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Data Warehouse Architecture In Data Mining And Warehousing Explained In Hindi
 
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πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“ 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) πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™ YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š
Views: 18504 5 Minutes Engineering
2 - Data warehouse Architecture  Overview
 
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A quick video to understand standard Datawarehouse architecture. It consists of following layers 1. Data Source layer 2. ETL 3. Staging Area 4. Datawarehouse - Metadata, Summary and Raw Data 5. OLAP, Reporting and Data Mining Data warehouse is populated from multiple sources for an organisation. All these source system comes under Data Source layer. Some of the source systems are listed below: 1. Operations Systems -- such as Sales, HR, Inventory relational database. 2. ERP (SAP) and CRM (SalesForce.com) Systems. 3. Web server logs and Internal market research data. 4. Third-party data - such as census data, demographics data, or survey data. ETL Tools: Talend Open Studio, Jaspersoft ETL, Ab initio, Informatica, Datastage, Clover ETL, Pentaho ETL, Kettle For more details visit http://www.vikramtakkar.com/2015/09/data-warehouse-architecture-overview.html Datawarehouse Playlist: https://www.youtube.com/playlist?list=PLJ4bGndMaa8FV7nrvKXeHCLRMmIXVCyOG
Views: 90139 Vikram Takkar
Data warehouse Components – 3 Layer Architecture of Data Warehouse with Diagram(Hindi)
 
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Data warehouse Components – 3 Layer Architecture of Data Warehouse with Diagram(Hindi) Data Warehouse and Data Mining Lectures in Hindi
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: 285395 Last moment tuitions
Data Warehousing - An Overview
 
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This video aims to give an overview of data warehousing. It does not delve into the detail - that is for later videos. Here, you will meet Bill Inmon and Ralph Kimball who created the concept and the commercialised it respectively. You then get a quick tour of the basic concepts used in data warehousing.
Views: 346446 Andy Wicks
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Warehousing | Edureka
 
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** 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: 240646 edureka!
Big Data Architecture Patterns
 
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This talk is part of Cerner's Tech Talk series. Check us out at http://engineering.cerner.com/ and @CernerEng This talk focuses on the real world experience on the architectural patterns and tools integrations used to solve real business problems with data. This will be a technical session that covers tools such as Hadoop and NoSQL data stores and how to use them for the right use cases. During the session we will dive into customer architectures and where they have had both successes and failures using a combination of tools to server both OLTP and OLAP workloads. Some of the successes will include large cost reduction in SQL licensing and SAN as well as reduction in overall data warehouse costs including ETL appliances and manpower. The other core focus will be on driving change into businesses and how these customers were able to become leaders or maintain leadership using the data at hand and a set of tools. About the Speaker: Eddie Satterly (@eddie_satterly) is the Chief Big Data Evangelist in the office of the CTO at Splunk. Prior to working at Splunk, he has been in a variety of roles such as engineer, architect, and CTO. Satterly has extensive experience with Apache Cassandra and Apache Hadoop and was named to the Apache Cassandra MVP board in 2012. In addition to his role at Splunk, Satterly serves on the advisory board of two data startups and is a frequent conference speaker.
Views: 155537 CernerEng
Lecture 36 β€” Mining Data Streams | Mining of Massive Datasets | Stanford University
 
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. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "FAIR USE" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. .
Introduction  Distributed Data Mining
 
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Introduction Distributed Data Mining
Views: 319 Online Education
Data Warehouse Concepts | Data Warehouse Tutorial | Data Warehouse Architecture | Edureka
 
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***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** This tutorial on data warehouse concepts will tell you everything you need to know in performing data warehousing and business intelligence. The various data warehouse concepts explained in this video are: 1. What Is Data Warehousing? 2. Data Warehousing Concepts: 3. OLAP (On-Line Analytical Processing) 4. Types Of OLAP Cubes 5. Dimensions, Facts & Measures 6. Data Warehouse Schema - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Inelligence playlist here: https://goo.gl/DZEuZt. #DataWarehousing #DataWarehouseTutorial #DataWarehouseTraining #DataWarehouseConcepts 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: 51801 edureka!
Data Warehouse and Business Intelligence: Systems Architecture and OLTP vs. OLAP
 
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Discuss the basic archietcture for Data Warehouse and Business Intelligence; Compare OLTP vs.OLAP
Views: 121192 minderchen
Data Mining using R | Data Mining Tutorial for Beginners | R Tutorial for Beginners | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R tutorial on "Data Mining using R" will help you understand the core concepts of Data Mining comprehensively. This tutorial will also comprise of a case study using R, where you'll apply data mining operations on a real life data-set and extract information from it. Following are the topics which will be covered in the session: 1. Why Data Mining? 2. What is Data Mining 3. Knowledge Discovery in Database 4. Data Mining Tasks 5. Programming Languages for Data Mining 6. Case study using R Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #LogisticRegression #Datasciencetutorial #Datasciencecourse #datascience How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 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. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with β€˜in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Website: https://www.edureka.co/data-science Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. " Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 70271 edureka!
Introduction to Data Warehousing and Data Mining
 
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The term "Data Warehousing" is now commonly used in industry. It refers to a kind of heterogeneous information system -- one in which the focus is on gathering together the data from the different operational databases within an organization, and making it available for decision making purposes. This unit explains the differences between the type of information one can obtain from a data warehouse compared with a traditional database. We looked at the problems and steps involved in building a data warehouse, and examine some of the techniques that have been proposed for constructing data warehouses. (Chapter 15)
Views: 45304 vcilt14
Olap operations
 
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Olap operations
Views: 27499 IMSUC FLIP
2. What is Domain Driven Design?
 
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Strategic Design Explained: https://youtu.be/Evers5npkmE Tactical Design Explained: https://youtu.be/WZb-FPmiuMY How do you start designing microservices? The answer is Domain Driven Design. In this tutorial, I go through "What is Domain Driven Design?" and high-level overview of what it provides us. Domain Driven Design is well respected in developers community and the best way to start designing a microservices architecture. It's a thought. It's OOP done right. This lecture is a part of crash course on "Mastering the art of designing Microservices Architecture". For full crash course follow: https://goo.gl/qvupqc This crash course is a part of an 8 crash course series called ""Complete Guide To Creating Scalable Backend Infrastructures". The intro to complete series can be found here: https://youtu.be/BLMs_NITgSw Please like, subscribe and share for spreading the love of learning. Follow us on: https://www.facebook.com/getalphacode/ https://twitter.com/helloansh
Views: 42636 Alpha Code
Data Warehousing and Data Mining
 
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Research Project Presentation
Views: 16061 Thanos Caras
Knowledge Discovery From Data (KDD) Process (HINDI)
 
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Hello dosto mera naam hai shridhar mankar aur mein aap Sabka Swagat karta hu 5-minutes engineering channel pe. This channel is launched with a aim to enhance the quality of knowledge of engineering,here I am going to introduce you to every subject of computer engineering like artificial intelligence database management system software modeling and designing Software engineering and project planning data mining and warehouse data analytics Mobile communication Mobile computing Computer networks high performance computing parallel computing Operating system Software programming SPOS web technology internet of things design and analysis of algorithm
Views: 20327 5 Minutes Engineering
Data warehouse and Data mining Important for Comps Mumbai university
 
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Thanks alot to atharva for making this video
Views: 5743 Last moment tuitions
Data Cleaning Process Steps / Phases [Data Mining] Easiest Explanation Ever (Hindi)
 
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πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“ 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) πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™ YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5MINUTES ENGINEERING πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š
Views: 13683 5 Minutes Engineering
ODS database (Operation data Store ), Its properties and purpose explained with examples
 
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Most of the developers can't differentiate between ODS,Data warehouse, Data mart,OLTP systems and Data lakes. This video explains what exactly is an ODS, how is it different from the other systems. What are its properties that make it unique and if you have an ODS or a warehouse in your organisation
Views: 5239 Tech Coach
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: 61383 Last moment tuitions
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: 226898 Last moment tuitions
Data Warehouse in Telugu
 
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ETL and SSIS : https://youtu.be/kWxv9E7g-JM Business Intelligence is a technology based on customer and profit-oriented models that reduce operating costs and provide increased profitability by improving productivity, sales, service and helps to make decision-making capabilities at no time. Business Intelligence Models are based on multidimensional analysis and key performance indicators (KPI) of an enterprise "A data warehouse is a subject oriented, integrated, time variant, a nonvolatile collection of data in support of management's decision-making process". In addition to a relational/multidimensional database, a data warehouse environment often consists of an ETL solution, an OLAP engine, client analysis tools, and other applications that manage the process of gathering data and delivering it to business users. Data Mart - Datamart is a subset of data warehouse and it supports a particular region, business unit or business function. ETL (Extract, Transform and Load) is a process in data warehousing responsible for pulling data out of the source systems and placing it into a data warehouse. ETL and SSIS : https://youtu.be/kWxv9E7g-JM The Online Analytical Processing is designed to answer multi-dimensional queries, whereas the Online Transaction Processing is designed to facilitate and manage the usual business applications. While OLAP is customer-oriented, OLTP is market-oriented. Both OLTP and OLAP are two of the common systems for the management of data. The OLTP is a category of systems that manage transaction processing. OLAP is a compilation of ways to query multi-dimensional databases Tools for Data warehouse: Amazon Redshift Oracle 12c MSBI Informatica Data Validation. QuerySurge. ICEDQ. Datagaps ETL Validator. QualiDI. Talend Open Studio for Data Integration. Codoid's ETL Testing Services. Data Centric Testing.
Views: 5292 Learners Page
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 β€œUniversity 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: 900 University Academy
DW03 : Architecture of data warehouse ||  Data Mining and  Warehouse  || in Hindi
 
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Welcome to our new series i.e. the new subject Data mining And Data warehousing . In this video I will tell you about the Architecture of data warehouse #learnwithsahuji #dwhmwithsahuji
Views: 832 Learn With Sahuji
OLAP Servers ll ROLAP, MOLAP, HOLAP Explained In Hindi
 
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ROLAP MOLAP HOLAP These OLAP SERVERS are explained in this video πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“ 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) πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™ YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING
Views: 24659 5 Minutes Engineering
L4: Data Warehousing and Data Mining |Data warehouse architecture| three tier architecture in hindi
 
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Join My official Whatsapp group by following link https://chat.whatsapp.com/F9XFi6QYFYOGA9JGw4gc1o L4: Data Warehousing and Data Mining |Data warehouse architecture| three tier architecture in hindi Namaskar, In the Today's lecture, i will cover Data warehouse architecture of subject Theory of Programming For Problem Solving which is one of the toughest subject of computer science and engineering and this taught in first year of B.Tech and BE I am Sandeep Vishwakarma (www.universityacademy.in) from Raj Kumar Goel Institute of Technology Ghaziabad. I have started a YouTube Channel Namely β€œUniversity 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 with deep knowledge of a 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: 327 University Academy
Decision Tree Important Points ll Machine Learning ll DMW ll Data Analytics ll Explained in Hindi
 
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Decision Tree Explained with Example https://youtu.be/RVuy1ezN_qA πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“ SUBJECT :- Discrete Mathematics (DM) Theory Of Computation (TOC) 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) πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™ YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š
Views: 20733 5 Minutes Engineering
Schema : Star Schema, Snowflake Schema, Fact Constellation Schema Explained In Hindi
 
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πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“ 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) πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™ YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š
Views: 22835 5 Minutes Engineering
Introduction To Information Retrieval System [Artificial Intelligence] (HINDI)
 
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πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“ 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) πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™ YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š
Views: 8487 5 Minutes Engineering
Data Mining Lecture -- Decision Tree | Solved Example (Eng-Hindi)
 
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-~-~~-~~~-~~-~- Please watch: "PL vs FOL | Artificial Intelligence | (Eng-Hindi) | #3" https://www.youtube.com/watch?v=GS3HKR6CV8E -~-~~-~~~-~~-~-
Views: 181654 Well Academy
Hadoop Architecture ll Map Reduce,HDFS,YARN Framework, Common Utilities Explained in Hindi
 
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πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“ SUBJECT :- Discrete Mathematics (DM) Theory Of Computation (TOC) 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) πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™ YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š
Views: 12518 5 Minutes Engineering
SAS Tutorials For Beginners | SAS Training | SAS Tutorial For Data Analysis | Edureka
 
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This SAS Tutorial is specially designed for beginners, it starts with Why Data Analytics is needed, goes on to explain the various tools in Data Analytics, and why SAS is used among them, towards the end we will see how we can install SAS software and a short demo on the same! In this SAS Tutorial video you will understand: 1) Why Data Analytics? 2) What is Data Analytics? 3) Data Science Analytics Tools 4) Why SAS? 5) What is SAS? 6) What SAS Solves? 7) Components of SAS 8) How can we practice Base SAS? 9) Demo Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete SAS Training playlist here: https://goo.gl/MMLyuN #SASTraining #SASTutorial #SASCertification How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 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. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course The SAS training course is designed to provide knowledge and skills to become a successful Analytics professional. It starts with the fundamental concepts of rules of SAS as a Language to an introduction to advanced SAS topics like SAS Macros. - - - - - - - - - - - - - - Why Learn SAS? The Edureka SAS training certifies you as an β€˜in demand’ SAS professional, to help you grab top paying analytics job titles with hands-on skills and expertise around data mining and management concepts. SAS is the primary analytics tool used by some of the largest KPOs, Banks like American Express, Barclays etc., financial services irms like GE Money, KPOs like Genpact, TCS etc., telecom companies like Verizon (USA), consulting companies like Accenture, KPMG etc use the tool effectively. - - - - - - - - - - - - - - Who should go for this course? This course is designed for professionals who want to learn widely acceptable data mining and exploration tools and techniques, and wish to build a booming career around analytics. The course is ideal for: 1. Analytics professionals who are keen to migrate to advanced analytics 2. BI /ETL/DW professionals who want to start exploring data to eventually become data scientist 3. Project Managers to help build hands-on SAS knowledge, and to become a SME via analytics 4. Testing professionals to move towards creative aspects of data analytics 5. Mainframe professionals 6. Software developers and architects 7. Graduates aiming to build a career in Big Data as a foundational step Please write back to us at [email protected] or call us at +918880862004 or 18002759730 for more information. Website: https://www.edureka.co/sas-training Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Sidharta Mitra, IBM MDM COE Head @ CTS , says, "Edureka has been an unique and fulfilling experience. The course contents are up-to-date and the instructors are industry trained and extremely hard working. The support is always willing to help you out in various ways as promptly as possible. Edureka redefines the way online training is conducted by making it as futuristic as possible, with utmost care and minute detailing, packaged into the a unique virtual classrooms. Thank you Edureka!"
Views: 50314 edureka!
Introduction To Artificial Neural Network Explained With Example In Hindi
 
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πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“ 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) πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™ YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š
Views: 14712 5 Minutes Engineering
4+1 Architecture View Model (HINDI)
 
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Hello dosto mera naam hai shridhar mankar aur mein aap Sabka Swagat karta hu 5-minutes engineering channel pe. This channel is launched with a aim to enhance the quality of knowledge of engineering,here I am going to introduce you to every subject of computer engineering like artificial intelligence database management system software modeling and designing Software engineering and project planning data mining and warehouse data analytics Mobile communication Mobile computing Computer networks high performance computing parallel computing Operating system Software programming SPOS web technology internet of things design and analysis of algorithm
Views: 3682 5 Minutes Engineering
Relational Database Concepts
 
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Basic Concepts on how relational databases work. Explains the concepts of tables, key IDs, and relations at an introductory level. For more info on Crow's Feet Notation: http://prescottcomputerguy.com/tmp/crows-foot.png
Views: 585943 Prescott Computer Guy
What is OLAP?
 
05:05
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: 372735 Intricity101
What is Business Intelligence (BI)?
 
03:47
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: 374649 Hitachi Solutions Canada
L2: Data Warehousing and Data Mining |Enterprise data Warehousing|Data mart|Warehousing Terminology
 
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Join My official Whatsapp group by following link https://chat.whatsapp.com/F9XFi6QYFYOGA9JGw4gc1o L2: Data Warehousing and Data Mining |Enterprise data Warehousing|Data mart|Warehousing Terminology 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 β€œUniversity 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: 498 University Academy
Agile Data Warehouse Design Tutorial | Data Warehouse Model
 
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The development of a data warehouse starts with a data model. In this video tutorial from our Agile Data Warehouse design training course, expert author Michael Blaha will take you through the process of creating a data model. More details on this Agile Data Warehouse Design training course, as well as more free lessons, can be found at http://oreil.ly/1S4zJcs. YouTube: https://www.youtube.com/user/OreillyMedia Facebook: https://www.facebook.com/OReilly/?fref=ts Twitter: https://twitter.com/OReillyMedia Website: http://www.oreilly.com/
WDM 112: How a Web Crawler Works
 
12:34
What is crawling For Full Course Experience Please Go To http://mentorsnet.org/course_preview?course_id=1 Full Course Experience Includes 1. Access to course videos and exercises 2. View & manage your progress/pace 3. In-class projects and code reviews 4. Personal guidance from your Mentors
Views: 27727 Oresoft LWC
What is a Data Model?
 
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Why is a Data Model so important? What is a packaged Data Model? How does a Data Model fit into a Data Warehousing project? This video addresses these basic questions and helps Business Users have realistic expectations about packaged models. To Talk with a Specialist go to: http://www.intricity.com/intricity101/
Views: 85106 Intricity101
What is DATA INTEGRATION? What does DATA INTEGRATION mean? DATA INTEGRATION meaning & explanation
 
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What is DATA INTEGRATION? What does DATA INTEGRATION mean? DATA INTEGRATION meaning - DATA INTEGRATION definition - DATA INTEGRATION explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. SUBSCRIBE to our Google Earth flights channel - https://www.youtube.com/channel/UC6UuCPh7GrXznZi0Hz2YQnQ Data integration involves combining data residing in different sources and providing users with a unified view of them. This process becomes significant in a variety of situations, which include both commercial (such as when two similar companies need to merge their databases) and scientific (combining research results from different bioinformatics repositories, for example) domains. Data integration appears with increasing frequency as the volume and the need to share existing data explodes. It has become the focus of extensive theoretical work, and numerous open problems remain unsolved. Consider a web application where a user can query a variety of information about cities (such as crime statistics, weather, hotels, demographics, etc.). Traditionally, the information must be stored in a single database with a single schema. But any single enterprise would find information of this breadth somewhat difficult and expensive to collect. Even if the resources exist to gather the data, it would likely duplicate data in existing crime databases, weather websites, and census data. A data-integration solution may address this problem by considering these external resources as materialized views over a virtual mediated schema, resulting in "virtual data integration". This means application-developers construct a virtual schemaβ€”the mediated schemaβ€”to best model the kinds of answers their users want. Next, they design "wrappers" or adapters for each data source, such as the crime database and weather website. These adapters simply transform the local query results (those returned by the respective websites or databases) into an easily processed form for the data integration solution (see figure 2). When an application-user queries the mediated schema, the data-integration solution transforms this query into appropriate queries over the respective data sources. Finally, the virtual database combines the results of these queries into the answer to the user's query. This solution offers the convenience of adding new sources by simply constructing an adapter or an application software blade for them. It contrasts with ETL systems or with a single database solution, which require manual integration of entire new dataset into the system. The virtual ETL solutions leverage virtual mediated schema to implement data harmonization; whereby the data are copied from the designated "master" source to the defined targets, field by field. Advanced data virtualization is also built on the concept of object-oriented modeling in order to construct virtual mediated schema or virtual metadata repository, using hub and spoke architecture. Each data source is disparate and as such is not designed to support reliable joins between data sources. Therefore, data virtualization as well as data federation depends upon accidental data commonality to support combining data and information from disparate data sets. Because of this lack of data value commonality across data sources, the return set may be inaccurate, incomplete, and impossible to validate. One solution is to recast disparate databases to integrate these databases without the need for ETL. The recast databases support commonality constraints where referential integrity may be enforced between databases. The recast databases provide designed data access paths with data value commonality across databases. ....
Views: 6033 The Audiopedia
OLAP Operations ll Roll Up/Drill Up And Drill Down Explained In Hindi
 
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Online Analytical Processing Operations Roll Up/Drill Up And Drill Down Explained In Hindi. 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) πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™ YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š
Views: 17741 5 Minutes Engineering
Apriori Algorithm in Data Mining And Analytics Explained With Example in Hindi
 
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Apriori Algorithm Explained With Solved Example Generating Association Rules. Association Rules Are Primary Aim or Output Of Apriori Algorithm. πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“πŸŽ“ 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) πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘πŸ’‘ THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™πŸ™ YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING πŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“šπŸ“š
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