The Statistics of Web Performance Analysis

This document analyzes the annual report of Apple Inc. from 2004 to 2008. It summarizes the company's income statement, showing increasing sales, earnings, and net income each year. It also analyzes Apple's balance sheet, noting increasing current assets, total assets, and total equity. Overall, the trend percentages show strong growth across all financial metrics each year, indicating Apple has a solid financial position and is growing rapidly over this period.

This document discusses common size analysis, which allows companies to be compared across time and against competitors by expressing financial statement items as percentages of a base figure. There are three types of common size analysis: vertical common size income statements, horizontal common size income statements, and common size balance sheets. An example is provided where net income figures for two companies of different sizes are expressed as a percentage of sales revenue for better comparison. The document outlines some limitations of common size analysis and provides an example analysis of common size income statements and balance sheets.

Detailed analysis of five years financial statements( Income statement and Balance Sheet) using Trend , Comparative and Common size analysis.

This document provides a financial analysis of ICICI Prudential Life Insurance company. It includes an overview of the company and its products, sources of finance such as equity shares and debt, comparative financial statements from 2007-2008 showing increases in reserves and current assets. Financial ratios are calculated including current ratio, profitability ratio, debt ratio and return ratio. Findings note more charges taken from customers and lack of profit until 2008. Recommendations include caring more about fund management and providing lower charges to customers.

The document compares several major financial crises from 1929 to present day. It summarizes the key causes and impacts of each crisis, including the Great Depression, Black Monday, the European Exchange Rate Mechanism crisis, the Global Financial Crisis, the Greece crisis, Japan's debt crisis, and Brexit. It analyzes factors like leverage, liquidity issues, and policy failures that led to the crises. Economic indicators like GDP, unemployment, inflation, and stock market losses are compared across the different crises. Overall lessons on regulation, coordination, and stability of exchange rate mechanisms are discussed.

Bajaj Auto was founded in 1926 and initially manufactured sugar before diversifying into vehicle manufacturing in 1945. It is now India's largest two and three-wheeler manufacturer and the world's fourth largest. Bajaj Auto has experienced steady growth and released many new vehicle models over time. While its financial position is not as strong as competitor Hero Honda, with lower profit margins and negative working capital, Bajaj Auto remains an important player in India's large automobile industry and continues community service initiatives.

This document analyzes GM's balance sheet to highlight three important traits: size, liquidity, and solvency. It summarizes that GM is one of the largest companies in America based on total assets of $189 billion. It has adequate liquidity with a current ratio of 1.13, on par with other large companies. While GM's debt-to-equity ratio of 1.66 exceeds 1.0, it is comparable to many other S&P 500 firms.

The document discusses Kingfisher Airlines, an Indian airline established in 2003 that began operations in 2005. It provides key details about Kingfisher such as its headquarters, destinations served, and five-star rating. It then outlines Kingfisher's strengths as well as weaknesses, opportunities, and threats using a SWOT analysis framework. The presentation concludes by discussing problems Kingfisher faced such as heavy losses, strikes, and lack of management, and provides suggestions for how Kingfisher can continue to meet expectations of customers, suppliers, employees, and society.

This document analyzes Coca-Cola's financial statements and business strategies. It begins with an analysis of Coca-Cola's governance, including details about the CEO, board of directors, and executive compensation. It then discusses Porter's Five Forces analysis of the soda industry, finding rivalry to be high but threats of new entrants and substitutes to be medium. The document also analyzes Coca-Cola's income statements, balance sheets, profitability, and forecasts growth.

The document discusses various types of financial statement analysis including comparative statements, common size statements, trend analysis, and ratio analysis. It provides an example of a comparative balance sheet analysis for a company from 2006 to 2007. The analysis shows increases in fixed assets, long term liabilities, equity, and current assets. It also shows an increase in sales, gross profit, and net profit, indicating the overall financial position and profitability of the company improved from 2006 to 2007.

A financial analysis for Coca-Cola: company profile, financial statement, liquidity ratio, current ratio, cash ratio, quick ratio, profitability, efficiency, short term activity, long term activity, solvency, DuPont analysis and historical enterprise value (HEV). Done By Elie Obeid and Isabelle Khalil

This document provides an overview of project planning and estimation using function point analysis. It discusses defining a project's domain and scope, comparing projects and products, and the learning from projects. It also covers the software development lifecycle (SDLC) including planning, estimation models, and a case study on student registration using object-oriented analysis and design. Throughout are examples of applying function point analysis to estimate effort for a simple customer project.

Slide deck that explains the rationale behind perceptual speed index, and the collaborative work that happened over last year.

This document outlines a project to map and optimize the end-to-end total account process for a client globally. The project aims to identify opportunities to align with global best practices, standardize processes, and reduce turnaround times by 30-50%. Key deliverables include developing level 1 and 2 process maps, identifying optimization opportunities, and helping to validate process flows for a lift and shift project. The document describes the current state process which experiences high data mismatches and variations. Analysis identifies constraints like specialized roles and data issues. Recommendations include process documentation, error proofing, reducing handoffs, and using lean tools like 5S, visual management and standard work. The target state aims to improve cycle time, reduce defects, and

This document discusses using web scraping techniques to collect bank offer data from websites. It describes how an offer scavenger software can automate the extraction of relevant data from websites and organize it in a predefined format like a database. The document then provides details on how the researchers collected bank offer data from websites like centralbank.net.in using web scraping and Python libraries. It explains the data extraction, transformation and loading process to clean the scraped data and load it into a database. Some preliminary statistics are also generated from the collected data. Finally, it discusses some legal aspects of using web scraping techniques.

The document discusses using web scraping techniques to collect bank offer data from websites. It describes how web scraping works by analyzing website content, extracting relevant data, and formatting it into a structured database or spreadsheet. The paper then presents the process used to scrape bank offer data from Indian websites, including developing a Python script to automate scraping, scheduling regular scraping, cleaning the extracted data, and transforming it into a standardized format for analysis. The results section demonstrates the web scraping process and shows how the extracted data is further transformed using an ETL process into a clean dataset for analytics purposes.

The document proposes a web analytics software to analyze website visitor behavior using data from website access logs. The software would clean and extract log file data, store it in a database, and generate statistics, graphs, and forecasts. This would provide insights into visitor patterns like which products or services are most popular, how promotions impact sales, and classify profitable customer groups. The software aims to help websites better understand visitor behavior and customize services to increase sales and profits.

Developing a new modelling tool that will model emissions from road traffic. A pilot study is focusing on the situation in Aberdeen.

If your business is heavily dependent on the Internet, you may be facing an unprecedented level of network traffic analytics data. How to make the most of that data is the challenge. This presentation from Kentik VP Product and former EMA analyst Jim Frey explores the evolving need, the architecture and key use cases for BGP and NetFlow analysis based on scale-out cloud computing and Big Data technologies.

Learn how to perform text analytics with Minitab and Python. Text mining is useful when analyzing customer comments, call center transcriptions, doctor reports or any other free-form text that contains information you want to extract. We will show the basic steps from collecting summary statistics like Inverse Document Frequency (IDF) and cleaning text to more advanced concepts such as bag of words and sentiment values.

When Data Visualizations and Data Imports Just Don’t Work – Importing data is a dirty job as can painting user final pictures with that data. This webinar will explore the dirty little secrets that ensure data is imported completely and accurately, as well as, painting scenarios when a visualization may not be the best approach to meeting an audit objective. Specific learning objectives include: o Walk through case studies of “dirty” data and how to improve then using improved data requests and cleansing tools. o Watch case study examples of top tests to validate data tables to ensure data quality. o Discover a host of baseline tests and other baseline statistics to validate, understand and possibly extract key trends for review. o Understand visualization and dashboard types along with their associated analytical strengths from an audit perspective. o Identify situations where statistics may be more effective audit extractors than relying on the human eye to spot notable events.

This is the presentation given by Jon Kostyniuk at the #ITEToronto2017 conference on August 1, 2017. The TripChain framework represents an innovation in how trip generation data points can be stored and propagated for use within the transportation industry. This is accomplished through the implementation of a distributed, open peer-to-peer database for transportation professionals. For more information, please visit http://tripchain.org/.

This document summarizes Ian Machen's presentation on using citywide data and artificial intelligence to generate transportation solutions. It outlines the purpose, applications, challenges, process, lessons learned, and recommendations for developing data visualizations and fusing data from multiple city systems. The presentation covered use cases, sample visualization methods, challenges around complete insights and department silos, and the recommended step-process including identifying goals, challenges, performing audits and needs assessments, and setting performance indicators.

Data is growing exponentially. What should business managers do to make better business decisions? I explain three key things step by step. Just start today!

This document provides an introduction to data science from Amity Institute of Information Technology. It discusses data science tools and applications, the data science life cycle, and data science job roles. The data science life cycle includes 6 steps: defining the problem statement, data collection, data preparation, exploratory data analysis, data modeling, and data communication. Some applications of data science mentioned are internet search, recommendation systems, image and speech recognition, gaming, and online price comparison. Common data science jobs include data scientist, data engineer, data analyst, statistician, data architect, data admin, business analyst, and data/analytics manager.

ISWC 2015 - Linked Data Track Collecting, integrating, enriching and republishing open city data as linked data http://citydata.wu.ac.at/

As Walmart.com’s former head of Performance and Reliability, Cliff Crocker knows large scale web performance. Now SOASTA’s VP of products, Cliff is pouring his passion and expertise into cloud testing to solve the biggest challenges in mobile and web performance. The holiday rush of mobile and web traffic to your web site has the potential for unprecedented success or spectacular public failure. The world’s leading retailers have turned to the cloud to assure that no matter what load, mobile and web apps will delight customers and protect revenue. Join us as Cliff explores the key criteria for holiday web performance readiness: Closing the gap in front- and back-end web performance and reliability Collecting real user data to define the most realistic test scenarios Preparing properly for the virtual walls of traffic during peak events Leveraging CloudTest technology, as have 6 of 10 leading retailers

Presentation by John Repko to the Colorado Society for Information Management (http://www.sim-colorado.org/), March 19, 2013. It talks about big data "killer apps," and the two kinds of innovation ("Hindsight" and "Foresight") that big data can bring to any business.

Plumbee built analytics capabilities from scratch over time by starting with third-party analytics, collecting extensive unstructured event data, analyzing that data using spreadsheets and Hive, developing in-house experimentation and automation tools, and eventually transitioning to a relational data mart. This process allowed Plumbee to gain insights, improve features and the virtual economy, and scale their data use to support growth from 3 founders to 1.2 million monthly active users.

The document describes EMC's experiences with environmental data analytics projects. It discusses EMC setting up India's first environmental data management system for CPCB in 1986. This included air and water data management and analysis. The document also outlines other projects EMC has worked on, including an online environmental monitoring system for Egypt, analysis of Ganga river water quality data from sensors, and a corporate sustainability report for an Indian company. The presentation emphasizes that environmental data is large, irregular, fuzzy and from diverse sources, requiring advanced analytics to generate meaningful insights and reports.

I have been working on a new breed of estimation methodologies called "Open estimation methodologies". They can be called "Deliverable based estimation methodologies" also. This presentation is about this family of methodologies.

This document discusses techniques for improving the performance of D3 visualizations. It begins with an overview of D3 and some basic tutorials. It then describes issues with performance for force-directed layouts and edge-bundled layouts as the number of nodes and links increases. Solutions proposed include using canvas instead of SVG for rendering, reducing unnecessary calculations, and caching repeated drawing states. The document concludes that the number of DOM nodes has major performance implications and techniques like canvas can help when exact mouse interactions are not required.

There’s no such thing as fast enough. You can always make your website faster. This talk will show you how. The very first requirement of a great user experience is actually getting the bytes of that experience to the user before they they get tired and leave.In this talk we’ll start with the basics and get progressively insane. We’ll go over several frontend performance best practices, a few anti-patterns, the reasoning behind the rules, and how they’ve changed over the years. We’ll also look at some great tools to help you.

Frontend Performance Beginner to Expert to Crazy Person The very first requirement of a great user experience is actually getting the bytes of that experience to the user before they they get tired and leave. In this talk we'll start with the basics and get progressively insane. We'll go over several frontend performance best practices, a few anti-patterns, the reasoning behind the rules, and how they've changed over the years. We'll also look at some great tools to help you. La performance front-end de débutant, à expert, à fou furieux ! La toute première condition nécessaire à une bonne expérience utilisateur est de pouvoir obtenir les octets de cette expérience avant que l'utilisateur ne se lasse et parte. Nous débuterons cette conférence avec les bases pour progressivement devenir démentiel. Nous aborderons plusieurs des meilleurs pratiques de la performance front-end, quelques anti-patterns à éviter, le raisonnement derrière les règles, et comment ces dernières ont changé au fil des ans. Nous regarderons d'un peu plus près quelques très bon outils qui peuvent vous aider.

The document outlines steps for front-end performance optimization, beginning with basic techniques like caching, compression and domain sharing and progressing to more advanced strategies involving preloading, parallel downloads, and predicting response times. It was presented by Philip Tellis at WebPerfDays New York and includes references for further reading on topics like CDNs, TCP tuning, and the page visibility API.

RUM isn’t just for page level metrics anymore. Thanks to modern browser updates and new techniques we can collect real user data at the object level, finding slow page components and keeping third parties honest. In this talk we will show you how to use Resource Timing, User Timing, and other browser tricks to time the most important components in your page. We’ll also share recipes for several of the web’s most popular third parties. This will give you a head start on measuring object level performance on your own site.

The document outlines steps web performance experts take to optimize frontend performance, moving from beginner to advanced techniques. It starts with basic optimizations like enabling gzip, caching, and image optimization. It then discusses more advanced strategies like using a CDN, splitting JavaScript, auditing CSS, and parallelizing downloads. Finally it discusses very advanced techniques like pre-loading assets, detecting broken Accept-Encoding headers, and understanding how to optimize for HTTP/2. The document provides references for further information on each topic.

The document discusses front-end web performance optimization from beginner to expert levels. At the beginner level, it recommends starting with basic optimizations like measuring performance, enabling gzip compression, optimizing images, and caching. At the expert level, it discusses more advanced techniques like using a CDN, splitting JavaScript files, auditing CSS, and flushing content early. Finally, it outlines "crazy" optimizations like pre-loading assets, post-load fetching, and understanding round-trip network latency.

Boston Web Performance Meetup, April 22, 2014 The very first requirement of a great user experience is actually getting the bytes of that experience to the user before they they get fed up and leave. In this talk we'll start with the basics and get progressively insane. We'll go over several front-end performance best practices, a few anti-patterns, the reasoning behind the rules, and how they've changed over the years. We'll also look at some great tools to help you. Schedule: 6:30, pizza 7:15: talk

The very first requirement of a great user experience is actually getting the bytes of that experience to the user before they they get fed up and leave. In this talk we'll start with the basics and get progressively insane. We'll go over several frontend performance best practices, a few anti-patterns, the reasoning behind the rules, and how they've changed over the years. We'll also look at some great tools to help you.

The document appears to be a presentation on measuring real user experiences using Real User Monitoring (RUM) and analyzing the data. It discusses using RUM tools like Boomerang to collect data on user behavior and performance in real-time. The presentation then examines specific metrics collected like user patience, cache behavior, and how quickly new software versions are distributed based on the RUM data.

Part I of RUM Distillation 101. Part II is by Jonathan Klein available here: http://www.slideshare.net/jnklein/uxfest-performance-a

This document discusses using <IFRAME> tags to improve the performance of third party scripts. It describes how third party scripts normally block page loading and proposes using an iframe to load scripts asynchronously in parallel without blocking. It provides code for creating an iframe targeted to load scripts, handling cross-domain issues, and modifying the Method Queue Pattern to support iframes. The approach allows third party scripts to load without blocking the main page load.

The document discusses Boomerang, an open source tool for measuring real user performance on websites. It measures load times, bandwidth usage, latency and other metrics. Additional functionality can be added through plugins. The presentation encourages developers to use Boomerang to analyze user behavior, identify performance issues, and continuously improve sites based on real user data. It provides several examples of insights that can be gained, such as how performance varies by country, browser, and internet connection speed.

The document is a presentation about abusing JavaScript to measure web performance. It discusses using JavaScript to measure network latency, TCP handshake time, network throughput, DNS lookup time, IPv6 support and latency, and other performance metrics. It provides code examples for measuring each metric in JavaScript and notes challenges to consider. The presentation encourages the use of the open source Boomerang library for accurate performance measurement.

While building boomerang, we developed many interesting methods to measure network performance characteristics using JavaScript running in the browser. While the W3C's NavigationTiming API provides access to many performance metrics, there's far more you can get at with some creative tweaking and analysis of how the browser reacts to certain requests. In this talk, I'll go into the details of how boomerang works to measure network throughput, latency, TCP connect time, DNS time and IPv6 connectivity. I'll also touch upon some of the other performance related browser APIs we use to gather useful information. I will NOT be covering the W3C Navigation Timing API since that's been covered by Alois Reitbauer in a previous Boston Web Perf talk.

The document discusses analyzing real user monitoring (RUM) data to gain insights into website performance and user behavior. It describes building plugins to collect navigation and timing data from browsers. Various statistical techniques for analyzing the data are covered, including log-normal distributions, filtering outliers, sampling, and correlating metrics like page load time and bounce rates. The analysis of an example 8 million page dataset suggests very fast or slow page loads are associated with higher bounce rates, and thresholds for user-unfriendly performance are proposed based on bounce rates exceeding 50%.

This document contains slides from a presentation about using JavaScript to analyze network performance. It discusses how to measure latency, TCP handshake time, network throughput, DNS lookup time, IPv6 support and latency, and private network scanning using JavaScript. Code examples are provided for measuring each of these network metrics by making image requests and timing the responses. The presentation emphasizes that accurately measuring network throughput requires requesting resources of different sizes and accounting for TCP slow start. It also notes some challenges around caching and geo-located DNS results.