Search results “Analysis based on data”
Qualitative analysis of interview data: A step-by-step guide
The content applies to qualitative data analysis in general. Do not forget to share this Youtube link with your friends. The steps are also described in writing below (Click Show more): STEP 1, reading the transcripts 1.1. Browse through all transcripts, as a whole. 1.2. Make notes about your impressions. 1.3. Read the transcripts again, one by one. 1.4. Read very carefully, line by line. STEP 2, labeling relevant pieces 2.1. Label relevant words, phrases, sentences, or sections. 2.2. Labels can be about actions, activities, concepts, differences, opinions, processes, or whatever you think is relevant. 2.3. You might decide that something is relevant to code because: *it is repeated in several places; *it surprises you; *the interviewee explicitly states that it is important; *you have read about something similar in reports, e.g. scientific articles; *it reminds you of a theory or a concept; *or for some other reason that you think is relevant. You can use preconceived theories and concepts, be open-minded, aim for a description of things that are superficial, or aim for a conceptualization of underlying patterns. It is all up to you. It is your study and your choice of methodology. You are the interpreter and these phenomena are highlighted because you consider them important. Just make sure that you tell your reader about your methodology, under the heading Method. Be unbiased, stay close to the data, i.e. the transcripts, and do not hesitate to code plenty of phenomena. You can have lots of codes, even hundreds. STEP 3, decide which codes are the most important, and create categories by bringing several codes together 3.1. Go through all the codes created in the previous step. Read them, with a pen in your hand. 3.2. You can create new codes by combining two or more codes. 3.3. You do not have to use all the codes that you created in the previous step. 3.4. In fact, many of these initial codes can now be dropped. 3.5. Keep the codes that you think are important and group them together in the way you want. 3.6. Create categories. (You can call them themes if you want.) 3.7. The categories do not have to be of the same type. They can be about objects, processes, differences, or whatever. 3.8. Be unbiased, creative and open-minded. 3.9. Your work now, compared to the previous steps, is on a more general, abstract level. 3.10. You are conceptualizing your data. STEP 4, label categories and decide which are the most relevant and how they are connected to each other 4.1. Label the categories. Here are some examples: Adaptation (Category) Updating rulebook (sub-category) Changing schedule (sub-category) New routines (sub-category) Seeking information (Category) Talking to colleagues (sub-category) Reading journals (sub-category) Attending meetings (sub-category) Problem solving (Category) Locate and fix problems fast (sub-category) Quick alarm systems (sub-category) 4.2. Describe the connections between them. 4.3. The categories and the connections are the main result of your study. It is new knowledge about the world, from the perspective of the participants in your study. STEP 5, some options 5.1. Decide if there is a hierarchy among the categories. 5.2. Decide if one category is more important than the other. 5.3. Draw a figure to summarize your results. STEP 6, write up your results 6.1. Under the heading Results, describe the categories and how they are connected. Use a neutral voice, and do not interpret your results. 6.2. Under the heading Discussion, write out your interpretations and discuss your results. Interpret the results in light of, for example: *results from similar, previous studies published in relevant scientific journals; *theories or concepts from your field; *other relevant aspects. STEP 7 Ending remark This tutorial showed how to focus on segments in the transcripts and how to put codes together and create categories. However, it is important to remember that it is also OK not to divide the data into segments. Narrative analysis of interview transcripts, for example, does not rely on the fragmentation of the interview data. (Narrative analysis is not discussed in this tutorial.) Further, I have assumed that your task is to make sense of a lot of unstructured data, i.e. that you have qualitative data in the form of interview transcripts. However, remember that most of the things I have said in this tutorial are basic, and also apply to qualitative analysis in general. You can use the steps described in this tutorial to analyze: *notes from participatory observations; *documents; *web pages; *or other types of qualitative data. STEP 8 Suggested reading Alan Bryman's book: 'Social Research Methods' published by Oxford University Press. Steinar Kvale's and Svend Brinkmann's book 'InterViews: Learning the Craft of Qualitative Research Interviewing' published by SAGE. Good luck with your study. Text and video (including audio) © Kent Löfgren, Sweden
Views: 667530 Kent Löfgren
Temporal analysis: Generating time series from events based data
Often data is captured in a different format than required for analysis. Have you ever needed to perform historical analysis on events-based data? For example, how do you calculate turnover based on employees' start and end dates? Or, if sensor data captures when a device switches between on, off, and idle, how do you calculate the percent of time that a device was active per period? Join this Jedi session to find out!
Views: 374 Tableau Software
Philip Evans: How data will transform business
What does the future of business look like? In an informative talk, Philip Evans gives a quick primer on two long-standing theories in strategy — and explains why he thinks they are essentially invalid. TEDTalks is a daily video podcast of 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 much more. Find closed captions and translated subtitles in many languages at http://www.ted.com/translate Follow TED news on Twitter: http://www.twitter.com/tednews Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: http://www.youtube.com/user/TEDtalksDirector
Views: 226128 TED
Predicting Stock Prices - Learn Python for Data Science #4
In this video, we build an Apple Stock Prediction script in 40 lines of Python using the scikit-learn library and plot the graph using the matplotlib library. The challenge for this video is here: https://github.com/llSourcell/predicting_stock_prices Victor's winning recommender code: https://github.com/ciurana2016/recommender_system_py Kevin's runner-up code: https://github.com/Krewn/learner/blob/master/FieldPredictor.py#L62 I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ Stock prediction with Tensorflow: https://nicholastsmith.wordpress.com/2016/04/20/stock-market-prediction-using-multi-layer-perceptrons-with-tensorflow/ Another great stock prediction tutorial: http://eugenezhulenev.com/blog/2014/11/14/stock-price-prediction-with-big-data-and-machine-learning/ This guy made 500K doing ML stuff with stocks: http://jspauld.com/post/35126549635/how-i-made-500k-with-machine-learning-and-hft Please share this video, like, comment and subscribe! That's what keeps me going. and please support me on Patreon!: https://www.patreon.com/user?u=3191693 Check out this youtube channel for some more cool Python tutorials: https://www.youtube.com/watch?v=RZF17FfRIIo Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 486041 Siraj Raval
Making data mean more through storytelling | Ben Wellington | TEDxBroadway
Ben Wellington uses data to tell stories. In fact, he draws on some key lessons from fields well outside computer science and data analysis to make his observations about New York City fascinating. Never has a fire hydrant been so interesting as in this talk. Ben Wellington is a computer scientist and data analyst whose blog, I Quant NY, uses New York City open data to tell stories about everything from parking ticket geography to finding the sweet spot in MetroCard pricing. His articles have gone viral and, in some cases, led to policy changes. Wellington teaches a course on NYC open data at the Pratt Institute and is a contributor to Forbes and other publications. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx
Views: 145866 TEDx Talks
Metagenomics Analysis and Assembly-Based Metagenomics
This is the fourth session in the 2017 Microbiome Summer School: Big Data Analytics for Omics Science organized by the Université Laval Big Data Research Center and the Canadian Bioinformatics Workshops. This lecture is by Morgan Langille from Dalhousie University and Frederic Raymond from Universite Laval. For tutorials and lecture slides for this workshop, please visit bioinformaticsdotca.github.io. How it Begins by Kevin MacLeod is licensed under a Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) Source: http://incompetech.com/music/royalty-free/index.html?isrc=USUAN1100200 Artist: http://incompetech.com/
Views: 2679 Bioinformatics DotCa
How to analyze a case study?
This presentation describes an approach to analyze a case study - especially case studies from management discipline. Dr. Pradeep Racherla, Program Director & Associate Professor Marketing, Woxsen School of Business, elucidates different components of a case study and offers a framework to analyze a case study.
Views: 165297 Sanjay
Data Analysis for Social Scientists | MITx on edX | Course About Video
Learn methods for harnessing and analyzing data to answer questions of cultural, social, economic, and policy interest. Take this course free on edX: https://www.edx.org/course/data-analysis-social-scientists-mitx-14-310x#! ABOUT THIS COURSE This statistics and data analysis course will introduce you to the essential notions of probability and statistics. We will cover techniques in modern data analysis: estimation, regression and econometrics, prediction, experimental design, randomized control trials (and A/B testing), machine learning, and data visualization. We will illustrate these concepts with applications drawn from real world examples and frontier research. Finally, we will provide instruction for how to use the statistical package R and opportunities for students to perform self-directed empirical analyses. This course is designed for anyone who wants to learn how to work with data and communicate data-driven findings effectively. WHAT YOU'LL LEARN - Intuition behind probability and statistical analysis - How to summarize and describe data - A basic understanding of various methods of evaluating social programs - How to present results in a compelling and truthful way - Skills and tools for using R for data analysis
Views: 7118 edX
Data Scientist Vs Data Analyst
In this video I want to talk about the differences between a data scientist and a data analyst. is data science a viable career and if so should you try to become a data scientist or a data analyst. ► Full Playlist Exploring All Things Data Science ( http://bit.ly/2mB4G0N ) ► Top 4 Best Laptops for the Data Industry ( https://youtu.be/Vtk50Um_yxA ) ► Data Scientist Masters Certification ( http://bit.ly/2yCbsac ) ► Get the Best Certified Tutorials on Data Analytics... http://jobsinthefuture.com/index.php/2017/10/13/data-scientist-vs-data-analytics-what-is-the-big-data-difference/ Questions: - What is the best career path for a data scientist? - How do I become a data analyst? - What is the difference between a data scientist and a data analyst? - Is data science the same as data analytics? - Is data science a viable career path? - Is data analytics a viable career path? Jobs related to data science are booming right now with the tech industry growing at a rapid pace, but there is a lot of confusion between the Role of a Data Scientist and a Data Analyst... I am going to QUICKLY breakdown the difference for you so that you can get started right away with your career in the Data Analytics industry! First of all what is data analytics... Data analytics is the extraction a large, large, large amounts of data that are stored within a data base. This data comes from a multiplicity of places all over the world via website traffic, in-store and online purchases, social media activity, traffic patterns, etc, etc, etc.... the list could go on and on. Basically everything we do is being collected to be used as data to advertise to us, keep us safer when we are driving, or help us find the restaurant we want to eat at. Now to The Role of Data Scientist - The IT Rock Star! Data Scientists are the top professionals in their industry. They usually hold a Masters Degree in some relative Computer Science degree or even a PhD. They understand, very well, data from a business point of view and he/she can make accurate prediction of the data to advise clients on their next big business move! Data scientists have a solid foundation of computer applications, modeling, statistics and math! Highly Advanced in coding (Python, MySQL, R, JavaScript, etc... Ability to do high levels of math quickly Fantastic Statistical Analysis Abilities Great Communication Skill: Written and Oral And they have a brilliant Knack for communicating between the IT world and the Business Professionals. Starting Salary: $115,000 The Role of Data Analyst A Data Analyst is very important in the world of data science. They are in charge of collecting, organizing, and and obtaining statistical information from a large amount of data sets (Data sets are very large pools of data that must be searched in order to find the data that is relevant to a specific study). They are also the ones responsible for formulating all of their findings into an accurate report of powerpoint presentation to give to their client or internal team. Strong Understanding of Hadoop Based Analytics (Program to help extract data from large data sets and the analyze the data) Familiar with data analytics in a business setting Must have data storing a retrieval skills Proficiency in decision making Have the ability to transform data into understandable presentation Starting Salary: $60,000 ------- SOCIAL Twitter ► @jobsinthefuture Facebook ►/jobsinthefuture Instagram ►@Jobsinthefuture WHERE I LEARN: (affiliate links) Lynda.com ► http://bit.ly/2rQB2u4 edX.org ► http://fxo.co/4y00 MY FAVORITE GEAR: (affiliate links) Camera ► http://amzn.to/2BWvE9o CamStand ► http://amzn.to/2BWsv9M Compute ► http://amzn.to/2zPeLvs Mouse ► http://amzn.to/2C0T9hq TubeBuddy ► https://www.tubebuddy.com/bengkaiser ► Download the Ultimate Guide Now! ( https://www.getdrip.com/forms/883303253/submissions/new ) Thanks for Supporting Our Channel! DISCLAIMER: This video and description contains affiliate links, which means that if you click on one of the product links, I’ll receive a small commission. This help support the channel and allows us to continue to make videos like this. Thank you for the support!
Views: 92848 Ben G Kaiser
Introduction to Pivot Tables, Charts, and Dashboards in Excel (Part 1)
WATCH PART 2: https://www.youtube.com/watch?v=g530cnFfk8Y Download file used in the video: http://www.excelcampus.com/pivot-table-checklist-yt In this video series you will learn how to create an interactive dashboard using Pivot Tables and Pivot Charts. Works with Excel 2003, 2007, 2010, 2013 for Windows & Excel 2011 for Mac Don't worry if you have never created a Pivot Table before, I cover the basics of formatting your source data and creating your first Pivot Table as well. You will also get to see an add-in I developed named PivotPal that makes it easier to work with some aspects of Pivot Tables. Download the files to follow along at the following link. http://www.excelcampus.com/pivot-table-checklist-yt I have another video that shows how to reformat the pivot chart in Excel 2010. In the video above I'm using Excel 2013 and the menus are different from Excel 2007/2010. Here is the link to that video. http://www.youtube.com/watch?v=Jt_QqG-vRRw Get PivotPal: http://www.excelcampus.com/pivotpal Free webinar on The 5 Secrets to Understanding Pivot Tables: https://www.excelcampus.com/pivot-webinar-yt Subscribe to my free newsletter: http://www.excelcampus.com/newsletter
Views: 6099614 Excel Campus - Jon
Choosing which statistical test to use - statistics help.
Seven different statistical tests and a process by which you can decide which to use. The tests are: Test for a mean, test for a proportion, difference of proportions, difference of two means - independent samples, difference of two means - paired, chi-squared test for independence and regression. This video draws together videos about Helen, her brother, Luke and the choconutties. There is a sequel to give more practice choosing and illustrations of the different types of test with hypotheses.
Views: 680130 Dr Nic's Maths and Stats
James Powell - Building Web-based Analysis & Simulation Platforms
Titles - Building Web-based Analysis & Simulation Platforms with React/Redux, Flask, Celery, Bokeh, and Numpy Filmed at PyData 2017 Description What use is analytical code if it can't be integrated into a business workflow to solve real problems? This tutorial is about integrating analytical work into a real production system that can be used by business users. It focuses on building a web-based platform for managing long-running analytical code and presenting results in a convenient format, using cutting-edge combination of tools. Abstract The purpose of this stack is to be able to rapidly create web-based environments for users to interact with the results of analytical and simulation processes (without needing to retrain one's self as a web programmer!) This tutorial is composed of the following pieces: building a simple simulation using Numpy. For the purposes of this tutorial, we model a very simple Monte Carlo simulation with a number of user-controllable, tweakable algorithm inputs and model parameters. The simulation is chosen to be simple enough to present and code quickly. The purpose of this tutorial is not building Monte Carlo simulations but packaging them into lightweight production systems. Celery for launching and managing the above simulation jobs. This tutorial will not cover all aspects of Celery. It will merely show how the tool can be used as a job management system. Flask as a very thin JSON API layer. The tutorial will make use of Flask plugins for quickly building JSON APIs. This is the thinnest and least interesting component of the tutorial and won't be covered in great depth. React + Redux for a slick, simple single-page app. Attendees are expected to be least familiar with Javascript and the React ecosystem. The tutorial will spend a fair amount of time on this component, and will cover setting up build environment using Babel (for JSX transpilation) and Gulp as a build system. Bokeh for presenting graphical results from the simulation. This component may be cut based on time considerations. If time permits, it might also be possible to discuss the use of React Native to quickly build mobile apps using the same infrastructure. www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. We aim to be an accessible, community-driven conference, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
Views: 8707 PyData
Change Impact Analysis based on Linked Data
Application of Linked Data approach to System Engineering. Leading European transportation and health care companies takes up the challenge to establish and push forward an Interoperability Specification (IOS) as an open European standard for safety-critical system. This video shows how CRYSTAL Artemis project - http://www.crystal-artemis.eu/ - leveraged on the linked data approach to support a typical aerospace engineering method like a Change Impact Analysis with respect to interoperability. About CRYSTAL: CRYSTAL -- Critical System Engineering Acceleration- is an ARTEMIS project that take up results from previous European research projects to define an Interoperability standard (IOS) and a Reference Technology Platform (RTP) with a clear objective of industrialisation. IOS and RTP will enable a better integration of engineering tools based on the internet principles and web technologies like linked data throughout Product Lifecycle Management. With 4 industrial domains represented in this project including the aerospace domain, the project has proposed a user driven approach based on industrial scenarios and technology bricks.
Web-based Data Acquisition and Data Analysis System
This presentation is from Labinvent. The presentation shows how to create a new HPLC configuration, create an acquisition method, work with charts, save data.
Views: 75 Labinvent JSC
Cloud based analysis of condition data of a MV-drive
SINAMICS medium voltage drives allow the cloud-based analysis of condition data like the internal cabinet temperature and the load behavior of connected motors and production machines. The result is an optimized overall system with a higher availability
Views: 185 Siemens
Projects based Multi Omics Data Analysis Education
Learn More: edu.t-bio.info Effective, precise and personalized diagnostics and treatment stemming from an improved understanding of diseases has been in part driven by increased and improved data collection, especially high-throughput data. Genomic, transcriptomic, proteomic, metabolomic, and other ‘omic datasets enable biological research on a scale not possible even in the recent past.
Views: 12009 Pine Biotech
Data Preparation Step for Automated Diagnosis based on HRV Analysis and Machine Learning
Video for ICSET 2016 Conference for a paper titled "Data Preparation Step for Automated Diagnosis based on HRV Analysis and Machine Learning" Abstract: This paper describes the data preparation step of a proposed method for automated diagnosis of various diseases based on heart rate variability (HRV) analysis and machine learning. HRV analysis – consisting of time-domain analysis, frequency-domain analysis, and nonlinear analysis – is employed because its resulting parameters are unique for each disease and can be used as the statistical symptoms for each disease, while machine learning techniques are employed to automate the diagnosis process. The input data consist of electrocardiogram (ECG) recordings. The proposed method is divided into three main steps, namely dataset preparation step, machine learning step, and disease classification step. The dataset preparation step aims to prepare the training data for machine learning step from raw ECG signals, and to prepare the test data for disease classification step from raw RRI signals. The machine learning step aims to obtain the classifier model and its performance metric from the prepared dataset. The disease classification step aims to perform disease diagnosis from the prepared dataset and the classifier model. The implementation of data preparation step is subsequently described with satisfactory result. Keywords: Automated diagnosis, ECG signal, RRI signal, HRV analysis, and machine learning.
Views: 532 Vincentius Timothy
A Machine Learning-Based Trading Strategy Using Sentiment Analysis Data
Slides available ► https://goo.gl/1Xc3fJ Full Event ► https://goo.gl/ucxU1S Watch all sessions: ► https://goo.gl/LrMFPA Tucker Balch - Co-Founder & CTO - Lucena Research. In this talk, Tucker shows how sentiment information in combination with a Machine Learning technique can provide a successful stock trading strategy. Specifically, he creates a predictive Machine Learning-based model for company stock prices based on the recent sentiment data; he uses that model as an input to build portfolios that are re-balanced weekly and simulate the performance of those portfolios. His results indicate that the sentiment information has predictive value and is useful as part of a Machine Learning strategy that significantly outperforms the market from which the candidate equities are drawn. Presentation held at 3rd Annual RavenPack Research Symposium entitled "Big Data Analytics for Alpha, Smart Beta & Risk Management". Visit us at ►https://www.ravenpack.com/ Follow RavenPack on Twitter ► https://twitter.com/RavenPack
Views: 10057 RavenPack
Data analysis with python and Pandas - Select Row, column based on condition Tutorial 10
This video will explain how to select subgroup of rows based on logical condition. Visit complete course on Data Science with Python : https://www.udemy.com/data-science-with-python-and-pandas/?couponCode=YTSOCIAL090 For All other visit my udemy profile at : https://www.udemy.com/user/ankitmistry/
Views: 4970 MyStudy
Data Analysis in Excel 9 - Filter Data Based on The Frist, Last, or Middle Values in a Cell in Excel
Visit http://www.TeachExcel.com for more, including Excel Consulting, Macros, and Tutorials. This Excel Video Tutorial shows you how to Filter data in Excel based on the First, Last, or Middle Values in a cell. This covers some of the great Filter features in Excel. This tutorial will allow you to better view and analyze large data sets in Excel as well as to drill down content in Excel in order to view smaller subsets of a larger data set. For Excel consulting, classes, or to get the spreadsheet or macro used here visit the website http://www.TeachExcel.com There, you can also get more free Excel video tutorials, macros, tips, and a forum for Excel. Have a great day!
Views: 11454 TeachExcel
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hadoop Training | Edureka
** Flat 20% Off (Use Code: YOUTUBE20) Hadoop Training: https://www.edureka.co/hadoop ** This Edureka Big Data tutorial ( Big Data Hadoop Blog series: https://goo.gl/LFesy8 ) helps you to understand Big Data in detail. This tutorial will be discussing about evolution of Big Data, factors associated with Big Data, different opportunities in Big Data. Further it will discuss about problems associated with Big Data and how Hadoop emerged as a solution. Below are the topics covered in this tutorial: 1) Evolution of Data 2) What is Big Data? 3) Big Data as an Opportunity 4) Problems in Encasing Big Data Opportunity 5) Hadoop as a Solution 6) Hadoop Ecosystem 7) Edureka Big Data & Hadoop Training Subscribe to our channel to get video updates. Hit the subscribe button above. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Check our complete Hadoop playlist here: https://goo.gl/hzUO0m - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 40 hours of assignment and 30 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 Big Data and Hadoop online training is designed to help you become a top Hadoop developer. During this course, our expert Hadoop instructors will help you: 1. Master the concepts of HDFS and MapReduce framework 2. Understand Hadoop 2.x Architecture 3. Setup Hadoop Cluster and write Complex MapReduce programs 4. Learn data loading techniques using Sqoop and Flume 5. Perform data analytics using Pig, Hive and YARN 6. Implement HBase and MapReduce integration 7. Implement Advanced Usage and Indexing 8. Schedule jobs using Oozie 9. Implement best practices for Hadoop development 10. Work on a real life Project on Big Data Analytics 11. Understand Spark and its Ecosystem 12. Learn how to work in RDD in Spark - - - - - - - - - - - - - - Who should go for this course? If you belong to any of the following groups, knowledge of Big Data and Hadoop is crucial for you if you want to progress in your career: 1. Analytics professionals 2. BI /ETL/DW professionals 3. Project managers 4. Testing professionals 5. Mainframe professionals 6. Software developers and architects 7. Recent graduates passionate about building successful career in Big Data - - - - - - - - - - - - - - Why Learn Hadoop? Big Data! A Worldwide Problem? According to Wikipedia, "Big data is collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications." In simpler terms, Big Data is a term given to large volumes of data that organizations store and process. However, it is becoming very difficult for companies to store, retrieve and process the ever-increasing data. If any company gets hold on managing its data well, nothing can stop it from becoming the next BIG success! The problem lies in the use of traditional systems to store enormous data. Though these systems were a success a few years ago, with increasing amount and complexity of data, these are soon becoming obsolete. The good news is - Hadoop has become an integral part for storing, handling, evaluating and retrieving hundreds of terabytes, and even petabytes of data. - - - - - - - - - - - - - - Opportunities for Hadoopers! Opportunities for Hadoopers are infinite - from a Hadoop Developer, to a Hadoop Tester or a Hadoop Architect, and so on. If cracking and managing BIG Data is your passion in life, then think no more and Join Edureka's Hadoop Online course and carve a niche for yourself! Please write back to us at [email protected] or call us at +91 88808 62004 for more information. Customer Review: Michael Harkins, System Architect, Hortonworks says: “The courses are top rate. The best part is live instruction, with playback. But my favourite feature is viewing a previous class. Also, they are always there to answer questions, and prompt when you open an issue if you are having any trouble. Added bonus ~ you get lifetime access to the course you took!!! ~ This is the killer education app... I've take two courses, and I'm taking two more.”
Views: 635906 edureka!
Deciding based on data. Predictive Analysis and EDA (Exploratory Data Analysis)
Evidence data based decision making. Predictions based on data and statistics. Useful for Engineering Sciences Finances and Legal matters. Engineering Statistics. NIST/SEMATECH e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/handbook/, date.
Views: 29 8289468
Object-Based Image Analysis
Keith Pelletier, UMN Remote Sensing and Geospatial Analysis Laboratory The geospatial community is experiencing a data-rich era where Earth-observing platforms are capturing the landscape at fine-scale spatial and temporal resolutions. These remotely-sensed data provide a view from above that is essential for analyzing natural and anthropogenic interactions over large areas. Traditional approaches to these analyses are time and labor-intensive or limited by per-pixel techniques that fail to incorporate contextual cues. Object-based image analysis (OBIA) allows researchers and decision managers to integrate data from disparate sources at multiple scales and employ color, shape, and context for creating meaningful information. In this presentation, examples from mapping terrain, vegetation and urban infrastructure are used for illustrating data integration and analysis using OBIA. More information: https://uspatial.umn.edu/brownbag
Views: 38731 U-Spatial
BroadE: Use of Web-based annotation tools for bioinformatic analysis of proteomics data
Copyright Broad Institute, 2013. All rights reserved. The presentation above was filmed during the 2012 Proteomics Workshop, part of the BroadE Workshop series. The Proteomics Workshop provides a working knowledge of what proteomics is and how it can accelerate biologists' and clinicians' research. The focus of the workshop is on the most important technologies and experimental approaches used in modern mass spectrometry (MS)-based proteomics.
Views: 2101 Broad Institute
Slaying Excel Dragons Book #44; Data Analysis Filter Feature: Extract Data Based on Criteria
Download files: https://people.highline.edu/mgirvin/ExcelIsFun.htm Learn Excel from beginning to end. Complete Lessons about Excel. This video series accompanies the published book, Slaying Excel Dragons, ISBN 9781615470006 Chapter 6: Data Analysis Filter Feature: Extract Data Based on Criteria Pages 420 - 433 Topics: 1. Turn On Filter with Keyboard Shortcut (Toggle) 2. Filter Hides records that do not match criteria 3. Filter with One Criterion 4. Filter With Two Criteria (And criteria) 5. Filter With Two Criteria (Or criteria) 6. Extract Records 7. Clear Filters 8. Right-click Filtering 9. Filter by Color 10. Filter Below Average 11. Filter Top Five Sales 12. Sort after filter 13. Filter Words 14. Contains 15. Filter Dates 16. Filter to add or average with criteria Excel. Excel Basics. Excel intermediate. Excel How To. Learn Excel. Excel 2010.
Views: 9348 ExcelIsFun
Web-Based Analysis of Mass Spectrometry Data
ImageXD | June 8, 2016 | 1:00-1:30 p.m. | 190 Doe Library, UC Berkeley Speaker: Ben Bowen, Lawrence Berkeley National Lab Incredible advances are being made in image processing techniques and tools, but the scientists who use them typically don’t have the opportunity to communicate with scientists who work on similar problems in different domains. This workshop aims to address that. At ImageXD we will gather researchers from a variety of fields who work with images as a primary source of data. Invited speakers will discuss their image processing pipelines, identifying common principles, algorithms, and tools. Throughout, we aim learn from one another while strengthening ties across disciplinary boundaries. Learn more: http://www.imagexd.org/
Sleep quality analysis based on data collected by bluetooth ECG monitor clothing
We analyzed data and wrote algorithms on Arduino to make sleep quality analysis and developed interface models to display real-time data on Processing.
Views: 39 Simin Zhai
IBPS PO MAINS 2018-Strategy to Crack Data Analysis and Interpretation Complete Planning
Please watch: "IBPS CLERK 2018-19: Strategy for Last 15 days Amar Sir YouTube Live" https://www.youtube.com/watch?v=kYQFBZMTu0c --~-- BANK/SSC/RAILWAY EXAMS Vision and Planning IBPS PO MAINS 2018-Strategy to Crack Data Analysis and Interpretation Complete Planning #Amar Sir “Math Dikhta Hai”. All the best! Let us watch: “IBPS PO MAINS 2018-Strategy to Crack Data Analysis and Interpretation Complete Planning”: https://youtu.be/aO5vh--rjU8 Our aim is to prepare students at their own, particularly the poors. So all the videos are free. But those who are able and wish to contribute to run this campaign smoothly may do the same. My mobile number 9931134475 is the Paytm and BHIM number. AMAR KUMAR SINGH SBI A/c 11009037430, IFSC-SBIN0000096, Main Branch, Jamshedpur. Our time of posting of videos on You Tube: 10:30 AM and 3:30 PM every day Join on Face Book: Chanakya Career Academy: https://www.facebook.com/groups/1441520242794598/ Amar Sir's Math Tricks: Quicker Method: Just in few seconds: Without using pen and paper: SBI PO/ Clerk/ IBPS PO/ Clerk/ SSC CGL/ Railway/ RRB/ LIC/ NDA/ CDS/ IAS/ JPSC/ BPSC: By Amar Sir having an experience of 23 years of teaching: Director of Chanakya Career Academy Pvt Ltd Sakchi Office:71-Pennar Road, Darbhanga Diary-1st Floor, Opposite Indian Overseas Bank, Sakchi, Jamshedpur-831001, Jharkhand. Bistupur Office: 1st Floor, Tewary Bechar, Main Road, Above City Style, Bistupur, Jamshedpur, Jharkhand. Office Contact:0657-220596/9570880011
Views: 11653 Amar Sir
Creating a Highlight Video in INTERACT based on data analysis (2)
This video shows how a highlight video is created in INTERACT, based on events generated by data analysis. INTERACT is the platform for Synchronized Viewing and Analysis of Video Footage and Audio Files in Observational Research. It allows for Content Coding and Event Logging and creates valuable Qualitative and Quantitative results. It is based on 25 years of proven technology and based on the knowledge of thousands of researchers worldwide. INTERACT enables accelerated answers to complex research questions, because it brings video, audio, physiology and live observations together, all in one single software tool. #mangoldinternational #mangoldsoftware #mangoldinteract #eyetracking #eyetracker https://www.mangold-international.com/en/products/software/behavior-research-with-mangold-interact
Exploratory factor analysis of ordinal variables in SPSS based on matrix of polychoric correlations
This video provides a strategy for obtaining a matrix of polychoric correlations from LISREL to perform factor analysis on ordinal variables in SPSS. You can obtain a free student version of LISREL here: http://www.ssicentral.com/lisrel/student.html You can obtain a copy of the data used in the video here: https://drive.google.com/open?id=1n9SnVnBe1G7iGV8bYS-8CAV1gzbcbLZA You can download a copy of the SPSS syntax file used in the video here: https://drive.google.com/open?id=1bh_QGikepMju6ArwEeqomELPyrs0iJNh For further info on the approach to performing factor analysis in SPSS on matrix input data, you can go here: http://www-01.ibm.com/support/docview.wss?uid=swg21479694 For more instructional videos and other materials on various statistics topics, be sure to my webpages at the links below: Introductory statistics: https://sites.google.com/view/statisticsfortherealworldagent/home Multivariate statistics: https://sites.google.com/view/statistics-for-the-real-world/home
Views: 850 Mike Crowson
AssetWise - Risk Based Inspection Analysis and Data Management
As an integrity engineer, you need to conduct risk based inspection analyses to maintain the integrity of piping and pressurized vessels. With AssetWise, you can reduce the risk of containment loss as a result of deterioration. AssetWise combines analysis with inspection data management that supports a dynamic risk-based inspection process. See more at: https://www.bentley.com/en/products/product-line/asset-reliability-software/assetwise-apm-strategy-development
A Rule-Based Approach for User-Driven Event Data Analysis - Weisi Chen UNSW
Recently, "e-Research" is being adopted worldwide across all research disciplines, harnessing high-capacity and collaborative data from a large range of data sources and communication technology to improve and enable research that cannot be conducted otherwise. E-Research often involves data-intensive analysis tasks and it is mainly performed by non-IT experts from different application domains (e.g. biology, physics, health) who mostly use data, libraries and packages from a variety of sources and manage the analysis process by themselves. One of the most important data types e-Researchers use to conduct analysis processes is "event data", which records information of some timed events in a particular domain. Event data analysis is becoming increasingly of interest to academic researchers looking for patterns in the data, contributing to the emergence and popularity of a new field called "data intensive science". Unlike domain experts working in large companies which have access to IT staff and expensive software infrastructure, researchers find it harder to efficiently manage event processing rules by themselves especially when these rules increase in size and complexity over time. In this thesis, we propose an event data analysis platform intended for non-IT experts that facilitates the evolution of event processing rules according to changing requirements. This platform integrates a rule-learning framework called Ripple-Down Rules (RDR) operating in conjunction with an event pattern detection process invoked as a service. This solution is demonstrated on real-life scenario involving financial data analysis. In the past 12 months, the architecture design has been finalised and an implementation has been developed. The architecture and has been validated using a small rule set, which has been accepted by ASSRI conference. In the next 6 months, my focus will be the thorough validation of the architecture, which involves e-Researchers who will be asked to add new rules and give feedback on the experience. Most importantly, I'll start the write-up of the thesis.
Big Data Intelligence CTF Based on Risk Analysis Approach
ig Data Intelligence is the collection and analysis of operational data that support the business suggestions and strategic decisions to an inferential process that looks at past operational performance to predict suspect profile of terrorist based on financial transaction data.
Views: 44 Alan Tandjung
David Abbott - Integrating data-driven and model-based analysis tools for functional MRI [2015]
Lecture at Neuroinformatics 2015 in Cairns, Australia. One day special session organized by the INCF Australia Node, August 22. Session 2: Imaging informatics Talk title: Integrating data-driven and model-based analysis tools for functional MRI Speaker: David Abbott, The Florey Institute of Neuroscience and Mental Health
Views: 82 INCF
How to Extract Data from a Spreadsheet using VLOOKUP, MATCH and INDEX
When you need to find and extract a column of data from one table and place it in another, use the VLOOKUP function. This function works in any version of Excel in Windows and Mac, and also in Google Sheets. It allows you to find data in one table using some identifier it has in common with another table. The two tables can be on different sheets or even on different workbooks. There is also an HLOOKUP function, which does the same thing, but with data arranged horizontally, across rows. See the companion tutorial on Tuts+ at https://computers.tutsplus.com/tutorials/how-to-extract-data-from-a-spreadsheet-using-vlookup-match-and-index--cms-20641. By Bob Flisser.
Views: 2647786 Tuts+ Computer Skills
Market Basket Analysis in Tableau
One of retailers’ favorite analysis techniques to help them understand the purchase behavior of their customers is the market basket analysis. We'll use Tableau to perform a simple market basket analysis based upon default Superstore data. anthonysmoak.com @anthonysmoak
Views: 38 Anthony B. Smoak
Cloud based Spend Analysis and Spend Management
Data Analytics, Spend Analysis & Procurement Intelligence for small and medium-sized businesses – Learn more about Orpheus.Cloud | Spend Analytics. We provide full spend visibility, data transparency, and advanced spend analysis - Rely on a solid database and thus real-time data! Current reporting solutions mostly consist of Excel-spreadsheets and manually collected data-sets that do not offer full transparency over the companies spend and provide neither in-depth analyses nor appealing visualizations. Orpheus now has the solution: Our cloud-based software Orpheus.Cloud - Spend Analytics: - The setup of Orpheus.Cloud is fast and uncomplicated, and the tool is easy to use. - Our predefined dashboards contain all relevant procurement KPIs and analyses such as ABC-analysis, Spend Trends and Spend fragmentation. - We solve problems regarding data quality and transparency applying AI-methods and intelligent algorithms. - Savings potentials can easily be transferred into initiatives and made visible in the P&L. Website: https://www.orpheus-it.com/ Facebook: https://www.facebook.com/Orpheus.IT/
Views: 195 Orpheus GmbH
System-Oriented Approaches for Robust Integrative Analysis of ‘Omics’ Data
Byung –Jun Yoon, Ph.D Associate Professor Deparment of Electrical & Computer Enginnering Texas A & M University
Views: 125 UTHealth SBMI

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