Learn about data problems with multiple examples and the data QA process. The volume is low. Please click the Cc button to see subtitles in English. Next, view VBScript tutorials at https://www.youtube.com/watch?v=03BfHDJsFpk&index=1&list=PLc3SzDYhhiGXH8hEHtayRPdwAsddelkh6 Follow me on: Website: http://inderpsingh.blogspot.com/ Google+: https://plus.google.com/+InderPSingh Twitter: https://twitter.com/inder_p_singh
Views: 13994 Software and Testing Training
Time Series data Mining Using the Matrix Profile: A Unifying View of Motif Discovery, Anomaly Detection, Segmentation, Classification, Clustering and Similarity Joins Part 1 Authors: Abdullah Al Mueen, Department of Computer Science, University of New Mexico Eamonn Keogh, Department of Computer Science and Engineering, University of California, Riverside Abstract: The Matrix Profile (and the algorithms to compute it: STAMP, STAMPI, STOMP, SCRIMP and GPU-STOMP), has the potential to revolutionize time series data mining because of its generality, versatility, simplicity and scalability. In particular it has implications for time series motif discovery, time series joins, shapelet discovery (classification), density estimation, semantic segmentation, visualization, clustering etc. Link to tutorial: http://www.cs.ucr.edu/~eamonn/MatrixProfile.html More on http://www.kdd.org/kdd2017/ KDD2017 Conference is published on http://videolectures.net/
Views: 2486 KDD2017 video
In this episode of AI Adventures, Yufeng explores the fascinating world of pandas, an open-source python library that provides easy to use, high-performance data structures and data analysis tools. Associated Medium post "Wrangling data with Pandas": https://goo.gl/txENbw Pandas: http://pandas.pydata.org/ Watch more episodes of AI Adventures: https://goo.gl/UC5usG Subscribe to get all the episodes as they come out: https://goo.gl/S0AS51
Views: 39207 Google Cloud Platform
***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** Data quality assurance is the process of profiling the data to discover inconsistencies and other anomalies in the data, as well as performing data cleansing activities (e.g. removing outliers, missing data interpolation) to improve the data quality . These activities can be undertaken as part of data warehousing or as part of the database administration of an existing piece of applications software. Video covers the following topics : 1.Data Quality Concept 2Error Handling Concepts 3.ETL Summary 4.Data Extraction 5.Data Transform 6.Data Loading 7.What is Data warehouse? 8.Data warehouse Architecture 9.Why Data warehouse is used? Related Blogs: http://www.edureka.co/blog/a-brief-on-etl/?utm_source=youtube&utm_medium=referral&utm_campaign=data-quality-concept http://www.edureka.co/blog/architecture-of-a-data-warehouse/?utm_source=youtube&utm_medium=referral&utm_campaign=data-quality-concept 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. The topics related to ‘Introduction to Dataware Housing’ have been covered in our course ‘Datawarehousing‘. 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: 24511 edureka!
None-- Created using PowToon -- Free sign up at http://www.powtoon.com/ . Make your own animated videos and animated presentations for free. PowToon is a free tool that allows you to develop cool animated clips and animated presentations for your website, office meeting, sales pitch, nonprofit fundraiser, product launch, video resume, or anything else you could use an animated explainer video. PowToon's animation templates help you create animated presentations and animated explainer videos from scratch. Anyone can produce awesome animations quickly with PowToon, without the cost or hassle other professional animation services require.
Views: 2605 Afiq Zaimi
In this critical analysis of data mining effects on individual privacy the topics that are focused on include marketing data mining, medical data mining, and privacy concerns and ethics about data mining. In sequence, this paper is organized as follows. Section 2 provides the background information and significance of data mining for the past and future. Section 3 opens the discussion with marketing data mining and how the Corporate Industrial Complex is already profiting off of data mining with no regards for individual privacy. Section 4 continues the discussion with medical data mining, a hot button issue for most Americans, by analyzing the current situation, looking at the need for data mining, and the possible threats to individual privacy. Section 5 ends the discussion with privacy concerns and ethics about data mining by comparing and contrasting the views of Americans and Europeans. Finally, Section 6 will summarize the paper and recap some of the main topic in the discussion about data mining effect on individual privacy. Tools used: Prezis Screenomatic basic upload to youtube
Views: 1056 Terry Henderson
A quick tutorial for the data profiling tool Datamartist that gives and example of a value distribution data profile. Datamartist provides a flexible, easy to use ETL and data profiling tool that lets you get at your data.
Views: 453 Datamartist
Welcome back to Growth Insights! In this latest episode (number 5 already?!) we’ll be sharing Lead Generation Techniques & Data Visualisation Tools - Growth Insights #5. The Growth Insights series is our jam-packed, fast-paced video format in which we’ll introduce you to the growth tools, techniques and hacks our team has come across over the past few weeks. All under 7 minutes on a tri-weekly basis. This particular episode focuses on Lead Generation Techniques & Data Visualisation Tools. If you come across a tool, website or article mentioned in the video that you want to look into further, check out the links below! 0:16 - Dux Soup https://www.dux-soup.com/ 0:37 - Grouply https://grouply.io/ 0:54 - Revealbot https://revealbot.com/ 1:18 - Instanobel https://www.instanobel.com/ 1:29 - Data Gif Maker https://datagifmaker.withgoogle.com/ 1:43 - Free open Slack channels a plenty! http://bit.ly/1000slack 1:55 - Chatviz https://moovel.github.io/teamchatviz/ 2:08 - Statista’s Referral graph http://bit.ly/2qusuUI 2:10 - Chart: How much time adults spend online http://www.kpcb.com/internet-trends 2:53 - Ecommerce benchmarks analysis http://bit.ly/2t1PFL2 3:10 - Add this to the end of a competitor’s shopify store URL to see their top selling products: /collections/all?sort_by=best-selling&page=1 3:41 - Referral traffic: search vs browse http://bit.ly/1MrgOV9 3:58 - Create a brand identity in 60 seconds with http://www.hipsterbusiness.name & https://builtbyemblem.com/ 5:13 - How important is retention? Read: http://bit.ly/1xH1n5b 5:26 - Data visualisation tool https://lists.design/ 5:40 - Andy Carvell’s push notifications quadrant http://bit.ly/2sIJecx 6:30 - Sign up for our first beta AI course here: grow.ac/aicourse 6:34 - Don’t forget to subscribe! https://www.youtube.com/channel/UCj6owuAZrJNsjQzc2ZtILIw?sub_confirmation=1 In this episode of our Growth Insights series we also cover: - lead generation automation - Facebook ad automation - AdWords automation - instagram automation tool - Instanobel - data gifmaker - public slack groups - community visualisation - referral traffic trends - E commerce benchmarks - competitor analysis hacks - how to create a brand identity in 60 sec - brand identity tools - data visualisation - push notifications framework ------------------------------------------------------- Amsterdam bound? Want to make AI your secret weapon? Join our A.I. for Marketing and growth Course! A 2-day course in Amsterdam. No previous skills or coding required! https://hubs.ly/H0dkN4W0 OR Check out our 2-day intensive, no-bullshit, skills and knowledge Growth Hacking Crash Course: https://hubs.ly/H0dkN4W0 OR our 6-Week Growth Hacking Evening Course: https://hubs.ly/H0dkN4W0 OR Our In-House Training Programs: https://hubs.ly/H0dkN4W0 OR The world’s only Growth & A.I. Traineeship https://hubs.ly/H0dkN4W0 Make sure to check out our website to learn more about us and for more goodies: https://hubs.ly/H0dkN4W0 London Bound? Join our 2-day intensive, no-bullshit, skills and knowledge Growth Marketing Course: https://hubs.ly/H0dkN4W0 ALSO! Connect with Growth Tribe on social media and stay tuned for nuggets of wisdom, updates and more: Facebook: https://www.facebook.com/GrowthTribeIO/ LinkedIn: https://www.linkedin.com/company/growth-tribe Twitter: https://twitter.com/GrowthTribe/ Instagram: https://www.instagram.com/growthtribe/ Video URL: https://youtu.be/-1mMoO0UZ_E -~-~~-~~~-~~-~- Please watch: "Artificial Intelligence Tools & Cold Emailing Tips - Growth Insights #8 " https://www.youtube.com/watch?v=mCp5zYl3hD4 -~-~~-~~~-~~-~-
Views: 9908 Growth Tribe
SQL Server Integration Services (SSIS) can be used to apply Data Mining predictions. This tutorial demonstrates how to use the SSIS "Data Mining Query" to predictive the risk of having a vehicle using profile information stored in a SQL Server table. I also have a comprehensive 60 minute T-SQL course available at Udemy : https://www.udemy.com/t-sql-for-data-analysts/?couponCode=ANALYTICS50%25OFF
Views: 7749 Steve Fox
This workshop will cover regression analysis concepts for the analysis of geographic data. Using these statistical methods in many areas (e.g., business, public health, natural resources) allows you to examine, model, and explore data relationships to help answer questions such as “why do we see so much disease in particular areas?” Regression analysis also allows you to predict spatial outcomes for other places or time periods. Application and use of ordinary least squares regression (OLS) and geographically weighted regression (GWR) will be demonstrated. You will learn how to build a properly specified OLS model and interpret the results and diagnostics. The latest advancements in regression and prediction in ArcGIS will be covered.
Views: 1428 Esri Events
http://www.sas.com/vdmml Boost analytical productivity and solve your most complex problems faster with a single, integrated in-memory environment that's both open and scalable. SAS VISUAL DATA MINING AND MACHINE LEARNING SAS Visual Data Mining and Machine Learning supports the end-to-end data mining and machine-learning process with a comprehensive, visual (and programming) interface that handles all tasks in the analytical life cycle. It suits a variety of users and there is no application switching. From data management to model development and deployment, everyone works in the same, integrated environment. http://www.sas.com/vdmml SUBSCRIBE TO THE SAS SOFTWARE YOUTUBE CHANNEL http://www.youtube.com/subscription_center?add_user=sassoftware ABOUT SAS SAS is the leader in analytics. Through innovative analytics, business intelligence and data management software and services, SAS helps customers at more than 75,000 sites make 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: 5112 SAS Software
Enroll in the course for free at: https://bigdatauniversity.com/courses/data-science-methodology-2/ Data Science Methodology Grab you lab coat, beakers, and pocket calculator…wait what? wrong path! Fast forward and get in line with emerging data science methodologies that are in use and are making waves or rather predicting and determining which wave is coming and which one has just passed. Connect with Big Data University: https://www.facebook.com/bigdatauniversity https://twitter.com/bigdatau https://www.linkedin.com/groups/4060416/profile ABOUT THIS COURSE •This course is free. •It is self-paced. •It can be taken at any time. •It can be audited as many times as you wish. Learn the major steps involved in tackling a data science problem. Learn the major steps involved in practicing data science, with interesting real-world examples at each step: from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment. https://bigdatauniversity.com/courses/data-science-methodology-2/
Views: 7017 Cognitive Class
Segmentation (Targeting, Profiling, Classification) is the process of dividing a database into distinct groups of individuals who share common characteristics. This is readily accomplished using modern data mining and machine learning techniques. The methods are easily implemented and work well with large datasets containing nonlinearities, interactions in the data and a mix of categorical and numerical variables. In this webinar, you will learn, via step-by-step instruction, how to use modern techniques to: 1) Segment a large database AND 2) Look at an already segmented/clustered database and discover the reasons for the class memberships. Access the data set, slides, and step-by-step guide here: http://info.salford-systems.com/customer-segmentation-webinar http://www.salford-systems.com
Views: 1004 Salford Systems
What information do social media websites really collect and store about you? I will show you how to access that data from a few different social media pages and analyse it for your own use, even if you've never used python data analytics tools before! EVENT: PyCon Australia (“PyCon AU”) 2018 SPEAKER: Caitlin Macleod PERMISSIONS: Original video was published with the Creative Commons Attribution license (reuse allowed). CREDITS: Original video source: https://www.youtube.com/watch?v=JNZH95aXNXo
Views: 3152 Coding Tech
This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2w2lQqE]. The aim of this video is to deal with Business Intelligence. It will use Apache POI for creating and reading spreadsheets, as well as show what users will do in MS Excel o Understand why as a data analyst, you need to save time using MS Excel o Perform some reads and writes of existing MS Excel spreadsheets For the latest Big Data and Business Intelligence video tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 2493 Packt Video
By using advanced analytics to create your segmentation strategies, you can: - Identify your most proitable customers - Focus your marketing on segments most likely to purchase - Discover potential niche markets - Develop or improve products to meet customer needs For more information visit http://www.angoss.com/predictive-analytics-software/applications/customer-analytics/
Views: 24135 AngossSoftware
The Society of Data Miners, in association with the Alan Turing Institute, is delighted to announce the second in a series of practitioner seminars. This talk will discuss the challenges of mining Police data to provide operational intelligence. Rick will introduce the data and systems involved in day-to-day reporting, resource tasking and arresting offenders, including the issues of linking data across systems and the challenges of extracting useful information from free text. Digging into more advanced analytics, Rick will discuss criminal network analysis or CNA, an important tool in crime prevention and detection, and the differences between analysing overt networks (SNA) and covert networks (CNA). Rick will describe how supervised and unsupervised learning methods have been used in the identification of prolific and priority offenders, and how the results are used to solve crimes and target offenders, and to use resources effectively. Finally Rick will describe the EU-funded FP7 project Valcri (www.valcri.org), and its task to provide a Police data set that is suitable for release into the research community. Rick Adderley Bio: Rick is a retired Police Officer having served for 32 years in an operational capacity. His legacy to the Service is an intelligence product which was developed for the West Midlands region and is now used by all UK Police Forces; he specialises in profiling criminal activity. Rick retired in 2003 and started his data mining company, A E Solutions, focusing within the UK Emergency Services arena. Rick is also a director of the Society of Data Miners.
Views: 979 The Alan Turing Institute
Why do so many companies make bad decisions, even with access to unprecedented amounts of data? With stories from Nokia to Netflix to the oracles of ancient Greece, Tricia Wang demystifies big data and identifies its pitfalls, suggesting that we focus instead on "thick data" -- precious, unquantifiable insights from actual people -- to make the right business decisions and thrive in the unknown. Check out more TED talks: http://www.ted.com The TED Talks channel features the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and more. Follow TED on Twitter: http://www.twitter.com/TEDTalks Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: https://www.youtube.com/TED
Views: 100101 TED
What is Data Mining? How is it different from Statistics? This video was created by Professor Galit Shmueli and has been used as part of blended and online courses on Business Analytics using Data Mining. It is part of a series of 37 videos, all of which are available on YouTube. For more information: http://www.dataminingbook.com https://www.twitter.com/gshmueli https://www.facebook.com/dataminingbook Here is the complete list of the videos: • Welcome to Business Analytics Using Data Mining (BADM) • BADM 1.1: Data Mining Applications • BADM 1.2: Data Mining in a Nutshell • BADM 1.3: The Holdout Set • BADM 2.1: Data Visualization • BADM 2.2: Data Preparation • BADM 3.1: PCA Part 1 • BADM 3.2: PCA Part 2 • BADM 3.3: Dimension Reduction Approaches • BADM 4.1: Linear Regression for Descriptive Modeling Part 1 • BADM 4.2 Linear Regression for Descriptive Modeling Part 2 • BADM 4.3 Linear Regression for Prediction Part 1 • BADM 4.4 Linear Regression for Prediction Part 2 • BADM 5.1 Clustering Examples • BADM 5.2 Hierarchical Clustering Part 1 • BADM 5.3 Hierarchical Clustering Part 2 • BADM 5.4 K-Means Clustering • BADM 6.1 Classification Goals • BADM 6.2 Classification Performance Part 1: The Naive Rule • BADM 6.3 Classification Performance Part 2 • BADM 6.4 Classification Performance Part 3 • BADM 7.1 K-Nearest Neighbors • BADM 7.2 Naive Bayes • BADM 8.1 Classification and Regression Trees Part 1 • BADM 8.2 Classification and Regression Trees Part 2 • BADM 8.3 Classification and Regression Trees Part 3 • BADM 9.1 Logistic Regression for Profiling • BADM 9.2 Logistic Regression for Classification • BADM 10 Multi-Class Classification • BADM 11 Ensembles • BADM 12.1 Association Rules Part 1 • BADM 12.2 Association Rules Part 2 • Neural Networks: Part I • Neural Networks: Part II • Discriminant Analysis (Part 1) • Discriminant Analysis: Statistical Distance (Part 2) • Discriminant Analysis: Misclassification costs and over-sampling (Part 3)
Views: 1214 Galit Shmueli
How to set up connection's between different widgets in Orange(Data Mining Tool) to perform Hierarchical Clustering.
Views: 313 Kanak Agarwal
This video aims to provide an overview of #ETL (Extract Load Transformation ) process and covers: #extraction Process and its Strategies Transformation and various tasks performed Loading Process and its Strategies ETL tools and its features. ETL Tools: Talend Open Studio, Jaspersoft ETL, Ab initio, Informatica, Datastage, Clover ETL, Pentaho ETL, Kettle ETL Tools Features: Source and Target Data System Connectivity Scalability and Performance Easy Transformation connectors Data Profiling Data Cleaning and Quality Easy integration with Web services Logging and Exception Handling Robust Administration features Efficient Batch and Real time processing For more details visit: http://www.vikramtakkar.com/2015/10/what-is-etl-extract-transformation-and.html Datawarehouse Playlist: https://www.youtube.com/playlist?list=PLJ4bGndMaa8FV7nrvKXeHCLRMmIXVCyOG
Views: 109396 Vikram Takkar
What is data mining? The Oracle Data Miner tutorial presents data mining introduction. Learn data mining techniques. More lessons, visit http://www.learn-with-video-tutorials.com/oracle-data-mining-tutorial-video
Views: 32813 Learn with video tutorials
An Introduction to Data Quality Profiling and Scorecards by Robert Whelan.He is an expert in Data Quality. DQ version 9.6
Views: 8854 dataUtrust
WANT TO EXPERIENCE A TALK LIKE THIS LIVE? Barcelona: https://www.datacouncil.ai/barcelona New York City: https://www.datacouncil.ai/new-york-city San Francisco: https://www.datacouncil.ai/san-francisco Singapore: https://www.datacouncil.ai/singapore Download slides of this talk: https://www.dataengconf.com/speaker/dbt-powerful-open-source-data-transformations?utm_source=youtube&utm_medium=social&utm_campaign=%20-%20DEC-BCN-18%20Slides%20Download ABOUT THE TALK: Fishtown Analytics works with companies like Casper, Invision, Away Travel, and many more to help them build out effective analytics practices. These companies have complex data sets that are best understood by their analysts and business users (not their engineers!). To empower these users, the team at Fishtown Analytics has built dbt, an open source data transformation and democratization tool. It allows analysts and other non-engineers to write data transformations, while giving data engineers the ability to govern the process and ensure data quality. In this talk, we'll explore the key practices that make this setup work, including continuous integration, data lineage, quality testing, and documentation. ABOUT THE SPEAKER: Connor is a co-founder and resident Data Engineer at Fishtown Analytics, where he is developing open source tools to empower data engineers and analysts. In a past life, he engineered and maintained multi-tenant, petabyte-scale data pipelines which power analytics for hundreds of data-savvy internet companies. FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai Facebook: https://www.facebook.com/datacouncilai
Views: 1002 Data Council
http://www.sas.com/enterpriseminer SAS Enterprise Miner streamlines data mining to create accurate predictive and descriptive models based on large volumes of enterprisewide data. SAS ENTERPRISE MINER Reveal valuable insights with powerful data mining software. Descriptive and predictive modeling provide insights that drive better decision making. Now you can streamline the data mining process to develop models quickly. Understand key relationships. And find the patterns that matter most. Looking for benefits? How about: * Build better models with the best tools. * Empower business users. * Improve prediction accuracy. Share reliable results. * Automate model deployment and scoring. LEARN MORE ABOUT SAS ENTERPRISE MINER http://www.sas.com/enterpriseminer 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: 101123 SAS Software
Speaker: Mao Ting Description By segmenting customers into groups with distinct patterns, businesses can target them more effectively with customized marketing and product features. I'll dive into a few machine learning and statistical techniques to extract insights from customer data, and demonstrate how to execute them on real data using Python and open-source libraries. Abstract I will go through clustering and decision tree analysis using sciki-learn and two-sample t test using scipy. We will learn the intuition for each technique, the math behind them, and how to implement them and evaluate the results using Python. I will be using open-source data for the demonstration, and show what insights you can extract from actual data using these techniques. Event Page: https://pycon.sg Produced by Engineers.SG Help us caption & translate this video! http://amara.org/v/P6SD/
Views: 16623 Engineers.SG
Data science can deliver transformational business insights by bringing together statistics, mathematics, computer science, machine learning, and business strategy. A variety of data science techniques are available which allow marketers to surface insights from large swathes of data, but which technique is right for your business and where do you start? In this on-demand webinar, our experts go over a broad range of data science techniques, and expose how major global brands are using them for valuable business insights including:customer lifetime value for customer segmentation and activation, forecasting and predictive analytics with machine learning, and natural language processing for digital marketing optimization
Views: 4147 Cardinal Path
To profile a Microsoft Excel™ File, watch this video. Learn to configure Data Profiling Rules, Interactively Analyse data by Drilling Down and Export Processing Flags Using Data Profiling Tool. http://acuate.com/dataprofiler/
Views: 2194 Anish Raivadera
Clustering Individual Transactional Data for Masses of Users Riccardo Guidotti (University of Pisa) Anna Monreale (University of Pisa) Mirco Nanni (KDD-Lab ISTI-CNR Pisa) Fosca Giannotti (ISTI-CNR) Dino Pedreschi (University of Pisa) Mining a large number of datasets recording human activities for making sense of individual data is the key enabler of a new wave of personalized knowledge-based services. In this paper we focus on the problem of clustering individual transactional data for a large mass of users. More on http://www.kdd.org/kdd2017/
Views: 4965 KDD2017 video
http://communities.sas.com/data-mining Brett Wujek talks about clustering, specifically about a relatively new methodology developed at SAS for determining a good or appropriate number of clusters for data called the Aligned Box Criterion, or ABC method. JOIN THE SAS DATA MINING COMMUNITY SAS Support Communities help users: Ask, Find and Share SAS knowledge. Join the SAS Data Mining Community today! http://communities.sas.com/data-mining SUBSCRIBE TO THE SAS SOFTWARE YOUTUBE CHANNEL http://www.youtube.com/subscription_center?add_user=sassoftware ABOUT SAS SAS is the leader in analytics. Through innovative analytics, business intelligence and data management software and services, SAS helps customers at more than 75,000 sites make 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: 9723 SAS Software
Recorded on 30 Oct 2013 at PASS Data Warehousing and Business Intelligence Virtual Chapter (PASS DW/BI VC) Data Lineage is the concept of enabling a client ability to analyze data in a NEW way yet still be able to see the original values, critical in Big Data. Ira Warren Whiteside and Victoria Stasiewicz will demonstrate how to do this in SSIS AND SSAS using Power Pivot, Power BI ,Office 365 and Power Query. We have several case studies for our current clients. Speakers: Ira Warren Whiteside, MDM Architect / BI Architect Ira has over 40 years of IT experience and has extensive knowledge of data warehousing. His roles have included management, Technical Team Lead, Business Analysis, Analytical Application Development, Data Wa rehousing Architecture, Data Modeling, Data Profiling, Data Mining, Text Mining, E-Commerce Implementation, Project Management, Decision Sup port/OLAP, Financial Application Development, E-Commerce, B2C, B2B with primary emphasis in Business Intelligence Applications and Data Warehousing Management. Mr. Whiteside has managed multi-million dollar projects from start to completion. His experience includes the planning, budgeting, project management/technical leadership and product management for large projects and software companies. In addition, Mr. Whiteside has been hands on, in that he has extensively used Microsoft SQL Server 2005/2012 tools, including SSIS, SSAS, SSRS (Microsoft Reporting Services) and Data mining. In addition Ira has authored and published various white papers, articles, provided numerous training seminars and presentations on the methodology required for data-driven application cogeneration in the Microsoft stack. Victoria Stasiewicz, Lead Data profiling Analyst and SSIS developer Victoria is a senior business analyst and data profiling analyst. She has extensive experience in the healthcare industry in analyzing and implementing the Sundial metric decomposition methodology as well as extensive experiencing in developing SSIS packages Join PASS DW/BI Virtual Chapter at http://bi.sqlpass.org Follow us on Twitter @PASSBIVC
Take a quick tour of DataCleaner - the premier commercial open source data quality solution. This video provides an overview of the applications user interface and a few features related to data profiling and cleansing. Be sure to visit www.datacleaner.org for more information.
Views: 5069 DataCleaner
What is CRIME ANALYSIS? What does CRIME ANALYSIS mean? CRIME ANALYSIS meaning - CRIME ANALYSIS definition - CRIME ANALYSIS explanation. SUBSCRIBE to our Google Earth flights channel - https://www.youtube.com/channel/UC6UuCPh7GrXznZi0Hz2YQnQ Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. Crime analysis is a law enforcement function that involves systematic analysis for identifying and analyzing patterns and trends in crime and disorder. Information on patterns can help law enforcement agencies deploy resources in a more effective manner, and assist detectives in identifying and apprehending suspects. Crime analysis also plays a role in devising solutions to crime problems, and formulating crime prevention strategies. Quantitative social science data analysis methods are part of the crime analysis process, though qualitative methods such as examining police report narratives also play a role. Crime analysis can occur at various levels, including tactical, operational, and strategic. Crime analysts study crime reports, arrests reports, and police calls for service to identify emerging patterns, series, and trends as quickly as possible. They analyze these phenomena for all relevant factors, sometimes predict or forecast future occurrences, and issue bulletins, reports, and alerts to their agencies. They then work with their police agencies to develop effective strategies and tactics to address crime and disorder. Other duties of crime analysts may include preparing statistics, data queries, or maps on demand; analyzing beat and shift configurations; preparing information for community or court presentations; answering questions from the public and the press; and providing data and information support for a police department's CompStat process. To see if a crime fits a certain known pattern or a new pattern is often tedious work of crime analysts, detectives or in small departments, police officers or deputies themselves. They must manually sift through piles of paperwork and evidence to predict, anticipate and hopefully prevent crime. The U.S. Department of Justice and the National Institute of Justice recently launched initiatives to support “predictive policing”, which is an empirical, data-driven approach. However this work to detect specific patterns of crime committed by an individual or group (crime series), remains a manual task. MIT doctoral student Tong Wang, Cambridge (Mass.) Police Department CPD Lieutenant Daniel Wagner, CPD crime analyst Rich Sevieri and Assoc. Prof. of Statistics at MIT Sloan School of Management and the co-author of Learning to Detect Patterns of Crime Cynthia Rudin have designed a machine learning method called “Series Finder” that can assist police in discovering crime series in a fraction of the time. Series Finder grows a pattern of crime, starting from a seed of two or more crimes. The Cambridge Police Department has one of the oldest crime analysis units in the world and their historical data was used to train Series Finder to detect housebreak patterns. The algorithm tries to construct a modus operandi (MO). The M.O. is a set of habits of a criminal and is a type of behavior used to characterize a pattern. The data of the burglaries include means of entry (front door, window, etc.), day of the week, characteristics of the property (apartment, house), and geographic proximity to other break-ins. Using nine known crime series of burglaries, Series Finder recovered most of the crimes within these patterns and also identified nine additional crimes. Machine learning is a tremendous tool for predictive policing. If patterns are identified the police can immediately try to stop them. Without such tools it can take weeks and even years of shifting though databases to discover a pattern. Series Finder provides an important data-driven approach to a very difficult problem in predictive policing. It’s the first mathematically principled approach to the automated learning of crime series.....
Views: 1260 The Audiopedia
We are the best web and mobile development organization in Germany that is inspired by cause to transform the thoughts into the reality. We build up the sites and portable applications that make the regularly enduring impressions and life-changing experiences. How about transforming the ideas into the greatest developments? Let's do it together. Comprehensive List of tools for Data Mining: 1- Rapid Miner 2- Weka 3- Orange 4- R 5- Knime 6- Rattle 7- Tanagra 8- XL Miner
Views: 98 MS Technologies
Data Mining with Weka: online course from the University of Waikato Class 2 - Lesson 2: Training and testing http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/D3ZVf8 https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 74133 WekaMOOC
Education Press Conference inspired by "Women on The Wall" please join them on Facebook.
Views: 48 J.D. Reeder
The Sintelix enterprise analytic platform thrives on unstructured data. Sintelix has been tailored to provide solutions for Law Enforcement, Intelligence and Defense. Learn more at www.sintelix.com General Introduction: 0:01 - 7:25 Out of the box ingestion demo: 7:25 - 15:30 Demonstration of search capabilities: 15:30 - 21:40 Harvester web and social media data mining: 21:40 - 29:00 Demonstration of configured projects in Sintelix 29:00 - 45:00
Views: 1054 Sintelix
This talk will be somewhere between academic and business talk. As an academic, I will explain the broad context of privacy and data protection related to data mining and predictive analytics and introduce the main theoretical dilemmas. However, the main part of my talk will focus on the practical side of implementation of GDPR: In that sense, I will present a general GDRP tool I created for easier implementation (https://prezi.com/gzz4d7dbfnrv/gdpr-tool-draft/). Presentation of the tool will be narrowed down to the topics of special interest related to the data mining and predictive analytics and their implications for implementation (profiling, monitoring of behaviour, types of processing, transparency, Principles DPO, DPIA, data subject rights ). This talk was presented by Mr. Djordje Krivokapic, Assistant professor at University of Belgrade, during Data Science Conference 4.0, as a part of Open Data track. More info about Data Science Conference: Website: http://datasciconference.com Instagram: https://www.instagram.com/datasciconf/ Facebook: https://www.facebook.com/DataSciConference/ Twitter: https://twitter.com/datasciconf Flickr: https://www.flickr.com/photos/data-science-conference To watch more new videos regarding Data Science - click subscribe to our YouTube Channel.
Views: 17 Institute of Contemporary Sciences
Description: In a presentation at the 2016 Concordia Annual Summit in New York, Mr. Alexander Nix discusses the power of big data in global elections. Cambridge Analytica’s revolutionary approach to audience targeting, data modeling, and psychographic profiling has made them a leader in behavioral microtargeting for election processes around the world. Speaker: Mr. Alexander Nix CEO, Cambridge Analytica
Views: 488349 Concordia
To find out more about our Online Training Courses, visit us at www.goodelearning.com, Use discount code: 'YT-SAVE15' to get 15% off any of our online courses! This course has been developed to provide the knowledge and understanding necessary to enable you to identify different customer groups. It will also show you how to understand the motivations, attitudes and behaviors of customers in those customer groups. You will be shown how to build profiles using existing customer groups as a basis. Good e-Learning are the leading provider of online training for business and IT professionals around the world.
Views: 7722 Good e-Learning