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Data Analysis in MySQL and Excel 2013 - Example
 
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In this video I show how to import a table from MySQL into Excel so that seasonal analysis can be conducted.
Views: 28928 Michael Herman
Advanced Excel - Data Mining Techniques using Excel
 
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Key Takeaways for the session : Breaking junk using formula and generate reports VBA to manipulate data in required format Data extraction from external files Who should attend? People from any domain who work on data in any form. Good for Engineers, Leads, Managers, Sales people, HR, MIS experts, Data scientists, IT Support, BPO, KPO etc. Feel free to write me at [email protected]
Weka Data Mining Tutorial for First Time & Beginner Users
 
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23-minute beginner-friendly introduction to data mining with WEKA. Examples of algorithms to get you started with WEKA: logistic regression, decision tree, neural network and support vector machine. Update 7/20/2018: I put data files in .ARFF here http://pastebin.com/Ea55rc3j and in .CSV here http://pastebin.com/4sG90tTu Sorry uploading the data file took so long...it was on an old laptop.
Views: 457564 Brandon Weinberg
End-To-End-Example: Data Analysis with Pandas
 
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In this end to end example we web scrape the HTML of this class schedule off of this website: https://ischool.syr.edu/classes/ into a pandas dataframe. From there we extract a feature column for which classes are Undergraduate versus Graduate, then we finish by finding the Undergraduate classes on Fridays or at 8AM. Like all End-To-End examples the program is written organically piece by piece until complete. I make mistakes and figure things out as I go. You can download the code for this example on GitHub: https://github.com/IST256/learn-python/tree/master/content/lessons/12/End-To-End-Example
Views: 5486 Michael Fudge
Data Mining Lecture - - Finding frequent item sets | Apriori Algorithm | Solved Example (Eng-Hindi)
 
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In this video Apriori algorithm is explained in easy way in data mining Thank you for watching share with your friends Follow on : Facebook : https://www.facebook.com/wellacademy/ Instagram : https://instagram.com/well_academy Twitter : https://twitter.com/well_academy data mining in hindi, Finding frequent item sets, data mining, data mining algorithms in hindi, data mining lecture, data mining tools, data mining tutorial,
Views: 212419 Well Academy
Develop a Data Science Project | Solving a Data Science Problem | Data Science Tutorial | Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) Watch sample class recording: http://www.edureka.co/data-science?utm_source=youtube&utm_medium=referral&utm_campaign=develop-datascience-project Data science is the study of the generalizable extraction of knowledge from data, yet the key word is science. Data Science is one of the most-sought after professions today. Universities across the world are offering courses in this discipline which stands testimony to this emerging profession. There are a very few professionals with the required skill and the demand for data scientists is racing ahead. The tutorial wil give a brief understanding about Data Science. The topics covered in the video: 1.Problem Statement 2.Variable Desriptions 3.Data EXploration 4.Data Cleaning and Preparation 5.Reading from Other Sources 6.Titanic Data Sets 7.Decision Trees and Random Forests 8.Build a Decision Tree 9.Build a Random Forest 10.Linear Regression 11.Logistic Regression 12.Machine Learning 13.Data Mining 14.Machine Learning and Data Mining Resources 15.Solving a Data Science Problem using R, Hadoop, Mahout Related Posts: http://www.edureka.co/blog/who-can-take-up-a-data-science-tutorial/?utm_source=youtube&utm_medium=referral&utm_campaign=develop-datascience-project http://www.edureka.co/blog/enroll-for-a-data-science-course/?utm_source=youtube&utm_medium=referral&utm_campaign=develop-datascience-project http://www.edureka.co/blog/types-of-data-scientists/?utm_source=youtube&utm_medium=referral&utm_campaign=develop-datascience-project http://www.edureka.co/blog/core-data-scientist-skills/?utm_source=youtube&utm_medium=referral&utm_campaign=develop-datascience-project Edureka is a New Age e-learning platform that provides Instructor-Led Live, Online classes for learners who would prefer a hassle free and self paced learning environment, accessible from any part of the world. ‘Develop a Data Science Project’ have been widely covered in our course ‘Data Science’. For more information, please write back to us at [email protected] Call us at US: 1800 275 9730 (toll free) or India: +91-8880862004
Views: 31396 edureka!
How to Clean Up Raw Data in Excel
 
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Al Chen (https://twitter.com/bigal123) is an Excel aficionado. Watch as he shows you how to clean up raw data for processing in Excel. This is also a great resource for data visualization projects. Subscribe to Skillshare’s Youtube Channel: http://skl.sh/yt-subscribe Check out all of Skillshare’s classes: http://skl.sh/youtube Like Skillshare on Facebook: https://www.facebook.com/skillshare Follow Skillshare on Twitter: https://twitter.com/skillshare Follow Skillshare on Instagram: http://instagram.com/Skillshare
Views: 89623 Skillshare
Excel Data Analysis: Sort, Filter, PivotTable, Formulas (25 Examples): HCC Professional Day 2012
 
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Download workbook: http://people.highline.edu/mgirvin/ExcelIsFun.htm Learn the basics of Data Analysis at Highline Community College Professional Development Day 2012: Topics in Video: 1. What is Data Analysis? ( 00:53 min mark) 2. How Data Must Be Setup ( 02:53 min mark) Sort: 3. Sort with 1 criteria ( 04:35 min mark) 4. Sort with 2 criteria or more ( 06:27 min mark) 5. Sort by color ( 10:01 min mark) Filter: 6. Filter with 1 criteria ( 11:26 min mark) 7. Filter with 2 criteria or more ( 15:14 min mark) 8. Filter by color ( 16:28 min mark) 9. Filter Text, Numbers, Dates ( 16:50 min mark) 10. Filter by Partial Text ( 20:16 min mark) Pivot Tables: 11. What is a PivotTable? ( 21:05 min mark) 12. Easy 3 step method, Cross Tabulation ( 23:07 min mark) 13. Change the calculation ( 26:52 min mark) 14. More than one calculation ( 28:45 min mark) 15. Value Field Settings (32:36 min mark) 16. Grouping Numbers ( 33:24 min mark) 17. Filter in a Pivot Table ( 35:45 min mark) 18. Slicers ( 37:09 min mark) Charts: 19. Column Charts from Pivot Tables ( 38:37 min mark) Formulas: 20. SUMIFS ( 42:17 min mark) 21. Data Analysis Formula or PivotTables? ( 45:11 min mark) 22. COUNTIF ( 46:12 min mark) 23. Formula to Compare Two Lists: ISNA and MATCH functions ( 47:00 min mark) Getting Data Into Excel 24. Import from CSV file ( 51:21 min mark) 25. Import from Access ( 54:00 min mark) Highline Community College Professional Development Day 2012 Buy excelisfun products: https://teespring.com/stores/excelisfun-store
Views: 1554138 ExcelIsFun
How To... Perform a Chi-Square Test (By Hand)
 
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Also known as a "Goodness of Fit" test, use this single sample Chi-Square test to determine if there is a significant difference between Observed and Expected values. This video shows a step-by-step method for calculating Chi-square.
Views: 402611 Eugene O'Loughlin
Beginner - Data Science Project
 
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The best way to learn data science and showcase your skills is by doing some actual projects – we learn best by doing. So, how do we choose a project to work on? Where do we start? One way to approach it is to first look at some career websites and find a few jobs in data science that you aspire to have in the future. Write down the skills, qualifications, day-to-day expectations, and overall job description from the jobs that interest you. This will give you the project “requirements” that you can work with to formulate a project. http://storybydata.com/data-science-learn-by-doing-global-super-store-project/
Views: 31197 Story by Data
How data mining works
 
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In this video we describe data mining, in the context of knowledge discovery in databases. More videos on classification algorithms can be found at https://www.youtube.com/playlist?list=PLXMKI02h3_qjYoX-f8uKrcGqYmaqdAtq5 Please subscribe to my channel, and share this video with your peers!
Views: 229710 Thales Sehn Körting
What is OLAP?
 
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This video explores some of OLAP's history, and where this solution might be applicable. We also look at situations where OLAP might not be a fit. Additionally, we investigate an alternative/complement called a Relational Dimensional Model. To Talk with a Specialist go to: http://www.intricity.com/intricity101/
Views: 372723 Intricity101
Social Network Analysis with R | Examples
 
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Social network analysis with several simple examples in R. R file: https://goo.gl/CKUuNt Data file: https://goo.gl/Ygt1rg Includes, - Social network examples - Network measures - Read data file - Create network - Histogram of node degree - Network diagram - Highlighting degrees & different layouts - Hub and authorities - Community detection R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 19982 Bharatendra Rai
Intro to Data Analysis / Visualization with Python, Matplotlib and Pandas | Matplotlib Tutorial
 
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Python data analysis / data science tutorial. Let’s go! For more videos like this, I’d recommend my course here: https://www.csdojo.io/moredata Sample data and sample code: https://www.csdojo.io/data My explanation about Jupyter Notebook and Anaconda: https://bit.ly/2JAtjF8 Also, keep in touch on Twitter: https://twitter.com/ykdojo And Facebook: https://www.facebook.com/entercsdojo Outline - check the comment section for a clickable version: 0:37: Why data visualization? 1:05: Why Python? 1:39: Why Matplotlib? 2:23: Installing Jupyter through Anaconda 3:20: Launching Jupyter 3:41: DEMO begins: create a folder and download data 4:27: Create a new Jupyter Notebook file 5:09: Importing libraries 6:04: Simple examples of how to use Matplotlib / Pyplot 7:21: Plotting multiple lines 8:46: Importing data from a CSV file 10:46: Plotting data you’ve imported 13:19: Using a third argument in the plot() function 13:42: A real analysis with a real data set - loading data 14:49: Isolating the data for the U.S. and China 16:29: Plotting US and China’s population growth 18:22: Comparing relative growths instead of the absolute amount 21:21: About how to get more videos like this - it’s at https://www.csdojo.io/moredata
Views: 237113 CS Dojo
Data Mining, Classification, Clustering, Association Rules, Regression, Deviation
 
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Complete set of Video Lessons and Notes available only at http://www.studyyaar.com/index.php/module/20-data-warehousing-and-mining Data Mining, Classification, Clustering, Association Rules, Sequential Pattern Discovery, Regression, Deviation http://www.studyyaar.com/index.php/module-video/watch/53-data-mining
Views: 88260 StudyYaar.com
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 ‘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: 70257 edureka!
Types of Data: Nominal, Ordinal, Interval/Ratio - Statistics Help
 
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The kind of graph and analysis we can do with specific data is related to the type of data it is. In this video we explain the different levels of data, with examples. Subtitles in English and Spanish.
Views: 881117 Dr Nic's Maths and Stats
SSRS Video :- How to create a simple report in SQL Server reporting services ?
 
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For more such videos visit http://www.questpond.com For more such videos subscribe https://www.youtube.com/questpondvideos?sub_confirmation=1 See our other Step by Step video series below :- Learn angular tutorial for beginners https://tinyurl.com/ycd9j895 Learn MVC Core step by step :- http://tinyurl.com/y9jt3wkv Learn MSBI Step by Step in 32 hours:- https://goo.gl/TTpFZN Learn Xamarin Mobile Programming Step by Step :- https://goo.gl/WDVFuy Learn Design Pattern Step by Step in 8 hours:- https://goo.gl/eJdn0m Learn C# Step by Step in 100 hours :- https://goo.gl/FNlqn3 Learn Data structures & algorithm in 8 hours :-https://tinyurl.com/ybx29c5s Learn SQL Server Step by Step in 16 hours:- http://tinyurl.com/ja4zmwu Learn Javascript in 2 hours :- http://tinyurl.com/zkljbdl Learn SharePoint Step by Step in 8 hours:- https://goo.gl/XQKHeP Learn TypeScript in 45 Minutes :- https://goo.gl/oRkawI Learn webpack in 50 minutes:- https://goo.gl/ab7VJi Learn Visual Studio code in 10 steps for beginners:- https://tinyurl.com/lwgv8r8 Learn Tableau step by step :- https://tinyurl.com/kh6ojyo Want to know about Why MSBI Career is good see this. https://goo.gl/OVYcsM Below is the full syllabus of Lear MSBI in 4 days videos Lab 1 :- BI Life cycle , Data flow , control flow , error viewing and ETL Demo Lab 2 :- Error handling , Conditional and data conversion.Trailer https://goo.gl/T3oM6Y Lab 3 :- For loop,Debugging , variables and parameters. Trailer https://goo.gl/IBQRvo Lab 4:- Packaging and Deployment, File component and running SSIS package as a task. Trailer https://goo.gl/pvgOlA Lab 5: - For dimension, measures, star schema, snow flake, shared connection managers & packages tasks. Here is the trailer for the video https://goo.gl/Ry08Or Lab 6:- For Slowly Changing dimensions Type 1 and Type 2 With and Without Historical data OLEDB Command Param and Sequence in OLEDB command Unicode and non-unicode characters. Trailer https://goo.gl/6hxNpU Lab 7 for Lookups , Optimizing datatype conversion and how to update changes in MSBI.Here is the trailer for the video https://goo.gl/5nAqyW Lab 8:- Sort, Merge and Merge joins to combine data from different data sources and create a Merged data. Lab 9 :- Creating SSAS Cube ( 30 minutes) Trailer https://goo.gl/LAkgqP Lab 10 :- SSAS Time series and Excel display of SSAS Cube. https://goo.gl/GORhiw Lab 11 :- Transaction and Checkpoints in MSBI. For trailer https://goo.gl/14NT3m Lab 12 :- Creating a simple SSRS report and implementing Matrix,Tabular,Parameters,Sorting,Expres­sions in SSRS https://goo.gl/79a3K9 Lab 13:- Using Data Profiling task to check data quality (20 Minutes) Trailer https://goo.gl/EzT3IM Lab 14:- Dimension Hierarchies (SSAS) (30 Minutes) Trailer https://goo.gl/RI4iU9 Lab 15 :- Webservice and XMLTask component. (15 Minutes) Lab 16:- DrillDown and Subreports (20 Minutes) Trailer https://goo.gl/WKJHvR Lab 17:- SSAS KPI (Key Performance indicators)(15 Minutes) Trailer https://goo.gl/Wlkb1H Lab 18:- Pivot, UnPivot and Aggregation (20 Minutes) Trailer https://goo.gl/gZzJkC Lab 19 :- SSAS Calculation. (30 Minutes) Lab 20:- SQL Execute Task (30 Minutes) Trailer https://goo.gl/XNMuFJ Lab 21:- Reference and Many-to-Many Relationship(30 Minutes) Trailer https://goo.gl/jYbGfd Lab 22 :- Script Task and Send Mail Task(15 Minutes) In this video we will talk about one of the important and useful task in SSIS called Script Task. Lab 23:- Script component (SSIS)(45 Minutes) Lab 24 :- Bar charts , Pie charts and Gauge report(20 Minutes) Trailer https://goo.gl/SUrjxO Lab 25 :- SSAS Partitions (30 Minutes) Trailer https://goo.gl/aZ13Kh Lab 26:- CDC (Changed Data Capture) in SSIS. (35 Minutes)Trailer https://goo.gl/rkcvsU Lab 27:- Additive, Semiadditive and non-additive measures in SSAS.(15 Minutes) In this video we will discuss about different kinds of measures in SSAS. Lab 28:- Buffer Size Tuning (SSIS).Trailer https://goo.gl/oTSxdK Lab 29:-How to impliment Multithreading in SSIS? Trailer https://goo.gl/7IHZTP Lab 30 :- SSAS Cube background Processing. (Trailer) https://goo.gl/X1pN3z Lab 31 :- Asynch and Blocking SSIS components. (Trailer) https://goo.gl/HifAEP Lab 32 :- SSRS Architecture and Deployment Lab 33 :- DQS( Data Quality Services ) Trailer https://goo.gl/s60hSO Lab 34 :- Tabular Model and Power Pivot (SSAS) Trailer https://goo.gl/BRik9A Lab 35 :- MDX (Multidimensional Expressions) Queries. Trailer https://goo.gl/vmnzjM Lab 36 :- Data Mining (Fundamentals and Time Series Algorithm).Trailer https://goo.gl/ylNccY Lab 37 :- Page Split and Performance issues with (SSIS). Trailer https://goo.gl/eKPkO1 Lab 38 :- Aggregations in SSAS.(Trailer) https://goo.gl/OsxiDE MSBI doubt session 1 :- SSAS Multi dimensional cube deployed on Tabular issue. https://goo.gl/5dRp4T
Views: 342772 Questpond
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: 240601 edureka!
Data Analysis with Python for Excel Users
 
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A common task for scientists and engineers is to analyze data from an external source. By importing the data into Python, data analysis such as statistics, trending, or calculations can be made to synthesize the information into relevant and actionable information. See http://apmonitor.com/che263/index.php/Main/PythonDataAnalysis
Views: 173988 APMonitor.com
Oracle data mining tutorial, data mining techniques classification
 
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What is data mining? The Oracle Data Miner tutorial presents data mining introduction. Learn data mining techniques.
Introduction to Data Mining in SQL Server Analysis Services
 
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Data mining is one of the key hidden gems inside of Analysis Services but has traditionally had a steep learning curve. In this session, you'll learn how to create a data mining model to predict who is the best customer for you and learn how to use other algorithms to spend your marketing model wisely. You'll also see how to use Time Series analysis for budget and forecast prediction. Finally, you'll learn how to integrate data mining into your application through SSIS or custom coding.
Views: 10655 PASStv
Quick Data Analysis with Google Sheets | Part 1
 
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Spreadsheet software like Excel or Google Sheets are still a very widely used toolset for analyzing data. Sheets has some built-in Quick analysis features that can help you to get a overview on your data and very fast get to insights. #DataAnalysis #GoogleSheet #measure 🔗 Links mentioned in the video: Supermetrics: http://supermetrics.com/?aff=1014 GA Demo account: https://support.google.com/analytics/answer/6367342?hl=en 🎓 Learn more from Measureschool: http://measureschool.com/products GTM Copy Paste https://chrome.google.com/webstore/detail/gtm-copy-paste/mhhidgiahbopjapanmbflpkcecpciffa 🚀Looking to kick-start your data journey? Hire us: https://measureschool.com/services/ 📚 Recommended Measure Books: https://kit.com/Measureschool/recommended-measure-books 📷 Gear we used to produce this video: https://kit.com/Measureschool/measureschool-youtube-gear Our tracking stack: Google Analytics: https://analytics.google.com/analytics/web/ Google Tag Manager: https://tagmanager.google.com/ Supermetrics: http://supermetrics.com/?aff=1014 ActiveCampaign: https://www.activecampaign.com/?_r=K93ZWF56 👍 FOLLOW US Facebook: http://www.facebook.com/measureschool Twitter: http://www.twitter.com/measureschool
Views: 15610 Measureschool
#1 Pivot Table Example | 1.6M Sales Data
 
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Pivot Table Example | Sales Data In this video, we have explained the Sales Data Analysis using Pivot Table in Excel and How to use Text formula and How to use a Sparkline in Excel. To watch more videos and Download that files at https://goo.gl/XHgHU4 Enroll our FREE Course at https://courses.yodalearning.com/p/free-office-2016-tips Keep yourself updated. Follow us now! Like us on https://www.facebook.com/yodalearning Tweet us on https://www.twitter.com/yodalearning Follow our boards at https://in.pinterest.com/yodalearning/pins/
Social Media Analytics - Twitter Analysis in R (Example @realDonaldTrump)
 
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Case Study: Donald Trump Twitter (@realDonaldTrump) Analysis Click here to see how to link to Twitter database: https://www.youtube.com/watch?v=ebutXE4MJ3Y (UPDATED) Twitter Analytics in R codes Powerpoint can be downloaded at https://drive.google.com/open?id=0Bz9Gf6y-6XtTNDE5a2V0dXBjWVU How to process tweets with emojis in R? What if there is a gsub utf-8 invalid error? (Example Solution) 1. Use gsub to replace the emojis (utf-8 coding) codes. 2. See slide 7 in the Powerpoint file above.
Views: 6264 The Data Science Show
SSAS Data Mining Overview
 
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Just an overview of SSAS Data Mining. Check out Microsoft's tutorial for more info: https://msdn.microsoft.com/en-us/library/ms167167(v=sql.120).aspx
Views: 2037 Randal Root
Data Cleaning In Python (Practical Examples)
 
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Data Cleaning In Python with Pandas In this tutorial we will see some practical issues we have when working with data,how to diagnose them and how to solve them. ==Tutorial and Data Set here== Github: https://goo.gl/erg89C Blog: https://goo.gl/6PJsdo Reference ====Common Data Cleaning Issues==== Reading File Inconsistent Column Names Missing Data Duplicates Inconsistent Data Types Outliers Noisy Data etc.
Views: 12645 J-Secur1ty
Support Vector Machine (SVM) - Fun and Easy Machine Learning
 
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Support Vector Machine (SVM) - Fun and Easy Machine Learning ►FREE YOLO GIFT - http://augmentedstartups.info/yolofreegiftsp ►KERAS COURSE - https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/?couponCode=YOUTUBE_ML ►MACHINE LEARNING COURSES -http://augmentedstartups.info/machine-learning-courses ------------------------------------------------------------------------ A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs an optimal hyperplane which categorizes new examples. To understand SVM’s a bit better, Lets first take a look at why they are called support vector machines. So say we got some sample data over here of features that classify whether a observed picture is a dog or a cat, so we can for example look at snout length or and ear geometry if we assume that dogs generally have longer snouts and cat have much more pointy ear shapes. So how do we decide where to draw our decision boundary? Well we can draw it over here or here or like this. Any of these would be fine, but what would be the best? If we do not have the optimal decision boundary we could incorrectly mis-classify a dog with a cat. So if we draw an arbitrary separation line and we use intuition to draw it somewhere between this data point for the dog class and this data point of the cat class. These points are known as support Vectors – Which are defined as data points that the margin pushes up against or points that are closest to the opposing class. So the algorithm basically implies that only support vector are important whereas other training examples are ‘ignorable’. An example of this is so that if you have our case of a dog that looks like a cat or cat that is groomed like a dog, we want our classifier to look at these extremes and set our margins based on these support vectors. ------------------------------------------------------------ Support us on Patreon ►AugmentedStartups.info/Patreon Chat to us on Discord ►AugmentedStartups.info/discord Interact with us on Facebook ►AugmentedStartups.info/Facebook Check my latest work on Instagram ►AugmentedStartups.info/instagram Learn Advanced Tutorials on Udemy ►AugmentedStartups.info/udemy ------------------------------------------------------------ To learn more on Artificial Intelligence, Augmented Reality IoT, Deep Learning FPGAs, Arduinos, PCB Design and Image Processing then check out http://augmentedstartups.info/home Please Like and Subscribe for more videos :)
Views: 176009 Augmented Startups
Frequent Pattern (FP) growth Algorithm for Association Rule Mining
 
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The FP-Growth Algorithm, proposed by Han, is an efficient and scalable method for mining the complete set of frequent patterns by pattern fragment growth, using an extended prefix-tree structure for storing compressed and crucial information about frequent patterns named frequent-pattern tree (FP-tree).
Views: 99694 StudyKorner
R - Sentiment Analysis and Wordcloud with R from Twitter Data | Example using Apple Tweets
 
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Provides sentiment analysis and steps for making word clouds with r using tweets about apple obtained from Twitter. Link to R and csv files: https://goo.gl/B5g7G3 https://goo.gl/W9jKcc https://goo.gl/khBpF2 Topics include: - reading data obtained from Twitter in a csv format - cleaning tweets for further analysis - creating term document matrix - making wordcloud, lettercloud, and barplots - sentiment analysis of apple tweets before and after quarterly earnings report R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 17146 Bharatendra Rai
Apriori Algorithm (Associated Learning) - Fun and Easy Machine Learning
 
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Apriori Algorithm (Associated Learning) - Fun and Easy Machine Learning ►FREE YOLO GIFT - http://augmentedstartups.info/yolofreegiftsp ►KERAS Course - https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/?couponCode=YOUTUBE_ML Limited Time - Discount Coupon Apriori Algorithm The Apriori algorithm is a classical algorithm in data mining that we can use for these sorts of applications (i.e. recommender engines). So It is used for mining frequent item sets and relevant association rules. It is devised to operate on a database containing a lot of transactions, for instance, items brought by customers in a store. It is very important for effective Market Basket Analysis and it helps the customers in purchasing their items with more ease which increases the sales of the markets. It has also been used in the field of healthcare for the detection of adverse drug reactions. A key concept in Apriori algorithm is that it assumes that: 1. All subsets of a frequent item sets must be frequent 2. Similarly, for any infrequent item set, all its supersets must be infrequent too. ------------------------------------------------------------ Support us on Patreon ►AugmentedStartups.info/Patreon Chat to us on Discord ►AugmentedStartups.info/discord Interact with us on Facebook ►AugmentedStartups.info/Facebook Check my latest work on Instagram ►AugmentedStartups.info/instagram Learn Advanced Tutorials on Udemy ►AugmentedStartups.info/udemy ------------------------------------------------------------ To learn more on Artificial Intelligence, Augmented Reality IoT, Deep Learning FPGAs, Arduinos, PCB Design and Image Processing then check out http://augmentedstartups.info/home Please Like and Subscribe for more videos :)
Views: 58404 Augmented Startups
SAS Visual Analytics Demo for Retail
 
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http://www.sas.com/visualanalytics Learn how to use SAS Visual Analytics to identify customer segments and do Market Basket Analysis Reporting. SAS VISUAL ANALYTICS Get fast answers to even the most complex questions using data of any size – including big data in Hadoop. Guided exploration makes it easy. In-memory processing makes it fast. Advanced data visualization tools make it clear. Scalability makes it the perfect fit. And the price makes it within your reach. LEARN MORE ABOUT SAS VISUAL ANALYTICS http://www.sas.com/software/visual-analytics/overview.html TRY VISUAL ANALYTICS YOURSELF Browse sample reports or explore on your own with this cloud-based demo. http://www.sas.com/software/visual-analytics/demos/all-demos.html SUBSCRIBE TO THE SAS SOFTWARE YOUTUBE CHANNEL http://www.youtube.com/subscription_center?add_user=sassoftware ABOUT SAS SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions, SAS helps customers at more than 75,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world The Power to Know.® VISIT SAS http://www.sas.com CONNECT WITH SAS SAS ► http://www.sas.com SAS Customer Support ► http://support.sas.com SAS Communities ► http://communities.sas.com Facebook ► https://www.facebook.com/SASsoftware Twitter ► https://www.twitter.com/SASsoftware LinkedIn ► http://www.linkedin.com/company/sas Google+ ► https://plus.google.com/+sassoftware Blogs ► http://blogs.sas.com RSS ►http://www.sas.com/rss
Views: 105683 SAS Software
Analysis of Data Reports
 
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See multiple examples of Analysis of Data Reports for HCS 438 - Statistical Applications at the University of Phoenix. Find targeted papers for this class here: http://www.research-paper-example.com/HCS-438.html
RESUME BUILDING FOR FRESHERS - PART 1 | Sample Resume Format | Resume Writing Tips
 
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FULL NAME Mobile: 0123456789 E-Mail: [email protected] (your name) OBJECTIVES (write your objectives in 3 sentences only) Very precise, short and should convey the message to the person reading it. For example : “To seek a position in a well established Organisation that offers room for professional growth, as this provides me ample opportunities to exhibit my skills and competencies in the chosen field”. ACADEMICS COURSES INSTITUTIONS BOARD YEAR OF PASSING % MBA (Marketing) XYZ School of Mgt. Bangalore University 2015 B.Com Name of College Name of university 2013 PUC (12th std) Name of College Name of university 2010 SSLC (10th std) Name of School Name of university 2008 PROJECTS (write a brief outline about your project, it should be structured & should highlight those points which would be beneficial for the current position’s interview) For example: Name of Co. : Western India Plywood’s ltd. Project Title : HR internship Project Outline : WIP is a public company which was started in the year 1945 and deals in the manufacturing and sales of both of plywood’s and hardwoods. The internship at Western India Plywood’s Ltd was for the duration of 3 month. During the tenure, I have hands on work in the areas mentioned below. • Functions of various departments in a company. • Assisted in the HR functionalities like Payroll database, Data Mining etc... • Was a part of the Exposure to launch an advertising campaign to attract more customers. PROFESSIONAL CERTIFICATIONS (Whatever certifications you have completed with relevant certificates &Specialisation). • Completed Advance Excel course from…..( Name of Institution / Centre ) • Completed Finance certification course …..( Name of Institution / Centre ) • SAP – (Domain specific: FICO, HCM, MM etc….) • Certified Six Sigma – Orange Belt, passed with distinction ACCOLADES ( Any awards and recognitions received ) • Presented Papers in the College / Inter College Journals • Represented College in Management Programs & Seminars • Nominated as the Best Student for….(any awards you can mention) COMPUTER PROFICIENCY (only if you have done some course or diploma) • Sound Knowledge in ERP, SAP Platforms • JAVA , C++ courses PERSONAL SKILLS (Write strengths based on your Major / minor specialisation, you can also relate your skills to the projects or events who might be part of & highlight them during an interview ) • Effective Client Relations • Quick Learner • Self Confidence & Positive Attitude • Ability to perform & contribute under pressure • Flexible & Adaptable to changes & challenges • Highly Self Motivated • Ability to work with Team EXTRA CURRICULAR ACTIVITES • Involved in raising Funds for NGOs • Participated in various Cultural Committee Development activities • Involved in CSR assignments for the college • Participated in Dance & Sports events conducted in Colleges • Participated in Management Fest & Inter College a Fests PERSONAL DOSSIER • Date of Birth : (Your Date of Birth) • Gender : Male/Female • Linguistic Proficiency : Read: - English, Hindi, (language u know to read only) Write: - English, Hindi (languages u know to write only) • LinkedIn Profile : ( Paste the Url link ) • Twitter Profile : ( Paste the Url link ) Declaration: I hereby declare that the information furnished above is true and to the best of my knowledge & belief. Place: Date: (FULL NAME) Disclaimer: The content written and spoken in this video are the soul property of Cassius Technologies Pvt Ltd. In case of any resemblance to any sites or any videos are mere coincidence.
Data Analysis in SPSS Made Easy
 
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Use simple data analysis techniques in SPSS to analyze survey questions.
Views: 835487 Claus Ebster
5 Sample Healthcare BI Reports
 
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Step Through 5 Sample Healthcare Business Intelligence Reports in 5 Minutes
Views: 73 US Medical IT
Data Warehouse tutorial. Creating an ETL.
 
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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
MDX Query Basics (Analysis Services 2012)
 
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This video is part of LearnItFirst's SQL Server 2012: A Comprehensive Introduction course. More information on this video and course is available here: http://www.learnitfirst.com/Course170 In this video, we walk through the basics of the MDX Query language. It is a very logical language, however, is somewhat large in syntax. If you enjoy writing Transact-SQL, you will really enjoy the MDX language. The AdventureWorks2012 multidimensional models need to be installed on your SSAS Multidimensional mode instance from the CodePlex web site. Highlights from this video: - The basics of an MDX query - What is the basic format of the MDX query language? - Is it necessary to have a WHERE clause in an MDX query? - How to signal the end of a statement in the MDX query language - Using the Internet Order Count and much more...
Views: 107044 LearnItFirst.com
Overall Explanation of Hong Kong IT Job Advertisement Data Mining Report
 
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Briefly tell the background and explain the logic of the Hong Kong IT Job Advertisement Data Mining Report. http://itjobanalysis.data-hk.com/
Views: 337 Cyrus Wong
Build A Complete Project In Machine Learning | Credit Card Fraud Detection | Eduonix
 
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Look what we have for you! Another complete project in Machine Learning! In today's tutorial, we will be building a Credit Card Fraud Detection System from scratch! It is going to be a very interesting project to learn! It is one of the 10 projects from our course 'Projects in Machine Learning' which is currently running on Kickstarter. For this project, we will be using the several methods of Anomaly detection with Probability Densities. We will be implementing the two major algorithms namely, 1. A local out wire factor to calculate anomaly scores. 2. Isolation forced algorithm. To get started we will first build a dataset of over 280,000 credit card transactions to work on! You can access the source code of this tutorial here: https://github.com/eduonix/creditcardML Want to learn Machine learning in detail? Then try our course Machine Learning For Absolute Beginners. Apply coupon code "YOUTUBE10" to get this course for $10 http://bit.ly/2Mi5IuP Kickstarter Campaign on AI and ML E-Degree is Launched. Back this Campaign and Explore all the Courses with over 58 Hours of Learning. Link- http://bit.ly/aimledegree Thank you for watching! We’d love to know your thoughts in the comments section below. Also, don’t forget to hit the ‘like’ button and ‘subscribe’ to ‘Eduonix Learning Solutions’ for regular updates. https://goo.gl/BCmVLG Follow Eduonix on other social networks: ■ Facebook: http://bit.ly/2nL2p59 ■ Linkedin: http://bit.ly/2nKWhKa ■ Instagram: http://bit.ly/2nL8TRu | @eduonix ■ Twitter: http://bit.ly/2eKnxq8
SSAS: Getting Started with the Table Analysis Tools - Data Mining Add-Ins
 
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This video will help you get started with the Data Mining Table Analysis Tools add-in for Excel 2007 by showing you how to open the tools, use the sample Excel data, and connect to an Analysis Services server. See the Video Transcript: http://msdn.microsoft.com/en-us/library/dd299412.aspx
Views: 10239 sqlserver
What is SSIS , SSAS and SSRS ( part 1)  with sample demo?
 
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For more such videos visit http://www.questpond.com See our other Step by Step video series below :- Learn angular tutorial for beginners https://tinyurl.com/ycd9j895 Learn MVC Core step by step :- http://tinyurl.com/y9jt3wkv Learn MVC 5 Step by Step in 16 hours:- https://goo.gl/dmdakg Learn MSBI Step by Step in 32 hours:- https://goo.gl/TTpFZN Learn Xamarin Mobile Programming Step by Step :- https://goo.gl/WDVFuy Learn Design Pattern Step by Step in 8 hours:- https://goo.gl/eJdn0m Learn C# Step by Step in 100 hours :- https://goo.gl/FNlqn3 Learn Data structures & algorithm in 8 hours :-https://tinyurl.com/ybx29c5s Learn SQL Server Step by Step in 16 hours:- http://tinyurl.com/ja4zmwu Learn Javascript in 2 hours :- http://tinyurl.com/zkljbdl Learn SharePoint Step by Step in 8 hours:- https://goo.gl/XQKHeP Learn TypeScript in 45 Minutes :- https://goo.gl/oRkawI Learn webpack in 50 minutes:- https://goo.gl/ab7VJi Learn Visual Studio code in 10 steps for beginners:- https://tinyurl.com/lwgv8r8 Learn Tableau step by step :- https://tinyurl.com/kh6ojyo =============================================== Learn MSBI in 4 days with Project ============================ Lab 1 :- MSBI Fundamentals, Data flow, Control Flow, ETL, Dataware house. (SSIS) :- https://youtu.be/mGPJx3ocFgg Lab 2:- Conditional split, Data conversion and Error handling. (SSIS) Lab 3:- For Loop, Variables, Parameters and Debugging. (SSIS) Lab 4:- Packaging and Deployment, File component and running SSIS package as a task.(SSIS) Lab 5: - For dimension, measures, star schema, snow flake, shared connection managers & packages tasks.(SSIS) Lab 6:- SCD, Type 0, Type 1, OLEDB Command and Unicode conversions.(SSIS) Lab 7:- Lookup, Data conversion optimization and updating SSIS package.(SSIS) Lab 8:- Sort, Merge and Merge Joins.(SSIS) Lab 9 :- Creating SSAS Cube. (SSAS) Lab 10:- SSAS Time series and Excel display.(SSAS) Lab11: - What are Transactions and CheckPoints in SSIS? (SSIS) Lab12: - Simple SSRS report & implementing Matrix, Tabular, Parameters, Sorting, Expressions. (SSRS) Lab 13:- Using Data Profiling task to check data quality. (SSIS) Lab 14:- Hierarchical Dimensions. (SSAS) Lab 15:- WebServices and XML Task. (SSIS) Lab16:- DrillDown and Subreports. (SSRS) Lab17 :- SSAS KPI (Key Performance Indicators). (SSAS) Lab 18:- Pivot, UnPivot and Aggregation. (SSIS) Lab 19 :- SSAS Calculation.(SSAS) Lab 20:- SQL Execute Task. (SSIS) Lab 21:- Reference and Many-to-Many Relationship. (SSAS) Lab 22 :- Script Task and Send Mail Task. (SSIS) Lab 23 :- Script component(SSIS) Lab 24 :- Bar chart, Gauge and Indicators.(SSRS) Lab 25:- Partitions in SSAS. (SSAS) Lab 26 :- CDC(Changed Data Capture) in SSIS. (SSIS) Lab 27:- Additive, Semiadditive and non-additive measures in SSAS.(SSAS) Lab 28:- Buffer Size Tuning (SSIS) Lab 29 :- How to implement Multithreading in SSIS?(SSIS) Lab 30:- Processing SSAS cube in background.(SSAS) Lab 31 :- Explain Asynchronous, Synchronous, Full, Semi and Non blocking Components. (SSIS) Lab 32 :- SSRS Architecture and Deployment (SSRS) Lab 33 :- DQS( Data Quality Services ) (SSIS) Lab 34 :- Explain Tabular Model and Power Pivot (SSAS). Lab 35 :- MDX (Multidimensional Expressions) Queries.(SSAS) Lab 36 :- Data Mining (Fundamentals and Time Series Algorithm).(SSAS) Lab 37 :- Page Split and Performance issues with SSIS.(SSIS) Lab 38 :- Aggregations in SSAS.(SSAS) Lab 39 :- ROLAP, MOLAP and HOLAP.(SSAS) Lab 40 :- Instrumentation using Data Taps (SSIS). Lab 41:- Lookup caching modes and Cache Transform. (SSAS) Lab 42: - Perspectives & Translations. (SSAS) Lab 43 :- Tabular Training 1 :- Installation, Xvelocity, Vertipaq, DAX,Creating cubes,measures, KPI, Partition and Translation? In this video we will try to understand what is SSIS , SSRS and SSAS, We also see a sample demo of ETL ( Extraction transformation and loading). This video series is for people who wants to Microsoft business intelligence. We are also distributing a 200 page Ebook "Learn MSBI (SSIS, SSRS, SSAS) Step by step". If you want this ebook please share this video in your facebook/twitter/linkedin account and email us on [email protected] with the shared link and we will email you the PDF. Buy Questpond videos on discount - http://www.itfunda.com/Interview
SSAS: Fill from Example - Data Mining Add-In
 
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In this tutorial we will learn how to use the Fill From Example Table Analysis Tool for Excel. Read the video transcript: http://msdn.microsoft.com/en-us/library/dd299418.aspx
Views: 3262 sqlserver
Logistic Regression Using Excel
 
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Predict who survives the Titanic disaster using Excel. Logistic regression allows us to predict a categorical outcome using categorical and numeric data. For example, we might want to decide which college alumni will agree to make a donation based on their age, gender, graduation date, and prior history of donating. Or we might want to predict whether or not a loan will default based on credit score, purpose of the loan, geographic location, marital status, and income. Logistic regression will allow us to use the information we have to predict the likelihood of the event we're interested in. Linear Regression helps us answer the question, "What value should we expect?" while logistic regression tells us "How likely is it?" Given a set of inputs, a logistic regression equation will return a value between 0 and 1, representing the probability that the event will occur. Based on that probability, we might then choose to either take or not take a particular action. For example, we might decide that if the likelihood that an alumni will donate is below 5%, then we're not going to ask them for a donation. Or if the probability of default on a loan is above 20%, then we might refuse to issue a loan or offer it at a higher interest rate. How we choose the cutoff depends on a cost-benefit analysis. For example, even if there is only a 10% chance of an alumni donating, but the call only takes two minutes and the average donation is 100 dollars, it is probably worthwhile to call.
Views: 181738 Data Analysis Videos
Simple Explanation of Chi-Squared
 
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An explanation of how to compute the chi-squared statistic for independent measures of nominal data. For an explanation of significance testing in general, see http://evc-cit.info/psych018/hyptest/index.html There is also a chi-squared calculator at http://evc-cit.info/psych018/chisquared/index.html
Views: 953020 J David Eisenberg
Become an Excel Wizard With Python
 
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In this talk, we will explore how the Python's openpyxl module allows your Python programs to read and modify Excel spreadsheet files. By using Python, you can take your Excel and data manipulation skills to the whole new level. PERMISSIONS: The original video was published on Six Feet Up Corp YouTube channel with the Creative Commons Attribution license (reuse allowed). CREDITS: Original video source: https://www.youtube.com/watch?v=ueq1iTWQU5U Additional recommended material for Python learners: https://amzn.to/2UMFhRt Python Programming: A Step By Step Guide From Beginner To Expert https://amzn.to/2JsiyZX A Smarter Way to Learn Python: Learn it faster. Remember it longer. https://amzn.to/2CwoGKu Python Crash Course: A Hands-On, Project-Based Introduction to Programming https://amzn.to/2Fi4cG9 Python Programming: An Introduction to Computer Science
Views: 244018 Coding Tech
Linear Regression in R | Linear Regression in R With Example | Data Science Algorithms | Simplilearn
 
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This "Linear regression in R" video will help you understand what is linear regression, why linear regression, you will see how linear regression works using a simple example and you will also see a use case predicting the revenue of a company using linear regression. Linear Regression is the statistical model used to predict the relationship between independent and dependent variables by examining two factors. The first one is which variables, in particular, are significant predictors of the outcome variable and the second one is how significant is the regression line to make predictions with the highest possible accuracy. Now, lets deep dive into this video and understand what is linear regression. Below topics are explained in this "Linear Regression in R" video: 1. Why linear regression? ( 00:28 ) 2. What is linear regression? ( 03:09 ) 3. How linear regression works? ( 03:48 ) 4. Use case - Predicting the revenue using linear regression (10:05) To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 You can also go through the Slides here: https://goo.gl/HBso29 Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning Become an expert in data analytics using the R programming language in this data science certification training course. You’ll master data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language. With this data science course, you’ll get hands-on practice on R CloudLab by implementing various real-life, industry-based projects in the domains of healthcare, retail, insurance, finance, airlines, music industry, and unemployment. Why learn Data Science with R? 1. This course forms an ideal package for aspiring data analysts aspiring to build a successful career in analytics/data science. By the end of this training, participants will acquire a 360-degree overview of business analytics and R by mastering concepts like data exploration, data visualization, predictive analytics, etc 2. According to marketsandmarkets.com, the advanced analytics market will be worth $29.53 Billion by 2019 3. Wired.com points to a report by Glassdoor that the average salary of a data scientist is $118,709 4. Randstad reports that pay hikes in the analytics industry are 50% higher than IT The Data Science Certification with R has been designed to give you in-depth knowledge of the various data analytics techniques that can be performed using R. The data science course is packed with real-life projects and case studies, and includes R CloudLab for practice. 1. Mastering R language: The data science course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R. 2. Mastering advanced statistical concepts: The data science training course also includes various statistical concepts such as linear and logistic regression, cluster analysis and forecasting. You will also learn hypothesis testing. 3. As a part of the data science with R training course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and the Internet. Four additional projects are also available for further practice. The Data Science with R is recommended for: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields Learn more at: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Linear-Regression-in-R-2Sb1Gvo5si8&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn/ - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 6653 Simplilearn
Build an Accounts Receivable Aging Report in Excel
 
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A viewer asked my help in building an A/R Aging Report. She wants to see the total for invoices that are "past due" 1 - 30 days, 31-60 days, etc. In this video I use the =TODAY(), =IF(), =AND() and =WEEKDAY() functions to build this report. If you have an Excel question, send it to me, I will answer it as soon as I possibly can do so. My DVD-ROM, "The 50 Best Tips, Tricks & Techniques for Excel 2007" is now available for sale. Visit my website - www.thecompanyrocks.com/excels - for details on how to purchase it.
Views: 184870 Danny Rocks
SQL Server 2008/R2 Analysis Services Data Mining: An Intro
 
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This video is part of LearnItFirst's SQL Server 2008/R2 Analysis Services course. More information on this video and course is available here: http://www.learnitfirst.com/Course165 Now, Scott will talk about putting Analysis Services and data mining together. He explains that there are really two parts to Analysis Services: the multidimensional part, and the data mining part, although most people just work with the multidimensional part. You will see the many uses for data mining, and get more comfortable with the basics before learning some terms in videos later in the chapter. Highlights from this video: - What can you do with SSAS and data mining? - Do you need anything other than SSAS to do data mining? - The data mining language - Example data mining reports - How much work is data mining? and much more...
Views: 28809 LearnItFirst.com