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  • Architecture for database analytics

    - by David Cournapeau
    Hi, We have an architecture where we provide each customer Business Intelligence-like services for their website (internet merchant). Now, I need to analyze those data internally (for algorithmic improvement, performance tracking, etc...) and those are potentially quite heavy: we have up to millions of rows / customer / day, and I may want to know how many queries we had in the last month, weekly compared, etc... that is the order of billions entries if not more. The way it is currently done is quite standard: daily scripts which scan the databases, and generate big CSV files. I don't like this solutions for several reasons: as typical with those kinds of scripts, they fall into the write-once and never-touched-again category tracking things in "real-time" is necessary (we have separate toolset to query the last few hours ATM). this is slow and non-"agile" Although I have some experience in dealing with huge datasets for scientific usage, I am a complete beginner as far as traditional RDBM go. It seems that using column-oriented database for analytics could be a solution (the analytics don't need most of the data we have in the app database), but I would like to know what other options are available for this kind of issues.

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  • How to Aggregate Web Feeds with Yahoo! Pipes

    Yahoo! Pipe is a free online web application which helps you combine many feeds into one. Sort it by your preference, filter it and finally present it. In other words, Yahoo! Pipes is a web mashup, w... [Author: Debbie Everson - Web Design and Development - March 30, 2010]

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  • Site Review: Yahoo.com - Forms Evaluation

    Yahoo uses Ajax to suggest search terms to users when they are entering a search phrase into the search text box. Once the user has entered a search term and then presses the search button, the browser will post the search form to the search results page. I think that Yahoo is making great use of Ajax in this situation because they are helping users find information as well as suggesting alternative search terms for them to try based on what has already been added.

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  • Using Site Explorer to Improve Yahoo Search Results

    It is the information generated within Yahoo Site Explorer, and the interpretation of that valuable data, that provides the necessary direction; to improve your Yahoo search results. As with any tool, Site Explorer must be used properly and effectively; to be beneficial.

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  • SEO Tips For Yahoo!

    At first, Yahoo! was the most popular search engine until Google entered the scene. Yahoo! said goodbye to its throne with Google's amazingly accurate results.

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  • Guest blog: A Closer Look at Oracle Price Analytics by Will Hutchinson

    - by Takin Babaei
    Overview:  Price Analytics helps companies understand how much of each sale goes into discounts, special terms, and allowances. This visibility lets sales management see the panoply of discounts and start seeing whether each discount drives desired behavior. In Price Analytics monitors parts of the quote-to-order process, tracking quotes, including the whole price waterfall and seeing which result in orders. The “price waterfall” shows all discounts between list price and “pocket price”. Pocket price is the final price the vendor puts in its pocket after all discounts are taken. The value proposition: Based on benchmarks from leading consultancies and companies I have talked to, where they have studied the effects of discounting and started enforcing what many of them call “discount discipline”, they find they can increase the pocket price by 0.8-3%. Yes, in today’s zero or negative inflation environment, one can, through better monitoring of discounts, collect what amounts to a price rise of a few percent. We are not talking about selling more product, merely about collecting a higher pocket price without decreasing quantities sold. Higher prices fall straight to the bottom line. The best reference I have ever found for understanding this phenomenon comes from an article from the September-October 1992 issue of Harvard Business Review called “Managing Price, Gaining Profit” by Michael Marn and Robert Rosiello of McKinsey & Co. They describe the outsized impact price management has on bottom line performance compared to selling more product or cutting variable or fixed costs. Price Analytics manages what Marn and Rosiello call “transaction pricing”, namely the prices of a given transaction, as opposed to what is on the price list or pricing according to the value received. They make the point that if the vendor does not manage the price waterfall, customers will, to the vendor’s detriment. It also discusses its findings that in companies it studied, there was no correlation between discount levels and any indication of customer value. I urge you to read this article. What Price Analytics does: Price analytics looks at quotes the company issues and tracks them until either the quote is accepted or rejected or it expires. There are prebuilt adapters for EBS and Siebel as well as a universal adapter. The target audience includes pricing analysts, product managers, sales managers, and VP’s of sales, marketing, finance, and sales operations. It tracks how effective discounts have been, the win rate on quotes, how well pricing policies have been followed, customer and product profitability, and customer performance against commitments. It has the concept of price waterfall, the deal lifecycle, and price segmentation built into the product. These help product and sales managers understand their pricing and its effectiveness on driving revenue and profit. They also help understand how terms are adhered to during negotiations. They also help people understand what segments exist and how well they are adhered to. To help your company increase its profits and revenues, I urge you to look at this product. If you have questions, please contact me. Will HutchinsonMaster Principal Sales Consultant – Analytics, Oracle Corp. Will Hutchinson has worked in the business intelligence and data warehousing for over 25 years. He started building data warehouses in 1986 at Metaphor, advancing to running Metaphor UK’s sales consulting area. He also worked in A.T. Kearney’s business intelligence practice for over four years, running projects and providing training to new consultants in the IT practice. He also worked at Informatica and then Siebel, before coming to Oracle with the Siebel acquisition. He became Master Principal Sales Consultant in 2009. He has worked on developing ROI and TCO models for business intelligence for over ten years. Mr. Hutchinson has a BS degree in Chemical Engineering from Princeton University and an MBA in Finance from the University of Chicago.

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  • Building an analytics dashboard in Rails

    - by Bob
    I'm looking to build a Rails app to do internal reporting (make charts or general data visualizations, create reports, show statistical analyses, etc.) on data my company collects. What would be helpful in building this? For example, any Rails/Javascript libraries I should be familiar with, or any open source analytics apps or existing dashboard tools I should look at?

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  • Custom Tracking with Google Analytics

    - by matthewb
    I am trying to figure out how to use my google analytics account, and do custom tracking on certain links and such, but following the technical information on the help site on google isn't getting me anywhere. Has anyone done something like this? Point me in the right direction.

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  • Google Analytics without ga.js

    - by Andrew
    I can't find anything recent on this. Is there any documentation on how to track with Google Analytics without using ga.js? I want a JS implementation on mobile devices but I don't want to load up 9KB of local memory or use server-side GA. I'm primarily interested only in tracking page views and uniques. Has anyone rolled their own GA implementation?

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  • Google Analytics API and Internal Search question

    - by Am
    I'm trying to use Google Analytics API to query internal searches that happen on my site. I'd like to be able to query the keywords and the number of times that keyword was used in internal search, based on URL of a page on the site. The idea is to find out which keywords direct the user to a particular page. Does anyone know which dimensions and metrics must use to query that information?

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