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Data Mining & Business Intelligence | Tutorial #12 | Data Integration Process
 
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Order my books at 👉 http://www.tek97.com/ #RanjiRaj #DataMining #DataIntegration Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj Lets see what is Data Integration and its issues in various spheres of Data Mining. Watch now ! لنرى ما هو التكامل البيانات وقضاياها في مختلف مجالات البيانات التنقيب. شاهد الآن ! Давайте посмотрим, что такое Интеграция данных и ее проблемы в различных областях интеллектуального анализа данных. Смотри ! Voyons ce qu'est l'intégration de données et ses problèmes dans diverses sphères de l'exploration de données. Regarde maintenant ! Sehen wir uns an, was Data Integration und ihre Probleme in verschiedenen Bereichen des Data Mining sind. Schau jetzt ! Veamos qué es la integración de datos y sus problemas en varias esferas de la minería de datos. Ver ahora ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 1985 Ranji Raj
Data Integration
 
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In this video I will discuss about Data Integration in data mining. Data integration means combining data from multiple sources into a one single store. There are number of issues to consider during data integration like schema integration , object matching and entity identification problem.
Views: 1313 DataMining Tutorials
Data Cleaning Process Steps / Phases [Data Mining] Easiest Explanation Ever (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 5MINUTES ENGINEERING 📚📚📚📚📚📚📚📚
Views: 6042 5 Minutes Engineering
KDD ( knowledge data discovery )  in data mining in hindi
 
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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://goo.gl/to1yMH or Fill the form we will contact you https://goo.gl/forms/2SO5NAhqFnjOiWvi2 if you have any query email us at [email protected] or [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: 61411 Last moment tuitions
Introduction to data mining and architecture  in hindi
 
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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://goo.gl/to1yMH or Fill the form we will contact you https://goo.gl/forms/2SO5NAhqFnjOiWvi2 if you have any query email us at [email protected] or [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: 173962 Last moment tuitions
Repository Data Mining on GitHub @ WeAreDevelopers Conference 2017
 
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Visit the largest developers congress in Europe: WeAreDevelopers World Congress, 16 - 18 May 2018 in Vienna, Austria. https://www.wearedevelopers.com/congress/ Maxim Schuwalow, Fabian Richter, Tobias Ludwig and Johannes Nicolai from GitHub https://www.wearedevelopers.com/ Facebook: https://www.facebook.com/wearedevelopers.org/ Twitter: https://www.twitter.com/wearedevs/ LinkedIn: https://www.linkedin.com/company/wearedevelopers.org/
Views: 429 WeAreDevelopers
Join - Operator - RapidMiner - Data Mining
 
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The Join operator. The Join operator joins two example sets together in a variety of ways. Its parameters allow example sets to be enriched with new attributes using data from other sources, filtered to include only examples of interest and combined with other example sets to form subsets or supersets. Topics covered Inner join Left join Right join Outer join The Id attribute parameter Double attributes
Views: 214 Markus Hofmann
DM7 Data Integration تكامل البيانات
 
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أ.محمود رفيق الفرا مختصر مساق التنقيب عن البيانات Data Mining
Views: 1775 MahmoudRFarra
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: 2955 Learners Page
Data Mining & Business Intelligence | Tutorial #19 | Data Discretization
 
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Order my books at 👉 http://www.tek97.com/ #DataDiscretization #DataMining Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj Learn what data discretisation in data reduction in the context of data mining is. Watch now! تعرف على ما هو تقديس البيانات في الحد من البيانات في سياق استخراج البيانات. شاهد الآن ! Aprenda qué es la discretización de datos en la reducción de datos en el contexto de la minería de datos. Ver ahora ! Узнайте, что такое дискретизация данных при сокращении данных в контексте интеллектуального анализа данных. Смотри ! Erfahren Sie, was Datendiskretisierung bei der Datenreduktion im Kontext von Data Mining ist. Schau jetzt ! Apprenez ce qu'est la discrétisation des données dans la réduction des données dans le contexte de l'exploration de données. Regarde maintenant ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 2140 Ranji Raj
Introduction to Data Mining-: Snow Flake Schema
 
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You can find the entire course here: https://goo.gl/rM2W1E You can find all the courses by Hashleen Kaur here: https://goo.gl/SPmZoX Introduction to Data Mining| | Snow Flake Schema In this lesson, Hashleen K has discussed about Snow Flake Schema.This video contains Snow Flaked Schema model in detail with the SQL Code for a simple query in Star Flaked Schema model. Download the Unacademy Learning App from the Google Play Store here:- https://goo.gl/02OhYI Download the Unacademy Educator app from the Google Play Store here: https://goo.gl/H4LGHE Visit Our Facebook Group on Engineering Curriculum here: https://goo.gl/5EqfqS
Data Mining & Business Intelligence | Tutorial #5 | Measuring Central Tendency
 
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Order my books at 👉 http://www.tek97.com/ #RanjiRaj #DataMining #CentralTendency Lets see the mathematical measure to estimate the central tendency in data mining sets Mean, Median, Mode. دعونا نرى التدبير الرياضي لتقدير الاتجاه المركزي في مجموعات استخراج البيانات يعني ، متوسط ​​، الوضع. データマイニングセットの中央傾向を推定するための数学的尺度を見ることができます。Mean、Median、Mode。 Voyons la mesure mathématique pour estimer la tendance centrale dans les ensembles d'exploration de données Mean, Median, Mode. Sehen wir uns das mathematische Maß an, um die zentrale Tendenz in den Data Mining-Sets Mean, Median, Mode zu schätzen. Vediamo la misura matematica per stimare la tendenza centrale nei set di data mining Media, Mediana, Modalità. ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 1053 Ranji Raj
What is schema integration
 
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What is schema integration - Find out more explanation for : 'What is schema integration' only from this channel. Information Source: google
Views: 49 WikiAudio12
Dealing / Filling The Missing Values [Data Mining] (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: 3713 5 Minutes Engineering
Data Integration UAS --- Tutorial Pentaho & Data Mining
 
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I Kadek Putrawan-----13101167 Agus Putra Utama Yasa-----13101292 Ekky Agustana-----13101325
Views: 319 deks putrawan
Data Mining & Business Intelligence | Tutorial #4 | Forms Of Data Preprocessing
 
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Order my books at 👉 http://www.tek97.com/ #RanjiRaj #DataMining #DataPreprocessing Its important to preprocess the data before processing. Have a look at different forms of data preprocessing in data mining. Watch now ! Il est important de prétraiter les données avant le traitement. Jetez un oeil à différentes formes de prétraitement des données dans l'exploration de données. Regarde maintenant ! Es ist wichtig, die Daten vor der Verarbeitung vorzuverarbeiten. Sehen Sie sich verschiedene Formen der Datenvorverarbeitung im Data Mining an. Schau jetzt ! Es importante preprocesar los datos antes del procesamiento. Eche un vistazo a las diferentes formas de preprocesamiento de datos en la minería de datos. Ver ahora ! من المهم أن preprocess البيانات قبل المعالجة. إلقاء نظرة على أشكال مختلفة من معالجة البيانات في تعدين البيانات. شاهد الآن ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 2633 Ranji Raj
Data Mining & Business Intelligence | Tutorial #13 | Data Transformation Process
 
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Order my books at 👉 http://www.tek97.com/ #RanjiRaj #DataMining #DataTransformation Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj Interested to know about how data is transformed in Data Mining well this video is the answer for that! Watch now! مهتم بمعرفة كيف يتم تحويل البيانات في Data Mining بشكل جيد هذا الفيديو هو الحل لذلك! شاهد الآن ! Interesado en saber cómo se transforman los datos en Data Mining, este video es la respuesta para eso. Ver ahora ! Interessiert zu wissen, wie Daten in Data Mining umgewandelt werden, ist dieses Video die Antwort dafür! Schau jetzt ! Intéressé de savoir comment les données sont transformées dans Data Mining bien cette vidéo est la réponse pour cela! Regarde maintenant ! Заинтересованы в том, как данные преобразуются в Data Mining, и это видео является ответом на это! Смотри ! Interesado en saber cómo se transforman los datos en Data Mining, este video es la respuesta para eso. Ver ahora ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 1497 Ranji Raj
Data Mining & Business Intelligence | Tutorial #2 | Architecture Of Data Mining System
 
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Order my books at 👉 http://www.tek97.com/ Get familiar with the architecture possessed by Data Mining System.#RanjiRaj #DataMining #Architecture 1. Knowledge Base 2. Data Mining Engine 3. Pattern Evaluation Module 4. User Interface Machen Sie sich mit der Architektur von Data Mining System vertraut. 1. Wissensdatenbank 2. Data Mining-Engine 3. Musterbewertungsmodul 4. Benutzeroberfläche تعرف على الهندسة المعمارية التي يمتلكها نظام استخراج البيانات. 1. قاعدة المعرفة 2. محرك تعدين البيانات 3. وحدة نمط التقييم 4. واجهة المستخدم Familiarícese con la arquitectura que posee Data Mining System. 1. Base de conocimiento 2. Motor de minería de datos 3. Módulo de evaluación de patrones 4. Interfaz de usuario ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 2407 Ranji Raj
Data Mining & Business Intelligence | Tutorial #3 | Issues in Data Mining
 
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This video addresses the issues which are there involved in Data Mining system. Watch now! #RanjiRaj #DataMining #DMIssues Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj
Views: 2066 Ranji Raj
Data Mining Functionalities
 
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data warehousing and data mining || data mining funtionalities
Views: 2631 naga mounika Reddy
Data Mining   KDD Process
 
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KDD - knowledge discovery in Database. short introduction on Data cleaning,Data integration, Data selection,Data mining,pattern evaluation and knowledge representation.
Data Mining & Business Intelligence | Tutorial #15 | Data Reduction - Data Cube Aggregation
 
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Order my books at 👉 http://www.tek97.com/ #DataReduction #DataCubeAggregation Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj See the detailed explanation about Data Cube Aggregation in Data Mining as part of Data Reduction step. Watch now ! انظر الشرح التفصيلي حول تجميع بيانات المكعب في Data Mining كجزء من خطوة تقليل البيانات. شاهد الآن ! Weitere Informationen zur Datenwürfelaggregation im Data Mining finden Sie im Abschnitt Datenreduktion. Schau jetzt ! Consultez l'explication détaillée sur l'agrégation de cubes de données dans l'exploration de données dans le cadre de l'étape de réduction des données. Regarde maintenant ! Подробное описание агрегации Data Cube в Data Mining см. В разделе шага Data Reduction. Смотри ! Consulte la explicación detallada sobre la agregación de cubo de datos en la minería de datos como parte del paso de reducción de datos. Ver ahora ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 2717 Ranji Raj
Dealing With Noisy Data : Binning Technique [Data Mining] (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: 4691 5 Minutes Engineering
What is DATA INTEGRATION? What does DATA INTEGRATION mean? DATA INTEGRATION meaning & explanation
 
05:47
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 schema—the mediated schema—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: 4683 The Audiopedia
INTRODUCTION TO DATA MINING IN HINDI
 
15:39
Buy Software engineering books(affiliate): Software Engineering: A Practitioner's Approach by McGraw Hill Education https://amzn.to/2whY4Ke Software Engineering: A Practitioner's Approach by McGraw Hill Education https://amzn.to/2wfEONg Software Engineering: A Practitioner's Approach (India) by McGraw-Hill Higher Education https://amzn.to/2PHiLqY Software Engineering by Pearson Education https://amzn.to/2wi2v7T Software Engineering: Principles and Practices by Oxford https://amzn.to/2PHiUL2 ------------------------------- find relevant notes at-https://viden.io/
Views: 103586 LearnEveryone
Data Integration - 5 minute Explained
 
04:52
Cloud, IoT and Mobile have spurred rapid change in the way consumers interact with businesses. As a result, companies need to innovate at unprecedented speeds to remain competitive. How can you utilize integration, event processing and analytics to give your company the edge it needs to move digitally with the world? Watch this short teaser and email me at [email protected] to find out.
Views: 3515 ronnie xie
Types of databases
 
08:27
This video is telling about different types of databases. Next video will be about different types of attributes. #datamining #database #types
Views: 438 yaachana bhawsar
Data Mining & Business Intelligence | Tutorial #20 | Data Reduction - Concept Hierarchy Generation
 
05:09
Order my books at 👉 http://www.tek97.com/ #DataReduction #ConceptHierarchyGeneration Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj Confused about what is Concept Hierarchy Generation in Data Mining in the context of Data Mining well this video is for you. Watch Now! ارتباك حول ما هو الجيل الهرمي مفهوم في "التعدين البيانات" في سياق "التنقيب عن البيانات" جيدا هذا الفيديو لك. شاهد الآن! Confus au sujet de ce qu'est la génération de hiérarchie de concept dans l'exploration de données dans le contexte de l'exploration de données bien cette vidéo est pour vous. Regarde maintenant! Verwirrt darüber, was ist Konzept-Hierarchie-Generierung in Data Mining im Zusammenhang mit Data Mining gut dieses Video ist für Sie. Schau jetzt! Confundido sobre qué es la Generación de Jerarquía Conceptual en Minería de Datos en el contexto de la Minería de Datos, este video es para usted. ¡Ver ahora! Смутно о том, что представляет собой генерация концепции иерархии в интеллектуальном анализе данных в контексте Data Mining, это видео для вас. Смотри! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 1534 Ranji Raj
Pentaho Data Integration short demo
 
09:28
Pentaho is a powerful Business Intelligence Suite offering many features: reporting, OLAP pivot tables, dashboarding and more. Report Designer: An advanced report creation tool. If you want to build a complex data-driven report, this is the right tool to use. Report Designer offers far more flexibility and functionality than the ad hoc reporting capabilities of the Pentaho User Console. • Design Studio: An Eclipse-based tool that enables you to hand-edit a report or analysis view xaction file. Generally, people use Design Studio to add modifications to an existing report that cannot be added with Report Designer. • Aggregation Designer: A graphical tool that helps improve Mondrian cube efficiency. • Metadata Editor: Enables you to add a custom metadata layer to an existing data source. Usually you would do this for a data source that you intend to use for reporting; it's not required, but it makes it easier for business users to parse the database when building a query. • Pentaho Data Integration: The Kettle extract, transform, and load (ETL) tool, which enables you to access and prepare data sources for analysis, data mining, or reporting. This is generally where you will start if you want to prepare data for analysis. • Schema Workbench: A graphical tool that helps you create ROLAP schemas for analysis. This is a required step in preparing data for analysis.
Data Integration and Data Exchange
 
53:29
Google TechTalks March 24, 2006 Alan Nash ABSTRACT I will discuss two fundamental problems in information integration: (1) how to answer a query over a public interface which combines data from several sources and (2) how to create a single database conforming to the public interface which combines data from several sources. I consider the case where the sources are relational databases, where the public interface is a public schema (a specification of the format of a database), and where the sources are related to the public schema by a mapping that is specified by constraints.
Views: 2662 Google
R operations   Data Cleaning,Error Correction and Data Transformation on airquality dataset
 
16:27
THIS VIDEO SHOWS R OPERATIONS LIKE DATA CLEANING,ERROR CORECTION AND DATA TRANSFORMATION ON AIR QUALITY DATASET
Views: 6170 yogesh murumkar
Building Advanced Analytics Applications with R and Python Integration
 
46:57
At Tableau we help people see and understand data. Seven words that drive everything we do. And they’ve never been more relevant. Tableau is all about making your analytics faster, smarter, and more powerful, so that everyone can get the answers they need. Helping people gain insight into their data to solve unexpected problems is what drives us. Tableau is a visual analytics and reporting solution that connects directly to R, Python, and more. It’s designed for you, the domain expert who understands the data. Its drag-and-drop interface allows you effortlessly connect to libraries and packages, import saved models, or write new ones directly into calculations, visualizing them in seconds. In this webinar, we will explore how various analytics partners are leveraged in Tableau, and how to take advantage of these integrations to move your analysis to the next level. Whether you work with R, Python, or other statistical or data mining environments, Tableau allows you to take advantage of your existing investments and knowledge to compose impactful data stories. Read more at http://forums.bsdinsight.com/forums/tableau.95/
Views: 5033 Tableau
DIFFERENCES BETWEEN OLTP AND OLAP IN DATA WAREHOUSING AND DATA MINING
 
17:58
This video contains the differences between 1. OLTP and OLAP 2. Database and Datawarehouse 3.Operational Processing and Informational Processing
Data Warehouse tutorial. Creating an ETL.
 
30:25
This Data Warehouse video tutorial demonstrates how to create ETL (Extract, Load, Transform) package. See more lessons http://www.learn-with-video-tutorials.com/data-warehouse-tutorial-video
Data Mining & Business Intelligence | Tutorial #18 | Data Reduction - Numerosity Reduction
 
06:56
Order my books at 👉 http://www.tek97.com/ #DataReduction #NumerosityReduction Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj Watch this video to understand what is Numerosity Reduction as part of Data Reduction in Data Mining. Watch now ! شاهد هذا الفيديو لفهم ما هو تخفيض العداد كجزء من الحد من البيانات في استخراج البيانات. شاهد الآن ! Sehen Sie sich dieses Video an, um zu verstehen, was Numerositätsreduktion als Teil der Datenreduktion im Data Mining darstellt. Schau jetzt ! Regardez cette vidéo pour comprendre ce qu'est la réduction de la numération dans le cadre de la réduction des données dans l'exploration de données. Regarde maintenant ! Посмотрите это видео, чтобы понять, что такое Numerosity Reduction как часть сокращения данных в интеллектуальном анализе данных. Смотри ! Mire este video para comprender qué es Numerosity Reduction como parte de la reducción de datos en Data Mining. Ver ahora ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 1064 Ranji Raj
Data Mining & Business Intelligence | Tutorial #26 | OPTICS
 
07:17
Order my books at 👉 http://www.tek97.com/ #RanjiRaj #DataMining #OPTICS Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj OPTICS is a density based clustering technique in data mining for identifying arbitrary shaped clusters. Watch Now ! OPTICS هي تقنية تجميع تعتمد على الكثافة في التنقيب عن البيانات لتحديد المجموعات العشوائية. شاهد الآن ! ОПТИКА - это метод кластеризации на основе плотности при добыче данных для идентификации кластеров произвольной формы. Смотри ! OPTICS es una técnica de agrupación basada en la densidad en la minería de datos para identificar clusters con formas arbitrarias. Ver ahora ! OPTICS ist eine dichte-basierte Clustering-Technik im Data Mining zur Identifizierung beliebig geformter Cluster. Schau jetzt ! OPTICS est une technique de clustering basée sur la densité dans l'exploration de données pour identifier des groupes de formes arbitraires. Regarde maintenant ! OPTICS é uma técnica de clustering baseada em densidade em mineração de dados para identificar clusters de forma arbitrária. Assista agora ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 889 Ranji Raj
ETL ( Extract Transform Load )   process fully explained  in hindi | Datawarehouse
 
08:42
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://goo.gl/to1yMH or Fill the form we will contact you https://goo.gl/forms/2SO5NAhqFnjOiWvi2 if you have any query email us at [email protected] or [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: 51947 Last moment tuitions
DWH: Snowflake Vs Star Schema
 
03:50
In this tutorial, you 'll learn what is the difference between snowflake and star schema? In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis. DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data and are used for creating trending reports for senior management reporting such as annual and quarterly comparisons. The data stored in the warehouse is uploaded from the operational systems (such as marketing, sales, etc., shown in the figure to the right). The data may pass through an operational data store for additional operations before it is used in the DW for reporting. The typical extract-transform-load (ETL)-based data warehouse uses staging, data integration, and access layers to house its key functions. The staging layer or staging database stores raw data extracted from each of the disparate source data systems. The integration layer integrates the disparate data sets by transforming the data from the staging layer often storing this transformed data in an operational data store (ODS) database. The integrated data are then moved to yet another database, often called the data warehouse database, where the data is arranged into hierarchical groups often called dimensions and into facts and aggregate facts. The combination of facts and dimensions is sometimes called a star schema. The access layer helps users retrieve data.[4] This definition of the data warehouse focuses on data storage. The main source of the data is cleaned, transformed, cataloged and made available for use by managers and other business professionals for data mining, online analytical processing, market research and decision support.[5] However, the means to retrieve and analyze data, to extract, transform and load data, and to manage the data dictionary are also considered essential components of a data warehousing system. Many references to data warehousing use this broader context. Thus, an expanded definition for data warehousing includes business intelligence tools, tools to extract, transform and load data into the repository, and tools to manage and retrieve metadata.
Views: 13157 radhikaravikumar
Data Warehouse Concepts | Data Warehouse Tutorial | Data Warehouse Architecture | Edureka
 
52:30
***** 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. - - - - - - - - - - - - - - Please write back to us at [email protected] or call us at +91 90660 20866 for more information. 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: 42573 edureka!
Data Reduction
 
09:28
The video describes the use of Data reduction to find the parameters of various activity coeffcieint models like Margules, NRTL, Wilson etc.
Views: 229 Milind Joshipura
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. - - - - - - - - - - - - - - Please write back to us at [email protected] or call us at +91 90660 20866 for more information. 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: 189062 edureka!
Pentaho BI Suite CE  Saiku + CDE Demo
 
13:05
Pentaho is a powerful Business Intelligence Suite offering many features: reporting, OLAP pivot tables, dashboarding and more. Report Designer: An advanced report creation tool. If you want to build a complex data-driven report, this is the right tool to use. Report Designer offers far more flexibility and functionality than the ad hoc reporting capabilities of the Pentaho User Console. • Design Studio: An Eclipse-based tool that enables you to hand-edit a report or analysis view xaction file. Generally, people use Design Studio to add modifications to an existing report that cannot be added with Report Designer. • Aggregation Designer: A graphical tool that helps improve Mondrian cube efficiency. • Metadata Editor: Enables you to add a custom metadata layer to an existing data source. Usually you would do this for a data source that you intend to use for reporting; it's not required, but it makes it easier for business users to parse the database when building a query. • Pentaho Data Integration: The Kettle extract, transform, and load (ETL) tool, which enables you to access and prepare data sources for analysis, data mining, or reporting. This is generally where you will start if you want to prepare data for analysis. • Schema Workbench: A graphical tool that helps you create ROLAP schemas for analysis. This is a required step in preparing data for analysis.
mod01lec02
 
36:13
Views: 9552 Data Mining - IITKGP
Data Mining & Business Intelligence | Tutorial #7 | Measuring Data Dispersion
 
06:31
Order my books at 👉 http://www.tek97.com/ #RanjiRaj #DataMining #DataDispersion This video will address the various mathematical measures to estimate the dispersion of data in a data mining system. Watch it now ! In diesem Video werden die verschiedenen mathematischen Maßnahmen zur Schätzung der Streuung von Daten in einem Data Mining-System behandelt. Jetzt ansehen ! Cette vidéo traitera des diverses mesures mathématiques permettant d'estimer la dispersion des données dans un système d'exploration de données. Regardez-le maintenant ! سيعالج هذا الفيديو الإجراءات الرياضية المختلفة لتقدير تشتت البيانات في نظام تعدين البيانات. مشاهدته الآن ! Este video abordará las diversas medidas matemáticas para estimar la dispersión de datos en un sistema de minería de datos. ¡Míralo ahora! В этом видео будут рассмотрены различные математические меры для оценки дисперсии данных в системе интеллектуального анализа данных. Смотри сейчас! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 845 Ranji Raj
Integrate 3 Tables from 1 Excel Sheet with Pentaho Data Integration
 
07:51
Pentaho is a powerful Business Intelligence Suite offering many features: reporting, OLAP pivot tables, dashboarding and more. Report Designer: An advanced report creation tool. If you want to build a complex data-driven report, this is the right tool to use. Report Designer offers far more flexibility and functionality than the ad hoc reporting capabilities of the Pentaho User Console. • Design Studio: An Eclipse-based tool that enables you to hand-edit a report or analysis view xaction file. Generally, people use Design Studio to add modifications to an existing report that cannot be added with Report Designer. • Aggregation Designer: A graphical tool that helps improve Mondrian cube efficiency. • Metadata Editor: Enables you to add a custom metadata layer to an existing data source. Usually you would do this for a data source that you intend to use for reporting; it's not required, but it makes it easier for business users to parse the database when building a query. • Pentaho Data Integration: The Kettle extract, transform, and load (ETL) tool, which enables you to access and prepare data sources for analysis, data mining, or reporting. This is generally where you will start if you want to prepare data for analysis. • Schema Workbench: A graphical tool that helps you create ROLAP schemas for analysis. This is a required step in preparing data for analysis.
What is Data Warehousing?
 
08:09
Data warehouse is constructed by integrating data from multiple heterogeneous sources that support analytical reporting. Data warehousing involves data cleaning, data integration, and data consolidations. Data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW). Data warehouse is a system used for reporting and data analysis. Data warehouse is considered a core component of business intelligence. Data warehouse are central repositories of integrated data from one or more disparate sources. Data warehouse store current and historical data in one single place. Data warehouse are used for creating analytical reports for workers throughout the enterprise. The data stored in the warehouse is uploaded from the operational systems (ERP). The data may pass through an operational data store and may require data cleansing for additional operations to ensure data quality before it is used in the Data warehouse for reporting. Staging database stores raw data extracted from source data systems. Data warehouse stores transformed data. The combination of facts and dimensions is sometimes called a star schema. The main source of the data is cleansed, transformed, cataloged and made available for use by managers and other business professionals.
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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

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