full-text or other content-based indexing. Automated information retrieval systems are used to reduce what has been called "information overload". Many universities and public libraries use IR systems to provide access to books, journals and other documents. Web search engines are the most visible IR applications. An information retrieval process begins when a user enters a query into the system. Queries are formal statements of information needs, for example search strings in web search engines. In information retrieval a query does not uniquely identify a single object in the collection. Instead, several objects may match the query, perhaps with different degrees of relevancy. An object is an entity that is represented by information in a content collection or database. User queries are matched against the database information. However, as opposed to classical SQL queries of a database, in information retrieval the results returned may or may not match the query, so results are typically ranked. This ranking of results is a key difference of information retrieval searching compared to database searching. Depending on the application the data objects may be, for example, text documents, images, audio, mind maps or videos. Often the documents themselves are not kept or stored directly in the IR system, but are instead represented in the system by document surrogates or metadata. Most IR systems compute a numeric score on how well each object in the database matches the query, and rank the objects according to this value. The top ranking objects are then shown to the user. The process may then be iterated if the user wishes to refine the query.
Views: 13611 The Audiopedia
What is Business Intelligence (BI)?
 
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There are many definitions for Business Intelligence, or BI. To put it simply, BI is about delivering relevant and reliable information to the right people at the right time with the goal of achieving better decisions faster. If you wanna have efficient access to accurate, understandable and actionable information on demand, then BI might be right for your organization. For more information, contact Hitachi Solutions Canada (canada.hitachi-solutions.com).
Views: 372234 Hitachi Solutions Canada
What is Data Mining
 
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Small introduction on Data Mining - What is Data Mining Data Mining is a tool to Extract Hidden data.
▶ What is Data, Information, Database and Data Warehouse in Data Mining | Data Mining Tutorial
 
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See Full #Data_Mining Video Series Here: https://youtu.be/t8lSMGW5eT0 In This Video You are gonna learn What is Data? What is Information? What is Database? What is Data Warehouse? »See Full #Data_Mining Video Series Here: https://youtu.be/t8lSMGW5eT0 In This Video You are gonna learn Data Mining #Bangla_Tutorial Data mining is an important process to discover knowledge about your customer behavior towards your business offerings. » My #Linkedin_Profile: https://www.linkedin.com/in/rafayet13 » Read My Full Article on #Data_Mining Career Opportunity & So On » Link: https://medium.com/@rafayet13 ডেটা শব্দটি ল্যাটিন শব্দ ডেটাম এর বহুবচন। যার বাংলায় অর্থ দাঁড়ায় উপাত্ব। নাম্বার, লেটার, সিম্বল সবকিছুই ডেটা। ডেটাকে প্রসেস করলে যা পাওয়া যায় তা-ই মুলত ইনফরমেশন। ডেটা যেখানে রাখা হয় তাকেই ডেটাবেজ বলে। সাধারণত ডেটাবেজে টেবিল, কলাম , রো এর সাহায্যে অরগেনাইজড অবস্থায় ডেটা রাখা হয় । কয়েকটি ছোট ছোট ডেটাবেজ মিলে একটি ডেটা ওয়্যারহাউজ তৈরি করা হয়।
Views: 2000 BookBd
Data Warehousing and Data Mining
 
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This course aims to introduce advanced database concepts such as data warehousing, data mining techniques, clustering, classifications and its real time applications. SlideTalk video created by SlideTalk at http://slidetalk.net, the online solution to convert powerpoint to video with automatic voice over.
Views: 4694 SlideTalk
data mining task
 
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Views: 3915 Sailaja NV
Data Mining, Classification, Clustering, Association Rules, Regression, Deviation
 
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Complete set of Video Lessons and Notes available only at http://www.studyyaar.com/index.php/module/20-data-warehousing-and-mining Data Mining, Classification, Clustering, Association Rules, Sequential Pattern Discovery, Regression, Deviation http://www.studyyaar.com/index.php/module-video/watch/53-data-mining
Views: 88089 StudyYaar.com
Decision Tree with Solved Example in English | DWM | ML | BDA
 
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Take the Full Course of Artificial Intelligence What we Provide 1) 28 Videos (Index is given down) 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in Artificial Intelligence Sample Notes : https://goo.gl/aZtqjh To buy the course click https://goo.gl/H5QdDU if you have any query related to buying the course feel free to email us : [email protected] Other free Courses Available : Python : https://goo.gl/2gftZ3 SQL : https://goo.gl/VXR5GX Arduino : https://goo.gl/fG5eqk Raspberry pie : https://goo.gl/1XMPxt Artificial Intelligence Index 1)Agent and Peas Description 2)Types of agent 3)Learning Agent 4)Breadth first search 5)Depth first search 6)Iterative depth first search 7)Hill climbing 8)Min max 9)Alpha beta pruning 10)A* sums 11)Genetic Algorithm 12)Genetic Algorithm MAXONE Example 13)Propsotional Logic 14)PL to CNF basics 15) First order logic solved Example 16)Resolution tree sum part 1 17)Resolution tree Sum part 2 18)Decision tree( ID3) 19)Expert system 20) WUMPUS World 21)Natural Language Processing 22) Bayesian belief Network toothache and Cavity sum 23) Supervised and Unsupervised Learning 24) Hill Climbing Algorithm 26) Heuristic Function (Block world + 8 puzzle ) 27) Partial Order Planing 28) GBFS Solved Example
Views: 224268 Last moment tuitions
Data Mining  Association Rule - Basic Concepts
 
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short introduction on Association Rule with definition & Example, are explained. Association rules are if/then statements used to find relationship between unrelated data in information repository or relational database. Parts of Association rule is explained with 2 measurements support and confidence. types of association rule such as single dimensional Association Rule,Multi dimensional Association rules and Hybrid Association rules are explained with Examples. Names of Association rule algorithm and fields where association rule is used is also mentioned.
Data Mining Classification and Prediction ( in Hindi)
 
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A tutorial about classification and prediction in Data Mining .
Views: 31836 Red Apple Tutorials
Data Mining - Clustering
 
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What is clustering Partitioning a data into subclasses. Grouping similar objects. Partitioning the data based on similarity. Eg:Library. Clustering Types Partitioning Method Hierarchical Method Agglomerative Method Divisive Method Density Based Method Model based Method Constraint based Method These are clustering Methods or types. Clustering Algorithms,Clustering Applications and Examples are also Explained.
Data Mining Lecture -- Decision Tree | Solved Example (Eng-Hindi)
 
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Views: 180566 Well Academy
Part 1.1| DATA INFORMATION DATA BASE DATA BASE MANAGEMENT SYSTEM definition difference what
 
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Views: 64147 KNOWLEDGE GATE
Data warehouse Features Lecture in Hindi - DWDM Lectures in Hindi, English
 
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Data warehouse Features Lecture in Hindi - DWDM Lectures in Hindi, English Data warehouse Features – Subject Oriented, Integrated, Time Variant, Non-Volatile Data, Data Granularity Data Warehouse and Data Mining Lectures in Hindi
ETL ( Extract Transform Load )   process fully explained  in hindi | Datawarehouse
 
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#etl #datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 61001 Last moment tuitions
Meta data  in 5 mins hindi
 
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#metadata #datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 108904 Last moment tuitions
OLAP vs OLTP in hindi
 
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#olap #oltp #datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 111955 Last moment tuitions
Data- What is the Importance of DATA in Tamil?
 
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Data is collection of information . Data store and Data process Play List : https://www.youtube.com/playlist?list=PLLa_h7BriLH2U05m3eN43779AnrmieYHz YouTube channel link www.youtube.com/atozknowledgevideos Website http://atozknowledge.com/ Technology in Tamil & English
Views: 18124 atoz knowledge
Data Warehouse Architecture In Data Mining And Warehousing Explained In Hindi
 
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📚📚📚📚📚📚📚📚 GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING 🎓🎓🎓🎓🎓🎓🎓🎓 SUBJECT :- Artificial Intelligence(AI) Database Management System(DBMS) Software Modeling and Designing(SMD) Software Engineering and Project Planning(SEPM) Data mining and Warehouse(DMW) Data analytics(DA) Mobile Communication(MC) Computer networks(CN) High performance Computing(HPC) Operating system System programming (SPOS) Web technology(WT) Internet of things(IOT) Design and analysis of algorithm(DAA) 💡💡💡💡💡💡💡💡 EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. 💡💡💡💡💡💡💡💡 THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING 📚📚📚📚📚📚📚📚
Views: 18140 5 Minutes Engineering
Data Processing Cycle
 
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Views: 33707 Julia Qistina
What is Definition of Database, DBMS, Objectives of Database, Data Integration, Data Integrity
 
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What is Definition of Database, DBMS, Objectives of Database, Data Integration, Data Integrity, Data Interdependence Data Basics ICS II (Computer Science) Chapter 1 Lecture 6
What is OLAP?
 
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This video explores some of OLAP's history, and where this solution might be applicable. We also look at situations where OLAP might not be a fit. Additionally, we investigate an alternative/complement called a Relational Dimensional Model. To Talk with a Specialist go to: http://www.intricity.com/intricity101/
Views: 372234 Intricity101
Steps of  Data Processing ? Explained in  Hindi
 
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Steps of Data Processing ? Explained in Hindi Computer knowledge for MP Patwari 2017, IBPS PO 2017, SBI PO 2017, SBI SO 2017,RRB, RBI ASSISTANT 2017, CPCT
Views: 41207 Spardha Gyan
Generalization | Database Management System
 
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This lecture describes the concept of Generalization as an enhanced feature of ER model. To ask your doubts on this topic and much more, click on this Direct Link: http://www.techtud.com/video-lecture/lecture-generalization IMPORTANT LINKS: 1) Official Website: http://www.techtud.com/ 2) Virtual GATE(for 'All India Test Series for GATE-2016'): http://virtualgate.in/login/index.php Both of the above mentioned platforms are COMPLETELY FREE, so feel free to Explore, Learn, Practice & Share! Our Social Media Links: Facebook Page: https://www.facebook.com/techtuduniversity Facebook Group: https://www.facebook.com/groups/virtualgate/ Google+ Page: https://plus.google.com/+techtud/posts Last but not the least, SUBSCRIBE our YouTube channel to stay updated about our regularly uploaded new videos.
Views: 53190 Techtud
Aggregation | Database Management System
 
07:11
This lecture explains the concept of Aggregation in enhanced ER model. To ask your doubts on this topic and much more, click on this Direct Link: http://www.techtud.com/video-lecture/lecture-aggregation IMPORTANT LINKS: 1) Official Website: http://www.techtud.com/ 2) Virtual GATE(for 'All India Test Series for GATE-2016'): http://virtualgate.in/login/index.php Both of the above mentioned platforms are COMPLETELY FREE, so feel free to Explore, Learn, Practice & Share! Our Social Media Links: Facebook Page: https://www.facebook.com/techtuduniversity Facebook Group: https://www.facebook.com/groups/virtualgate/ Google+ Page: https://plus.google.com/+techtud/posts Last but not the least, SUBSCRIBE our YouTube channel to stay updated about our regularly uploaded new videos.
Views: 64177 Techtud
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Warehousing | Edureka
 
01:38:50
** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ** This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial: 1. What Is The Need For BI? 2. What Is Data Warehousing? 3. Key Terminologies Related To DWH Architecture: a. OLTP Vs OLAP b. ETL c. Data Mart d. Metadata 4. DWH Architecture 5. Demo: Creating A DWH - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Intelligence playlist here: https://goo.gl/DZEuZt. #DataWarehousing #DataWarehouseTutorial #DataWarehouseTraining Subscribe to our channel to get video updates. Hit the subscribe button above. - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 25 hours of assignment and 10 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course: Edureka's Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 238006 edureka!
K mean clustering algorithm with solve example
 
12:13
#kmean datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 352294 Last moment tuitions
Introduction to Distributed Database in Hindi  | DDB tutorials #1
 
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In this video we have explain the basic concept of distributed database in simple way with advantages and promises of distributed database and also explain the difference between centralize and distributed database visit our website for full course www.lastmomenttuitions.com NOTES: https://lastmomenttuitions.com/how-to-buy-notes/ NOTES FORM : https://goo.gl/1aQtNc Introduction to Distributed Database : https://goo.gl/JHdpz8 Design Issues in Distributed database : https://goo.gl/aHFe8k Architectures in Distributed database : https://goo.gl/ETL5Ku Fragmentation and correctness rules : https://goo.gl/nbhq5T Horizontal fragmentation : https://goo.gl/N1rvgR Vertical fragmentation : https://goo.gl/tmNxY8 Derived horizontal fragmentation : https://goo.gl/LJ7cvV Query processing cost : https://goo.gl/uUL9de Concurrency Control Protocol : https://goo.gl/XC6oc9 Locking Based Concurrency : https://goo.gl/nrCctM Dead Lock and its Prevention Techniques : https://goo.gl/Nm7Gr6 Dead Lock Detection Method : https://goo.gl/yZxue8 Two Phase commit Protocol: https://goo.gl/6fjYrM Three Phase commit protocol : https://goo.gl/bbFHqV Phases of Distributed Query Processing : https://goo.gl/zUetvK whatsapp: 7038604912 more videos coming soon subscribe karke rakho tab tak
Views: 46669 Last moment tuitions
Temporal Database in Hindi
 
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A temporal database is a database with built-in support for handling data involving time, being related to the slowly changing dimension concept, for example a temporal data model and a temporal version of Structured Query Language (SQL). More specifically the temporal aspects usually include valid time and transaction time. These attributes can be combined to form bitemporal data. Valid time is the time period during which a fact is true in the real world. Transaction time is the time period during which a fact stored in the database was known. Bitemporal data combines both Valid and Transaction Time. It is possible to have timelines other than Valid Time and Transaction Time, such as Decision Time, in the database. In that case the database is called a multitemporal database as opposed to a bitemporal database. However, this approach introduces additional complexities such as dealing with the validity of (foreign) keys. Temporal databases are in contrast to current databases (at term that doesn't mean, currently available databases, some do have temporal features, see also below), which store only facts which are believed to be true at the current time. Temporal databases supports System-maintained transaction time. With the development of SQL and its attendant use in real-life applications, database users realized that when they added date columns to key fields, some issues arose. For example, if a table has a primary key and some attributes, adding a date to the primary key to track historical changes can lead to creation of more rows than intended. Deletes must also be handled differently when rows are tracked in this way. In 1992, this issue was recognized but standard database theory was not yet up to resolving this issue, and neither was the then-newly formalized SQL-92 standard. Richard Snodgrass proposed in 1992 that temporal extensions to SQL be developed by the temporal database community. In response to this proposal, a committee was formed to design extensions to the 1992 edition of the SQL standard (ANSI X3.135.-1992 and ISO/IEC 9075:1992); those extensions, known as TSQL2, were developed during 1993 by this committee.[3] In late 1993, Snodgrass presented this work to the group responsible for the American National Standard for Database Language SQL, ANSI Technical Committee X3H2 (now known as NCITS H2). The preliminary language specification appeared in the March 1994 ACM SIGMOD Record. Based on responses to that specification, changes were made to the language, and the definitive version of the TSQL2 Language Specification was published in September, 1994[4] An attempt was made to incorporate parts of TSQL2 into the new SQL standard SQL:1999, called SQL3. Parts of TSQL2 were included in a new substandard of SQL3, ISO/IEC 9075-7, called SQL/Temporal.[3] The TSQL2 approach was heavily criticized by Chris Date and Hugh Darwen.[5] The ISO project responsible for temporal support was canceled near the end of 2001. As of December 2011, ISO/IEC 9075, Database Language SQL:2011 Part 2: SQL/Foundation included clauses in table definitions to define "application-time period tables" (valid time tables), "system-versioned tables" (transaction time tables) and "system-versioned application-time period tables" (bitemporal tables). A substantive difference between the TSQL2 proposal and what was adopted in SQL:2011 is that there are no hidden columns in the SQL:2011 treatment, nor does it have a new data type for intervals; instead two date or timestamp columns can be bound together using a PERIOD FOR declaration. Another difference is replacement of the controversial (prefix) statement modifiers from TSQL2 with a set of temporal predicates. For illustration, consider the following short biography of a fictional man, John Doe: John Doe was born on April 3, 1975 in the Kids Hospital of Medicine County, as son of Jack Doe and Jane Doe who lived in Smallville. Jack Doe proudly registered the birth of his first-born on April 4, 1975 at the Smallville City Hall. John grew up as a joyful boy, turned out to be a brilliant student and graduated with honors in 1993. After graduation he went to live on his own in Bigtown. Although he moved out on August 26, 1994, he forgot to register the change of address officially. It was only at the turn of the seasons that his mother reminded him that he had to register, which he did a few days later on December 27, 1994. Although John had a promising future, his story ends tragically. John Doe was accidentally hit by a truck on April 1, 2001. The coroner reported his date of death on the very same day.
Views: 11631 Introtuts
Data Mining Lecture - - Finding frequent item sets | Apriori Algorithm | Solved Example (Eng-Hindi)
 
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In this video Apriori algorithm is explained in easy way in data mining Thank you for watching share with your friends Follow on : Facebook : https://www.facebook.com/wellacademy/ Instagram : https://instagram.com/well_academy Twitter : https://twitter.com/well_academy data mining in hindi, Finding frequent item sets, data mining, data mining algorithms in hindi, data mining lecture, data mining tools, data mining tutorial,
Views: 210500 Well Academy
transaction management in dbms tutorial | DBMS
 
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DBMS transaction management -select -insert -update
Views: 15832 Education 4u
L1: Data Warehousing and Data Mining |Introduction to Warehousing| What is Mining| Tutorial in Hindi
 
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Join My official Whatsapp group by following link https://chat.whatsapp.com/F9XFi6QYFYOGA9JGw4gc1o L1: Data Warehousing and Data Mining | What is Warehousing| What is Mining| Tutorial in Hindi Namaskar, In the Today's lecture i will cover Introduction to Data Warehousing and Data Mining of subject Data Warehousing and Data Mining which is one of the important subject of computer science and engineering Syllabus Unit1: Data Warehousing: Overview, Definition, Data Warehousing Components, Building a Data Warehouse, Warehouse Database, Mapping the Data Warehouse to a Multiprocessor Architecture, Difference between Database System and Data Warehouse, Multi Dimensional Data Model, Data Cubes, Stars, Snow Flakes, Fact Constellations, Concept. Unit 2: Data Warehouse Process and Technology: Warehousing Strategy, Warehouse /management and Support Processes, Warehouse Planning and Implementation, Hardware and Operating Systems for Data Warehousing, Client/Server Computing Model & Data Warehousing. Parallel Processors & Cluster Systems, Distributed DBMS implementations, Warehousing Software, Warehouse Schema Design. Unit 3: Data Mining: Overview, Motivation, Definition & Functionalities, Data Processing, Form of Data Pre-processing, Data Cleaning: Missing Values, Noisy Data, (Binning, Clustering, Regression, Computer and Human inspection), Inconsistent Data, Data Integration and Transformation. Data Reduction:-Data Cube Aggregation, Dimensionality reduction, Data Compression, Numerosity Reduction, Discretization and Concept hierarchy generation, Decision Tree. Unit 4: Classification: Definition, Data Generalization, Analytical Characterization, Analysis of attribute relevance, Mining Class comparisons, Statistical measures in large Databases, Statistical-Based Algorithms, Distance-Based Algorithms, Decision Tree-Based Algorithms. Clustering: Introduction, Similarity and Distance Measures, Hierarchical and Partitional Algorithms. Hierarchical Clustering- CURE and Chameleon. Density Based Methods-DBSCAN, OPTICS. Grid Based Methods- STING, CLIQUE. Model Based Method –Statistical Approach, Association rules: Introduction, Large Item sets, Basic Algorithms, Parallel and Distributed Algorithms, Neural Network approach. Unit 5: Data Visualization and Overall Perspective: Aggregation, Historical information, Query Facility, OLAP function and Tools. OLAP Servers, ROLAP, MOLAP, HOLAP, Data Mining interface, Security, Backup and Recovery, Tuning Data Warehouse, Testing Data Warehouse. Warehousing applications and Recent Trends: Types of Warehousing Applications, Web Mining, Spatial Mining and Temporal Mining I am Sandeep Vishwakarma (www.universityacademy.in) from Raj Kumar Goel Institute of Technology Ghaziabad. I have started a YouTube Channel Namely “University Academy” Teaching Training and Informative. On This channel am providing following services. 1 . Teaching: Video Lecture of B.Tech./ M.Tech. Technical Subject who provide you deep knowledge of particular subject. Compiler Design: https://www.youtube.com/playlist?list=PL-JvKqQx2Ate5DWhppx-MUOtGNA4S3spT Principle of Programming Language: https://www.youtube.com/playlist?list=PL-JvKqQx2AtdIkEFDrqsHyKWzb5PWniI1 Theory of Automata and Formal Language: https://www.youtube.com/playlist?list=PL-JvKqQx2AtdhlS7j6jFoEnxmUEEsH9KH 2. Training: Video Playlist of Some software course like Android, Hadoop, Big Data, IoT, R programming, Python, C programming, Java etc. Android App Development: https://www.youtube.com/playlist?list=PL-JvKqQx2AtdBj8aS-3WCVgfQ3LJFiqIr 3. Informative: On this Section we provide video on deep knowledge of upcoming technology, Innovation, tech news and other informative. Tech News: https://www.youtube.com/playlist?list=PL-JvKqQx2AtdFG5kMueyK5DZvGzG615ks Other: https://www.youtube.com/playlist?list=PL-JvKqQx2AtfQWfBddeH_zVp2fK4V5orf Download You Can Download All Video Lecture, Lecture Notes, Lab Manuals and Many More from my Website: http://www.universityacademy.in/ Regards University Academy UniversityAcademy Website: http://www.universityacademy.in/ YouTube: https://www.youtube.com/c/UniversityAcademy Facebook: https://www.facebook.com/UniversityAcademyOfficial Twitter https://twitter.com/UniAcadofficial Instagram https://www.instagram.com/universityacademyofficial Google+: https://plus.google.com/+UniversityAcademy
Views: 850 University Academy
Query Processing & Optimization Introduction | Query Processing Steps | Query Blocks
 
15:36
Query Processing & Optimization Introduction | Query Processing Steps | Query Blocks Like Us on Facebook - https://www.facebook.com/Easy-Engineering-Classes-346838485669475/ DBMS Hindi Classes Database Management System Tutorial for Beginners in Hindi Database Management System Study Notes DBMS Notes Database Management System Notes
INTRODUCTION TO TEXT MINING IN HINDI
 
10:34
find relevant notes at-https://viden.io/
Views: 8678 LearnEveryone
Last Minute Tutorials | Market basket analysis | Support and Confidence
 
08:44
Please feel free to get in touch with me :) If it helped you, please like my facebook page and don't forget to subscribe to Last Minute Tutorials. Thaaank Youuu. Facebook: https://www.facebook.com/Last-Minute-Tutorials-862868223868621/ Website: www.lmtutorials.com For any queries or suggestions, kindly mail at: [email protected]
Views: 34367 Last Minute Tutorials
What is Text Mining?
 
01:49
An introduction to the basics of text and data mining. To learn more about text mining, view the video "How does Text Mining Work?" here: https://youtu.be/xxqrIZyKKuk
Views: 52293 Elsevier
Extended ER Features, Generalization, Specialization, Aggregation in DBMS with Example
 
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DBMS Tutorial in Hindi, English - Extended ER Features, Generalization, Specialization, Aggregation in DBMS with Example for students of IP University Delhi and Other Universities, Engineering, MCA, BCA, B.Sc, M.Sc Colleges.