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  • How to configure Google Analytics experiments manually

    - by John
    I wish to run multivariate tests on an e-commerce site that run across all product pages. I will be setting and deciding the variations myself all I need to do is track the results in GA. I think may be possible (although only A/B testing is available via the GA UI): https://developers.google.com/analytics/devguides/platform/features/experiments#serving-framework EXTERNAL – You will choose variations, handle experiment optimization, and only report the chosen variation to Google Analytics. For example, this should be used by 3rd-party optimization platforms that want to integrate with Google Analytics for reporting purposes. In this case, the Google Analytics statistical engine will not run. However how do I configure this and push the data to GA in my page?

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  • Winner of the 2012 Government Big Data Solutions Award

    - by Jean-Pierre Dijcks
    Hot off the press: The winner of the 2012 Government Big Data Solutions Aware is the National Cancer Institute!! Read all the details on CTOLabs.com. A short excerpt to wet your appetite: "... This solution, based on the Oracle Big Data Appliance with the Cloudera Distribution of Apache Hadoop (CDH), leverages capabilities available from the Big Data community today in pioneering ways that can serve a broad range of researchers. The promising approach of this solution is repeatable across many other Big Data challenges for bioinfomatics, making this approach worthy of its selection as the 2012 Government Big Data Solution Award." Read the entire post. Congrats to the entire team!!

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  • Google Analytics not working for multiple domains

    - by syalam
    I have a webapp that allows users to embed an iframe on their website. This iframe contains a Google Analytics snippet that is logging an event that captures the website the iframe is embedded on. Google Analytics isn't reporting anything, even though I am clearly embedding this iframe on numerous websites (on multiple domains as well). Does Google Analytics not allow tracking for multiple domains?

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  • Google Analytics: Block Your Dynamic IP Visits?

    - by 4thSpace
    I have a dynamic IP, which doesn't work for Google Analytics IP filtering. I read this post How to excludes my visits from Google Analytics? but don't see any code for setting the variable mentioned there. Has anyone been able to block their website visits from Google Analytics using a cookie? EDIT: This seems to work https://tools.google.com/dlpage/gaoptout. Although I don't think it was designed as I'm using it.

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  • AdWords traffic not (properly) reflected in Analytics

    - by CJM
    I have an AdWords account, which was set to use Auto-tagging of URLs. When looking at the Analytics account for that site, I couldn't find any reference to AdWords traffic either in the Advertising section or the Traffic Sources section. So I manually constructed the URL tags, and updated the Campaign Ad. Once the ad was approved and the clicks started coming through again, I could see the results in the Traffic Sources section of Analytics. In the Sources Campaigns section, my campaign was listed, and under Sources All Traffic, it was registering the same level of traffic from google/adwords. However, the Advertising AdWords section is still drawing a blank. Any ideas? Are there explicit steps needed to enable full tracking of AdWords campaigns? If it is relevant, the Adwords campaign was set up with one account, and the Analytics tracking with another, but both accounts have full access to both AdWords and Analytics.

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  • How to track events or e-commerce sales that occur later using Google Analytics?

    - by Anton
    Here's my problem: I have a static site with Google Analytics tracking code. To buy one of my services, users call me, and when their order is ready (many days later), I send them an e-mail link to a special page (download.php) where I have GA tracking code that is executed the first time they visit, so I track a "sale". The issue is, GA thinks that "sale" was a separate visit, and erroneously shows that only direct visits to my site result in sales. I don't understand how I can view stats (Pages / Visit, Avg. Time on Site, etc.) about users who eventually bought something. I've tried events and e-commerce tracking with no luck. Please help!

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  • Using Google Analytics to determine how much time a visitor spends in each section of my site

    - by flossfan
    I have a site with various pages, like: /about/history /about/team /contact/email-us /contact I want to figure out how much time people are spending on the entire /about section, and how much on the /contact section. If I run a query on the Google Analytics API and set the dimension to ga:pagePathLevel1 and the metric to ga:avgTimeOnPage, I get results like this: { pagePathLevel1: /about, avgTimeOnPage: 28 }, { pagePathLevel1: /contact, avgTimeOnPage: 10 } This looks roughly like what I want, but I'm not sure how to intepret it: Is the value of avgTimeOnPage the average time spent by any user on all pages that match that path? Or is it the average time spent by any user on any single page that matches that path? I'm looking for the average time spent across all pages matching that path, but the time estimates look shorter than I'd expect.

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  • How can I track scrolling in a Google Analytics custom report?

    - by SnowboardBruin
    I want to track scrolling on my website since it's a long page (rather than multiple pages). I saw several different methods, with and without an underscore for trackEvent, with and without spaces between commas <script> ... ... ... ga('create', 'UA-45440410-1', 'example.com'); ga('send', 'pageview'); _gaq.push([‘_trackEvent’, ‘Consumption’, ‘Article Load’, ‘[URL]’, 100, true]); _gaq.push([‘_trackEvent’, ‘Consumption’, ‘Article Load’, ‘[URL]’, 75, false]); _gaq.push([‘_trackEvent’, ‘Consumption’, ‘Article Load’, ‘[URL]’, 50, false]); _gaq.push([‘_trackEvent’, ‘Consumption’, ‘Article Load’, ‘[URL]’, 25, false]); </script> It takes a day for counts to load with Google Analytics, otherwise I would just tweak and test right now.

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  • Is there a way I can verify my Google Analytics custom report?

    - by SnowboardBruin
    I want to track scrolling on my website since it's a long page (rather than multiple pages). I saw several different methods, with and without an underscore for trackEvent, with and without spaces between commas <script> ... ... ... ga('create', 'UA-45440410-1', 'example.com'); ga('send', 'pageview'); _gaq.push([‘_trackEvent’, ‘Consumption’, ‘Article Load’, ‘[URL]’, 100, true]); _gaq.push([‘_trackEvent’, ‘Consumption’, ‘Article Load’, ‘[URL]’, 75, false]); _gaq.push([‘_trackEvent’, ‘Consumption’, ‘Article Load’, ‘[URL]’, 50, false]); _gaq.push([‘_trackEvent’, ‘Consumption’, ‘Article Load’, ‘[URL]’, 25, false]); </script> It takes a day for counts to load with Google Analytics, otherwise I would just tweak and test right now.

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  • Analytics - Total events divided by number of unique pages?

    - by GeekyAndUnique
    I am using Google Analytics events to track keywords on my articles - not necessarily the best system I know but there are too many for variables I can't easily change it right now - and I would like to be able to see how popular each keyword is by dividing the number of page views with a keyword by the number of unique pages. Is there a/what is the best way of doing this? EDIT FOR CLARITY I currently have a system set up where every time somebody loads an article an event is fired for each of the tags/keywords used, with the keyword being the label. I can currently view my view count for each of the keywords by looking at the total events for each label, however I would like to be able to see which keywords are the most popular by dividing the number of times the event has been fired by the the number of different pages it has been fired from.

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  • Google Analytics + External Site Statistics Tracking in one application?

    - by Soleil
    My company is a broker in the real estate industry. As such, we send a lot of our listings to sites like Trulia.com and Zillow.com, among others. These sites direct leads to our realtors, and provide us with reports every month detailing the activity our listings have had on their site-- links back to our website, emails generated, etc. Our Marketing and Advertising departments want to take that information and enter it into a system to keep track of everything in one place, for the purpose of producing comparison reports. I cannot find any externally available product that provides this functionality. I would sincerely like to avoid writing this tool myself. Does anyone know of a tool that could do this? In short, an ideal system would: Imports Google Analytics data via API Imports real estate listing site data via CSV import / manual entry Provides comparison reports based on data Does anyone know of anything pre-made that can do this?

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  • The Oldest Big Data Problem: Parsing Human Language

    - by dan.mcclary
    There's a new whitepaper up on Oracle Technology Network which details the use of Digital Reasoning Systems' Synthesys software on Oracle Big Data Appliance.  Digital Reasoning's approach is inherently "big data friendly," as it leverages multiple components of the Hadoop ecosystem.  Moreover, the paper addresses the oldest big data problem of them all: extracting knowledge from human text.   You can find the paper here.   From the Executive Summary: There is a wealth of information to be extracted from natural language, but that extraction is challenging. The volume of human language we generate constitutes a natural Big Data problem, while its complexity and nuance requires a particular expertise to model and mine. In this paper we illustrate the impressive combination of Oracle Big Data Appliance and Digital Reasoning Synthesys software. The combination of Synthesys and Big Data Appliance makes it possible to analyze tens of millions of documents in a matter of hours. Moreover, this powerful combination achieves four times greater throughput than conducting the equivalent analysis on a much larger cloud-deployed Hadoop cluster.

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  • Using custom variables in Google Analytics funnels?

    - by Matt Huggins
    Google Analytics allow you to view how many users completed funnels through a set of pages in order to reach a goal URL. The service also allows you to pass custom variables when tracking a page view. Is it possible to combine the two, such that I create a funnel based upon the vale of a custom variable set for each visitor?

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  • To sample or not to sample...

    - by [email protected]
    Ideally, we would know the exact answer to every question. How many people support presidential candidate A vs. B? How many people suffer from H1N1 in a given state? Does this batch of manufactured widgets have any defective parts? Knowing exact answers is expensive in terms of time and money and, in most cases, is impractical if not impossible. Consider asking every person in a region for their candidate preference, testing every person with flu symptoms for H1N1 (assuming every person reported when they had flu symptoms), or destructively testing widgets to determine if they are "good" (leaving no product to sell). Knowing exact answers, fortunately, isn't necessary or even useful in many situations. Understanding the direction of a trend or statistically significant results may be sufficient to answer the underlying question: who is likely to win the election, have we likely reached a critical threshold for flu, or is this batch of widgets good enough to ship? Statistics help us to answer these questions with a certain degree of confidence. This focuses on how we collect data. In data mining, we focus on the use of data, that is data that has already been collected. In some cases, we may have all the data (all purchases made by all customers), in others the data may have been collected using sampling (voters, their demographics and candidate choice). Building data mining models on all of your data can be expensive in terms of time and hardware resources. Consider a company with 40 million customers. Do we need to mine all 40 million customers to get useful data mining models? The quality of models built on all data may be no better than models built on a relatively small sample. Determining how much is a reasonable amount of data involves experimentation. When starting the model building process on large datasets, it is often more efficient to begin with a small sample, perhaps 1000 - 10,000 cases (records) depending on the algorithm, source data, and hardware. This allows you to see quickly what issues might arise with choice of algorithm, algorithm settings, data quality, and need for further data preparation. Instead of waiting for a model on a large dataset to build only to find that the results don't meet expectations, once you are satisfied with the results on the initial sample, you can  take a larger sample to see if model quality improves, and to get a sense of how the algorithm scales to the particular dataset. If model accuracy or quality continues to improve, consider increasing the sample size. Sampling in data mining is also used to produce a held-aside or test dataset for assessing classification and regression model accuracy. Here, we reserve some of the build data (data that includes known target values) to be used for an honest estimate of model error using data the model has not seen before. This sampling transformation is often called a split because the build data is split into two randomly selected sets, often with 60% of the records being used for model building and 40% for testing. Sampling must be performed with care, as it can adversely affect model quality and usability. Even a truly random sample doesn't guarantee that all values are represented in a given attribute. This is particularly troublesome when the attribute with omitted values is the target. A predictive model that has not seen any examples for a particular target value can never predict that target value! For other attributes, values may consist of a single value (a constant attribute) or all unique values (an identifier attribute), each of which may be excluded during mining. Values from categorical predictor attributes that didn't appear in the training data are not used when testing or scoring datasets. In subsequent posts, we'll talk about three sampling techniques using Oracle Database: simple random sampling without replacement, stratified sampling, and simple random sampling with replacement.

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  • Big Data – Buzz Words: What is NoSQL – Day 5 of 21

    - by Pinal Dave
    In yesterday’s blog post we explored the basic architecture of Big Data . In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – NoSQL. What is NoSQL? NoSQL stands for Not Relational SQL or Not Only SQL. Lots of people think that NoSQL means there is No SQL, which is not true – they both sound same but the meaning is totally different. NoSQL does use SQL but it uses more than SQL to achieve its goal. As per Wikipedia’s NoSQL Database Definition – “A NoSQL database provides a mechanism for storage and retrieval of data that uses looser consistency models than traditional relational databases.“ Why use NoSQL? A traditional relation database usually deals with predictable structured data. Whereas as the world has moved forward with unstructured data we often see the limitations of the traditional relational database in dealing with them. For example, nowadays we have data in format of SMS, wave files, photos and video format. It is a bit difficult to manage them by using a traditional relational database. I often see people using BLOB filed to store such a data. BLOB can store the data but when we have to retrieve them or even process them the same BLOB is extremely slow in processing the unstructured data. A NoSQL database is the type of database that can handle unstructured, unorganized and unpredictable data that our business needs it. Along with the support to unstructured data, the other advantage of NoSQL Database is high performance and high availability. Eventual Consistency Additionally to note that NoSQL Database may not provided 100% ACID (Atomicity, Consistency, Isolation, Durability) compliance.  Though, NoSQL Database does not support ACID they provide eventual consistency. That means over the long period of time all updates can be expected to propagate eventually through the system and data will be consistent. Taxonomy Taxonomy is the practice of classification of things or concepts and the principles. The NoSQL taxonomy supports column store, document store, key-value stores, and graph databases. We will discuss the taxonomy in detail in later blog posts. Here are few of the examples of the each of the No SQL Category. Column: Hbase, Cassandra, Accumulo Document: MongoDB, Couchbase, Raven Key-value : Dynamo, Riak, Azure, Redis, Cache, GT.m Graph: Neo4J, Allegro, Virtuoso, Bigdata As of now there are over 150 NoSQL Database and you can read everything about them in this single link. Tomorrow In tomorrow’s blog post we will discuss Buzz Word – Hadoop. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Kipróbálható az ingyenes új Oracle Data Miner 11gR2 grafikus workflow-val

    - by Fekete Zoltán
    Oracle Data Mining technológiai információs oldal. Oracle Data Miner 11g Release 2 - Early Adopter oldal. Megjelent, letöltheto és kipróbálható az Oracle Data Mining, az Oracle adatbányászat új grafikus felülete, az Oracle Data Miner 11gR2. Az Oracle Data Minerhez egyszeruen az SQL Developer-t kell letöltenünk, mivel az adatbányászati felület abból indítható. Az Oracle Data Mining az Oracle adatbáziskezelobe ágyazott adatbányászati motor, ami az Oracle Database Enterprise Edition opciója. Az adatbányászat az adattárházak elemzésének kifinomult eszköze és folyamata. Az Oracle Data Mining in-database-mining elonyeit felvonultatja: - nincs felesleges adatmozgatás, a teljes adatbányászati folyamatban az adatbázisban maradnak az adatok - az adatbányászati modellek is az Oracle adatbázisban vannak - az adatbányászati eredmények, cluster adatok, döntések, valószínuségek, stb. szintén az adatbázisban keletkeznek, és ott közvetlenül elemezhetoek Az új ingyenes Data Miner felület "hatalmas gazdagodáson" ment keresztül az elozo verzióhoz képest. - grafikus adatbányászati workflow szerkesztés és futtatás jelent meg! - továbbra is ingyenes - kibovült a felület - új elemzési lehetoségekkel bovült - az SQL Developer 3.0 felületrol indítható, ez megkönnyíti az adatbányászati funkciók meghívását az adatbázisból, ha épp nem a grafikus felületetet szeretnénk erre használni Az ingyenes Data Miner felület az Oracle SQL Developer kiterjesztéseként érheto el, így az elemzok közvetlenül dolgozhatnak az adatokkal az adatbázisban és a Data Miner grafikus felülettel is, építhetnek és kiértékelhetnek, futtathatnak modelleket, predikciókat tehetnek és elemezhetnek, támogatást kapva az adatbányászati módszertan megvalósítására. A korábbi Oracle Data Miner felület a Data Miner Classic néven fut és továbbra is letöltheto az OTN-rol. Az új Data Miner GUI-ból egy képernyokép: Milyen feladatokra ad megoldási lehetoséget az Oracle Data Mining: - ügyfél viselkedés megjövendölése, prediktálása - a "legjobb" ügyfelek eredményes megcélzása - ügyfél megtartás, elvándorlás kezelés (churn) - ügyfél szegmensek, klaszterek, profilok keresése és vizsgálata - anomáliák, visszaélések felderítése - stb.

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  • Big Data Accelerator

    - by Jean-Pierre Dijcks
    For everyone who does not regularly listen to earnings calls, Oracle's Q4 call was interesting (as it mostly is). One of the announcements in the call was the Big Data Accelerator from Oracle (Seeking Alpha link here - slightly tweaked for correctness shown below):  "The big data accelerator includes some of the standard open source software, HDFS, the file system and a number of other pieces, but also some Oracle components that we think can dramatically speed up the entire map-reduce process. And will be particularly attractive to Java programmers [...]. There are some interesting applications they do, ETL is one. Log processing is another. We're going to have a lot of those features, functions and pre-built applications in our big data accelerator."  Not much else we can say right now, more on this (and Big Data in general) at Openworld!

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  • Big Data Learning Resources

    - by Lara Rubbelke
    I have recently had several requests from people asking for resources to learn about Big Data and Hadoop. Below is a list of resources that I typically recommend. I'll update this list as I find more resources. Let's crowdsource this... Tell me your favorite resources and I'll get them on the list! Books and Whitepapers Planning for Big Data Free e-book Great primer on the general Big Data space. This is always my recommendation for people who are new to Big Data and are trying to understand it....(read more)

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  • E-Book on big data (featuring Analysts, Customers and more)

    - by Jean-Pierre Dijcks
    As we are gearing up for Openworld, here is a nice E-book on big data to start paging through. It contains Gartner's take on big data, customer and partner interviews and a lot more good info. Enjoy the read so you come prepared for Openworld!! Read the E-Book here. For those coming to Oracle Openworld (or the Americas Cup races around the same time), you can find big data sessions via this URL. Enjoy!!

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  • Google analytics ignoring "required step" in goals

    - by Matt Huggins
    I am A/B testing a landing page to see which converts better. The funnels are set up exactly the same in terms of the goal completion URL and funnel steps, with one exception: the first step (which is a required step) has a different URL to represent each of the two landing pages. Unfortunately, Google is tracking a conversion for both of these goals regardless of which landing page a user is reaching! It looks like the "required step" is broken...perhaps it is a deeper issue if others haven't noticed it, such as it only not working when the goal URL is the same between multiple goals. Here is an example of what I mean. Goal 1: Goal URL: /users/dashboard (head match) Funnel: 1. /homepages/index1 (required step) 2. /users/register 3. /users/edit Goal 2: Goal URL: /users/dashboard (head match) Funnel: 1. /homepages/index2 (required step) 2. /users/register 3. /users/edit As you can see, the only difference is step #1 of the funnel. Since I am A/B testing the landing page of the site, this should be the only difference. However, when I look at the goal page of Google Analytics, I see that the goal is being recorded for both of these regardless of the landing page being reached. The only tinkering I've done is attempting to wrap each funnel step's goal in ^ and $ characters for an exact regular expression match, but this didn't make a difference. Thoughts?

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  • timetable in a jTable

    - by chandra
    I want to create a timetable in a jTable. For the top row it will display from monday to sunday and the left colume will display the time of the day with 2h interval e.g 1st colume (0000 - 0200), 2nd colume (0200 - 0400) .... And if i click a button the timing will change from 2h interval to 1h interval. I do not want to hardcode it because i need to do for 2h, 1h, 30min , 15min, 1min, 30sec and 1 sec interval and it will take too long for me to hardcode. Can anyone show me an example or help me create an example for the 2h to 1h interval so that i know what to do? The data array is for me to store data and are there any other easier or shortcuts for me to store them because if it is in 1 sec interval i got thousands of array i need to type it out. private void oneHour() //1 interval functions { if(!once) { initialize(); once = true; } jTable.setModel(new javax.swing.table.DefaultTableModel( new Object [][] { {"0000 - 0100", data[0][0], data[0][1], data[0][2], data[0][3], data[0][4], data[0][5], data[0][6]}, {"0100 - 0200", data[2][0], data[2][1], data[2][2], data[2][3], data[2][4], data[2][5], data[2][6]}, {"0200 - 0300", data[4][0], data[4][1], data[4][2], data[4][3], data[4][4], data[4][5], data[4][6]}, {"0300 - 0400", data[6][0], data[6][1], data[6][2], data[6][3], data[6][4], data[6][5], data[6][6]}, {"0400 - 0600", data[8][0], data[8][1], data[8][2], data[8][3], data[8][4], data[8][5], data[8][6]}, {"0600 - 0700", data[10][0], data[4][1], data[10][2], data[10][3], data[10][4], data[10][5], data[10][6]}, {"0700 - 0800", data[12][0], data[12][1], data[12][2], data[12][3], data[12][4], data[12][5], data[12][6]}, {"0800 - 0900", data[14][0], data[14][1], data[14][2], data[14][3], data[14][4], data[14][5], data[14][6]}, {"0900 - 1000", data[16][0], data[16][1], data[16][2], data[16][3], data[16][4], data[16][5], data[16][6]}, {"1000 - 1100", data[18][0], data[18][1], data[18][2], data[18][3], data[18][4], data[18][5], data[18][6]}, {"1100 - 1200", data[20][0], data[20][1], data[20][2], data[20][3], data[20][4], data[20][5], data[20][6]}, {"1200 - 1300", data[22][0], data[22][1], data[22][2], data[22][3], data[22][4], data[22][5], data[22][6]}, {"1300 - 1400", data[24][0], data[24][1], data[24][2], data[24][3], data[24][4], data[24][5], data[24][6]}, {"1400 - 1500", data[26][0], data[26][1], data[26][2], data[26][3], data[26][4], data[26][5], data[26][6]}, {"1500 - 1600", data[28][0], data[28][1], data[28][2], data[28][3], data[28][4], data[28][5], data[28][6]}, {"1600 - 1700", data[30][0], data[30][1], data[30][2], data[30][3], data[30][4], data[30][5], data[30][6]}, {"1700 - 1800", data[32][0], data[32][1], data[32][2], data[32][3], data[32][4], data[32][5], data[32][6]}, {"1800 - 1900", data[34][0], data[34][1], data[34][2], data[34][3], data[34][4], data[34][5], data[34][6]}, {"1900 - 2000", data[36][0], data[36][1], data[36][2], data[36][3], data[36][4], data[36][5], data[36][6]}, {"2000 - 2100", data[38][0], data[38][1], data[38][2], data[38][3], data[38][4], data[38][5], data[38][6]}, {"2100 - 2200", data[40][0], data[40][1], data[40][2], data[40][3], data[40][4], data[40][5], data[40][6]}, {"2200 - 2300", data[42][0], data[42][1], data[42][2], data[42][3], data[42][4], data[42][5], data[42][6]}, {"2300 - 2400", data[44][0], data[44][1], data[44][2], data[44][3], data[44][4], data[44][5], data[44][6]}, {"2400 - 0000", data[46][0], data[46][1], data[46][2], data[46][3], data[46][4], data[46][5], data[46][6]}, }, new String [] { "Time/Day", "(Mon)", "(Tue)", "(Wed)", "(Thurs)", "(Fri)", "(Sat)", "(Sun)" } )); } private void twoHour() //2 hour interval functions { if(!once) { initialize(); once = true; } jTable.setModel(new javax.swing.table.DefaultTableModel( new Object [][] { {"0000 - 0200", data[0][0], data[0][1], data[0][2], data[0][3], data[0][4], data[0][5], data[0][6]}, {"0200 - 0400", data[4][0], data[4][1], data[4][2], data[4][3], data[4][4], data[4][5], data[4][6]}, {"0400 - 0600", data[8][0], data[8][1], data[8][2], data[8][3], data[8][4], data[8][5], data[8][6]}, {"0600 - 0800", data[12][0], data[12][1], data[12][2], data[12][3], data[12][4], data[12][5], data[12][6]}, {"0800 - 1000", data[16][0], data[16][1], data[16][2], data[16][3], data[16][4], data[16][5], data[16][6]}, {"1000 - 1200", data[20][0], data[20][1], data[20][2], data[20][3], data[20][4], data[20][5], data[20][6]}, {"1200 - 1400", data[24][0], data[24][1], data[24][2], data[24][3], data[24][4], data[24][5], data[24][6]}, {"1400 - 1600", data[28][0], data[28][1], data[28][2], data[28][3], data[28][4], data[28][5], data[28][6]}, {"1600 - 1800", data[32][0], data[32][1], data[32][2], data[32][3], data[32][4], data[32][5], data[32][6]}, {"1800 - 2000", data[36][0], data[36][1], data[36][2], data[36][3], data[36][4], data[36][5], data[36][6]}, {"2000 - 2200", data[40][0], data[40][1], data[40][2], data[40][3], data[40][4], data[40][5], data[40][6]}, {"2200 - 2400",data[44][0], data[44][1], data[44][2], data[44][3], data[44][4], data[44][5], data[44][6]} },

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  • Oracle's Primavera P6 Analytics Now Available!

    - by mark.kromer
    Oracle's Primavera product team has announced this week that general availability of our first Oracle BI (OBI) based analytical product with pre-built business intelligence dashboards, reports and KPIs built in. P6 Analytics uses OBI's drill-down capabilities, summarizations, hierarchies and other BI features to provide knowledge to your business users to make the best decisions on portfolios, projects, schedules & resources with deep insights. Without needing to launch into the P6 tool, your executives, PMO, project sponsors, etc. can view up to date project performance information as well as historic trends of project performance. Using web-based portal technology, P6 Analytics makes it easy to manage by exception and then drill down to quickly identify root cause analysis of problem projects. At the same time, a brand new version of the P6 Reporting Database R2 was just announded and is also now available. This updated reporting database provides you with 4 star schemas with spread data and includes P6 activity, project and resource codes. You can use the data warehouse and ETL functions of the P6 Reporting Database R2 with your own reporting tools or build dashboards that utilize the hierarchies & drill down to the day-level on scheduled activities using Busines Objects, Cognos, Microsoft, etc. Both of these products can be downloaded from E-Delivery under the Primavera applications section in the P6 EPPM v7.0 media pack. I put some examples below of the resource utilization, earned value, landing page and portfolio analysis dashboards that come out of the box with P6 Analytics to give you these deep insights into your projects & portfolios on day 1 of using the tool. Please send an email to Karl or me if you have any questions or would like more information. Oracle Technology Network and the Oracle.com marketing sites are currently being refreshed with further details of these exciting new releases of the Primavera BI and data warehouse products. Lastly, scroll below for some screenshots of the new P6 Analytics R1 product using OBIEE! Thanks, Mark Kromer

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  • Google Analytics checkout page tracking problem

    - by Amir E. Habib
    I am running a multilingual website, each lang on a different domain name. I am trying to lead all purchase requests to the checkout progress, which has its own domain too. In order to keep Google Analytics tracking I've updated the Google Analytics code accordingly. I set the source domain to 'multiple top-level domains'. Everything is going fine so far unless in E-commerce Overview; the "Sources / Medium" is always showing as (direct) - or the name of the source domain. Since I am redirecting using PHP header(location:.. etc.) the Google _link method doesn't seem to be working properly - I want to focus on two questions: Should I create a new profile for the checkout domain in Google Analytics? (I am now using the profile ID of the source domain even though I move to the checkout domain, si that OK?) When I'm trying to pass the cookies of the source domain to the checkout domain, I notice that the Google cookies are copied to the new domain (the cookie path is .checkout-domain/) and they have the same values of the original cookies - But for some reason another set of cookies is created once I access a page with google analytics code in the checkout pages, with different values (same path). Feels like I'm doing something wrong here, so my question is - What am I doing wrong here? Does anyone have an idea how to pass the cookies to the checkout domain?

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  • Wordpress Multisite and Google Analytics in subfolders with mapped domains

    - by David
    I have a wordpress multisite with sub folders. The site's subfolders are mapped to domains, which are set to primary. I'm using the 'Google Analytics Multisite Async' code to track things. From what I can see it's tracking the sites fine (getting page hits for each site in google analytics) baring the original site in the Multisite which in content overview lists domains then the amount of traffic it's getting along with the orginal domains traffic. I don't want to track any other traffic for my orginal site than what goes to that. i.e. I don't want it tracking my other sites in multi-site. e.g. domain1.com is my orginal and I have lots of other sites in the multisite lets say domain2.com, domain3.com. In content overview in Analytics it's listing say domain2.com as content. Can I tell it to filter these out some how either in Analytics or within WordPress? Hopefully explained that clearly!

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