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  • Data Mining Introduction

    Many people that work for years with SQL Server never use the Data Mining. This article has the objective to introduce them to this magic and exciting new world. 24% of devs don’t use database source control – make sure you aren’t one of themVersion control is standard for application code, but databases haven’t caught up. So what steps can you take to put your SQL databases under version control? Why should you start doing it? Read more to find out…

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  • July SQL Server UG Event in Manchester

    I will be speaking at the SQL Server UK User Group event in Manchester on 16.07.2009.  I am going to be talking about data mining again and how it isn’t all statistics and people with PhDs from Oxford.  Come join me and the excellent Chris Testa-O’Neill.  More details and registration can be found here

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  • WebCenter Customer Spotlight: Hitachi Data Systems

    - by me
    Author: Peter Reiser - Social Business Evangelist, Oracle WebCenter Watch this Webcast to see a live demo on how HDS creates multilingual content for their 35+ regional websites  Solution SummaryHitachi Data Systems (HDS) provides mid-range and high-end storage systems, software and services. It is a wholly owned subsidiary of Hitachi Ltd. HDS is based in Santa Clara, California, and has over 5,300 employees in more then 100 countries and regions. HDS's main objectives were to provide a consistent message across all their sites, to maintain a tight governance structure across their messages and related content, expand the use of the existing content management systems and implement a centralized translation management system. HDS implemented a global web content management system based on Oracle WebCenter Content and integrated the Lingotek translation management system to manage their multilingual content. The implemented solution provides each Geo with the ability to expand their web offering to meet local market needs, while staying aligned with the Corporate Web Guidelines Company OverviewHitachi Data Systems (HDS) provides mid-range and high-end storage systems, software and services. It is a wholly owned subsidiary of Hitachi Ltd. and part of the Hitachi Information Systems & Telecommunications Division. The company sells through direct and indirect channels in more than 170 countries and regions. Its customers include of 50 percent of the Fortune 100 companies. HDS is based in Santa Clara California and has over 5,300 employees in more than 100 countries and regions. Business ChallengesHDS has over 35 global websites and the lack of global web capabilities led to inconsistency of messaging, slower time to market and failed to address local language needs. There was an extensive operational overhead due to manual and redundant processes. Translation efforts where superficial, inconsistent and wasteful and the lack of translation automation tools discouraged localization.  HDS's main objectives were to provide a consistent message across all their sites, to maintain a tight governance structure across their messages and related content, expand the use of the existing content management systems and implement a centralized translation management system. Solution DeployedHDS implemented a global web content management system based on Oracle WebCenter Content. The solution supports decentralized publishing for their 35+ global sites to address local market needs while ensuring editorial and brand review trough embedded review processes. They integrated the Lingotek translation management system into Oracle WebCenter Content to manage their multilingual content. Business Results Provides each Geo with the ability to expand their web offering to meet local market needs, while staying aligned with the Corporate Web Guidelines Enables end-to-end content lifecycle management across multiple languages Leverage translation memory for reuse and consistency Reduce time to market with central repository of translated content Additional Information HDS Webcast Oracle WebCenter Content Lingotek website

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  • Oracle as a Data Source

    This article takes a quick look at Oracle database's materialized view and extends the concept of that feature to a case where Oracle is the data source for another relational database management system.

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  • Business layer access to the data layer

    - by rerun
    I have a Business layer (BL) and a Data layer (DL). I have an object o with a child objects collection of Type C. I would like to provide a semantics like the following o.Children.Add("info"). In the BL I would like to have a static CLASS that all of business layer classes uses to get a reference to the current datalayer instance. Is there any issue with that or must I use the factory pattern to limit creation to A class in the BL that knows the DL instance.

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  • Using NBuilder to mock up a data driven UI - Part 1

    In this article we will take a look at a fairly new open source project called NBuilder (http://www.nbuilder.org and http://code.google.com/p/nbuilder/) and how it can be used to provide us with fake data out of the gate. NBuilder allows you to quickly stand up generated objects based on standard .net types in an easy fluent manner. And that is just the start!

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  • Resolving data redundancy up front

    - by okeofs
    Introduction As all of us do when confronted with a problem, the resource of choice is to ‘Google it’. This is where the plot thickens. Recently I was asked to stage data from numerous databases which were to be loaded into a data warehouse. To make a long story short, I was looking for a manner in which to obtain the table names from each database, to ascertain potential overlap.   As the source data comes from a SQL database created from dumps of a third party product,  one could say that there were +/- 95 tables for each database.   Yes I know that first instinct is to use the system stored procedure “exec sp_msforeachdb 'select "?" AS db, * from [?].sys.tables'”. However, if one stops to think about this, it would be nice to have all the results in a temporary or disc based  table; which in itself , implies additional labour. This said,  I decided to ‘re-invent’ the wheel. The full code sample may be found at the bottom of this article.   Define a few temporary tables and variables   declare @SQL varchar(max); declare @databasename varchar(75) /* drop table ##rawdata3 drop table #rawdata1 drop table #rawdata11 */ -- A temp table to hold the names of my databases CREATE TABLE #rawdata1 (    database_name varchar(50) ,    database_size varchar(50),    remarks Varchar(50) )     --A temp table with the same database names as above, HOWEVER using an --Identity number (recNO) as a loop variable. --You will note below that I loop through until I reach 25 (see below) as at --that point the system databases, the reporting server database etc begin. --1- 24 are user databases. These are really what I was looking for. --Whilst NOT the best solution,it works and the code was meant as a quick --and dirty. CREATE TABLE #rawdata11 (    recNo int identity(1,1),    database_name varchar(50) ,    database_size varchar(50),    remarks Varchar(50) )   --My output table showing the database name and table name CREATE TABLE ##rawdata3 (    database_name varchar(75) ,    table_name varchar(75), )   Insert the database names into a temporary table I pull the database names using the system stored procedure sp_databases   INSERT INTO #rawdata1 EXEC sp_databases Go   Insert the results from #rawdata1 into a table containing a record number  #rawdata11 so that I can LOOP through the extract   INSERT into #rawdata11 select * from  #rawdata1   We now declare 3 more variables:  @kounter is used to keep track of our position within the loop. @databasename is used to keep track of the’ current ‘ database name being used in the current pass of the loop;  as inorder to obtain the tables for that database we  need to issue a ‘USE’ statement, an insert command and other related code parts. This is the challenging part. @sql is a varchar(max) variable used to contain the ‘USE’ statement PLUS the’ insert ‘ code statements. We now initalize @kounter to 1 .   declare @kounter int; declare @databasename varchar(75); declare @sql varchar(max); set @kounter = 1   The Loop The astute reader will remember that the temporary table #rawdata11 contains our  database names  and each ‘database row’ has a record number (recNo). I am only interested in record numbers under 25. I now set the value of the temporary variable @DatabaseName (see below) .Note that I used the row number as a part of the predicate. Now, knowing the database name, I can create dynamic T-SQL to be executed using the sp_sqlexec stored procedure (see the code in red below). Finally, after all the tables for that given database have been placed in temporary table ##rawdata3, I increment the counter and continue on. Note that I used a global temporary table to ensure that the result set persists after the termination of the run. At some stage, I plan to redo this part of the code, as global temporary tables are not really an ideal solution.    WHILE (@kounter < 25)  BEGIN  select @DatabaseName = database_name from #rawdata11 where recNo = @kounter  set @SQL = 'Use ' + @DatabaseName + ' Insert into ##rawdata3 ' + + ' SELECT table_catalog,Table_name FROM information_schema.tables' exec sp_sqlexec  @Sql  SET @kounter  = @kounter + 1  END   The full code extract   Here is the full code sample.   declare @SQL varchar(max); declare @databasename varchar(75) /* drop table ##rawdata3 drop table #rawdata1 drop table #rawdata11 */ CREATE TABLE #rawdata1 (    database_name varchar(50) ,    database_size varchar(50),    remarks Varchar(50) ) CREATE TABLE #rawdata11 (    recNo int identity(1,1),    database_name varchar(50) ,    database_size varchar(50),    remarks Varchar(50) ) CREATE TABLE ##rawdata3 (    database_name varchar(75) ,    table_name varchar(75), )   INSERT INTO #rawdata1 EXEC sp_databases go INSERT into #rawdata11 select * from  #rawdata1 declare @kounter int; declare @databasename varchar(75); declare @sql varchar(max); set @kounter = 1 WHILE (@kounter < 25)  BEGIN  select @databasename = database_name from #rawdata11 where recNo = @kounter  set @SQL = 'Use ' + @DatabaseName + ' Insert into ##rawdata3 ' + + ' SELECT table_catalog,Table_name FROM information_schema.tables' exec sp_sqlexec  @Sql  SET @kounter  = @kounter + 1  END    select * from ##rawdata3  where table_name like '%SalesOrderHeader%'

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  • GDD-BR 2010 [0H] OpenID-based single sign-on and OAuth data access

    GDD-BR 2010 [0H] OpenID-based single sign-on and OAuth data access Speaker: Ryan Boyd Track: Chrome and HTML5 Time slot: H[17:20 - 18:05] Room: 0 A discussion of all the auth tangles you've encountered so far -- OpenID, SSO, 2-Legged OAuth, 3-Legged OAuth, and Hybrid OAuth. We'll show you when and where to use them, and explain how they all integrate with Google APIs and other developer products. From: GoogleDevelopers Views: 11 0 ratings Time: 41:24 More in Science & Technology

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  • Managing Data Growth in SQL Server

    'Help, my database ate my disk drives!'. Many DBAs spend most of their time dealing with variations of the problem of database processes consuming too much disk space. This happens because of errors such as incorrect configurations for recovery models, data growth for large objects and queries that overtax TempDB resources. Rodney describes, with some feeling, the errors that can lead to this sort of crisis for the working DBA, and their solution.

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  • How to optimise mesh data

    - by Wardy
    So i have some procedurally generated mesh data and i want to reduce it down to its minimum number of verts. In case it matters this is a unity project. Working on the basis of a simple example, lets assume a typical flat surface of points 2 by 3. The point / vertex at [1,1] is used in many triangles. I've generated mesh for a voxel type engine that adds verts to a list based on face visiblility and now I want to remove all the duplicates. Can anyone come up with an efficient way of doing this because what i have is sooo bad its not even funny (and i don't even think it's logically correct) ... private void Optimize() { Vector3 v; Vector3 v2; for (int i = 0; i < Vertices.Count; i++) { v = Vertices[i]; for (int j = i+1; j < Vertices.Count; j++) { v2 = Vertices[j]; if (v.x == v2.x && v.y == v2.y && v.z == v2.z) { for (int ind = 0; ind < Indices.Count; ind++) { if (Indices[ind] == j) { Indices[ind] = i; } else if (Indices[ind] > j && Indices[ind] > 0) Indices[ind]--; } Vertices.RemoveAt(j); Uvs.RemoveAt(j); Normals.RemoveAt(j); } } } } EDIT: Ok i managed to get this (code sample above updated) to render an "optimised" set of verts but the UV data is all wrong now, which would make sense because i'm basically just removing any UV Vector that represents a UV coord for a removed vert and not actually considering what I need to do to "fix the tri" so to speak. The code now seemingly does work but its quite time consuming, still looking to further optimise.

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  • Virtualized data centre&ndash;Part three: Architecture

    - by marc dekeyser
    Having the basics (like discussed in the previous articles) is all good and well, but how do we get started on this?! It can be quite daunting after all!   From my own point of view I can absolutely confirm your worries and concerns, but also tell you that it is not as hard as it seems! Deciding on what kind of motherboard to buy, processor and how much memory is an activity you will spend quite some time doing research on. And that is not even mentioning storage! All in all it comes down to setting you expectations and your budget. Probably adjusting your expectations according to your budget :). Processors As a rule of thumb you want VT-D (virtualization) technology built in to the processor allowing you to have 64 bit machines running on your host. Memory The more the better! If you are building a home lab don’t bother with ECC unless you are going to run machines that absolutely should be on all the time and your comfort depends on it! Motherboard Depends on what you are going to do with storage: If you are going the NAS way then the number of SATA port/RAID capabilities do not really matter. If you decide to have a single server with lots of dedicated storage it obviously matters how much SATA ports you will have, alternatively you could use a RAID controller (but these set you back a pretty penny if you want one. DELL 6i’s are usually available for a good bargain if you can find one!). Easiest is to get one with a built-in graphics card (on-board) as you are just adding more heat, power usage and possible points of failure. Networking Just like your choice of motherboard the networking side tends to depend on how you want to go. A single virtualization  host with local storage can usually get away with having a single network card, a cluster or server which uses iSCSI storage tends to have more than one teamed up :). Storage The dreaded beast from the dark! The horror which lives in the forest! The most difficult decision you are going to make in the building of your lab. Why you might ask? Simple my friend, having the right choice of storage can make or break your virtualization solution. The performance of you storage choice will have an important impact on the responsiveness of your virtual machines and the deployment of new machines. It also makes a run with your budget! If you decide to go the NAS route you will be dropping a lot more money than if you would be having just a bunch of disks sitting in a server and manually distributing the virtual machines over the disks. Platform I’m a Microsoftee so Hyper-V is a dead giveaway for me. If you are interested in using VMware I won’t stop you but the rest of my posts will be oriented on Server 2012 Hyper-V (aka 3.0)! What did I use? Before someone asks me this in the comments I’ll give you a quick run down of what I am using. - Intel 2.4 quad core processors (i something something) - 24 GB DDR3 Memory - Single disk in each server (might look at this as I move the servers to 2012) - Synology DS1812+ NAS - 3 network interfaces where possible - HP1800 procurve managed switch I decided to spring for the NAS as I will also be using it for backups and media storage (which is working out quite nicely with my Xbox 360 I must say). At the time of building my 2 boxes (over a year and a half ago) these set me back about 900 euros each so I can image you can build the same or better for a lower price. Next article will be diagramming what I want to achieve and starting a build on the Hyper V 3.0 cluster!

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  • Using NumPy arrays as 2D mathematical vectors?

    - by CorundumGames
    Right now I'm using lists as position, velocity, and acceleration vectors in my game. Is that a better option than using NumPy's arrays (not the standard library's) as vectors (with float data types)? I'm frequently adding vectors and changing their values directly, then placing the values in these vectors into a Pygame Rect. The vector is used for position (because Rects can't hold floats, so we can't go "between" pixels), and the Rect is used for rendering (because Pygame will only take in Rects for rendering positions).

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  • Parallel Data Warehouse

    - by jchang
    The Microsoft Parallel Data Warehouse diagram was somewhat difficult to understand in terms of the functionality of each subsystem in relation to the configuration of its components. So now that HP has provided a detailed list of the PDW components , the diagram below shows the PDW subsystems with component configuration (InfiniBand, FC, and network connections not shown). Observe that there are three different ProLiant server models, the DL360 G7, DL370 G6 and the DL380 G7, in five different configurations...(read more)

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  • Tournament bracket method to put distance between teammates

    - by Fred Thomsen
    I am using a proper binary tree to simulate a tournament bracket. It's preferred any competitors in the bracket that are teammates don't meet each other until the later rounds. What is an efficient method in which I can ensure that teammates in the bracket have as much distance as possible from each other? Are there any other data structures besides a tree that would be better for this purpose? EDIT: There can be more than 2 teams represented in a bracket.

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  • Data searches that leverage existing indexes

    Recent installments of our SQL Server 2005 Express Edition series have been discussing its implementation of Full Text Indexing. This article focuses on data searches, which leverage existing indexes, taking into account such features as noise words and thesaurus files.

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  • Read how a customer uses Oracle NoSQL Database

    - by Jean-Pierre Dijcks
    For those who have had the pleasure to be in SF for Oracle Openworld, you might have seen or heard about this story already. If you did not, here is a great story on how to use Oracle NoSQL Database. Apart from all the cool technology, I'm just excited that this is a company founded by a football international and dealing with sports data, games and other cool things. Like an all things cool combo in one place.

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