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  • Oracle Healthcare Data Warehouse Foundations RELEASED!

    - by Glen McCallum
    Since I joined Oracle I've been working on Oracle Healthcare Data Warehouse Foundations (OHDF). It was officially released earlier this month at HIMSS. But for over 2 months prior to that I had to keep it a secret. It was so tough; I didn't even tell my family when they asked me what I was working on. Anyway, OHDF is an enterprise healthcare data model. Unlike Healthcare Transaction Base, OHDF is in 3rd normal form. It is logical and reasonably easy to understand for anyone with some experience in the healthcare domain. OHDF is emerging as the core of Oracle's healthcare business intelligence applications.

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  • Data Warehouse Best Practices

    - by jean-pierre.dijcks
    In our quest to share our endless wisdom (ahem…) one of the things we figured might be handy is recording some of the best practices for data warehousing. And so we did. And, we did some more… We now have recreated our websites on Oracle Technology Network and have a separate page for best practices, parallelism and other cool topics related to data warehousing. But the main topic of this post is the set of recorded best practices. Here is what is available (and it is a series that ties together but can be read independently), applicable for almost any database version: Partitioning 3NF schema design for a data warehouse Star schema design Data Loading Parallel Execution Optimizer and Stats management The best practices page has a lot of other useful information so have a look here.

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  • Oracle Warehouse Builder 11gR2 Windows-ra is

    - by Fekete Zoltán
    A héten megjelent az Oracle Database 11g Release 2 Windows platformra is, így lett teljes a kép a legfontosabb szerver operációs rendszerek körében, ezáltal az OWB kliens is hozzáférheto lett Windows-on. Az OWB az Oracle piacvezeto ETL eszköze, extraction, transformation, load - adatkinyerés, betöltés és átalakítás. Az Oracle Warehouse Builder Java-s kliens programja eddig is elérheto volt Linuxon, most már supportáltan megvan Windows-ra is (kis hegesztéssel eddig is lehetett a Linux-os Java-s változatot használni Windows-on). Az OWB vindózos kliens kétféle módon érheto el: - a Database 11gR2 Windows install készlet telepítésével automatikusan felkerül, letöltés - önállóan is felrakható más gépre (standalon), letöltés, itt a Linux kliens is megtalálható. Ez a standalone verzió most jelent meg az OTN-en 2-3 órája. :)

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  • Fast Track Data Warehouse 3.0 Reference Guide

    - by jchang
    Microsoft just release Fast Track Data Warehouse 3.0 Reference Guide version. The new changes are increased memory recommendation and the disks per RAID group change from 2-disk RAID 1 to 4-Disk RAID 10. Memory The earlier FTDW reference architecture cited 4GB memory per core. There was no rational behind this, but it was felt some rule was better than no rule. The new FTDW RG correctly cites the rational that more memory helps keep hash join intermediate results and sort operations in memory. 4-Disk...(read more)

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  • Oracle Insurance Gets Innovative with Insurance Business Intelligence

    - by nicole.bruns(at)oracle.com
    Oracle Insurance announced yesterday the availability of Oracle Insurance Insight 7.0, an insurance-specific data warehouse and business intelligence (BI) system that transforms the traditional approach to BI by involving business users in the creation and maintenance."Rapid access to business intelligence is essential to compete and thrive in today's insurance industry," said Srini Venkatasantham, vice president, Product Strategy, Oracle Insurance. "The adaptive data modeling approach of Oracle Insurance Insight 7.0, combined with the insurance-specific data model, offers global insurance companies a faster, easier way to get the intelligence they need to make better-informed business decisions." New Features in Oracle Insurance 7.0 include:"Adaptive Data Modeling" via the new warehouse palette: Gives business users the power to configure lines of business via an easy-to-use warehouse palette tool. Oracle Insurance Insight then automatically creates data warehouse elements - such as line-specific database structures and extract-transform-load (ETL) processes -speeding up time-to-value for BI initiatives. Out-of-the-box insurance models or create-from-scratch option: Includes pre-built content and interfaces for six Property and Casualty (P&C) lines. Additionally, insurers can use the warehouse palette to deploy any and all P&C or General Insurance lines of business from scratch, helping insurers support operations in any country.Leverages Oracle technologies: In addition to Oracle Business Intelligence Enterprise Edition, the solution includes Oracle Database 11g as well as Oracle Data Integrator Enterprise Edition 11g, which delivers Extract, Load and Transform (E-L-T) architecture and eliminates the need for a separate transformation server. Additionally, the expanded Oracle technology infrastructure enables support for Oracle Exadata. Martina Conlon, a Principal with Novarica's Insurance practice, and author of Business Intelligence in Insurance: Current State, Challenges, and Expectations says, "The need for continued investment by insurers in business intelligence capabilities is widely understood, and the industry is acting. Arming the business intelligence implementation with predefined insurance specific content, and flexible and configurable technology will get these projects up and running faster."Learn moreTo see a demo of the Oracle Insurance Insight system, click hereTo read the press announcement, click here

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  • Details on Oracle's Primavera P6 Reporting Database R2

    - by mark.kromer
    Below is a graphic screenshot of our detailed announcement for the new Oracle data warehouse product for Primavera P6 called P6 Reporting Database R2. This DW product includes the ETL, data warehouse star schemas and ODS that you'll need to build an enterprise reporting solution for your projects & portfolios. This product is included on a restricted license basis with the new Primavera P6 Analytics R1 product from Oracle because those Analytics are built in OBIEE based on this data warehouse product.

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  • PASS Business Intelligence Virtual Chapter Upcoming Sessions (November 2013)

    - by Sergio Govoni
    Let me point out the upcoming live events, dedicated to Business Intelligence with SQL Server, that PASS Business Intelligence Virtual Chapter has scheduled for November 2013. The "Accidental Business Intelligence Project Manager"Date: Thursday 7th November - 8:00 PM GMT / 3:00 PM EST / Noon PSTSpeaker: Jen StirrupURL: https://attendee.gotowebinar.com/register/5018337449405969666 You've watched the Apprentice with Donald Trump and Lord Alan Sugar. You know that the Project Manager is usually the one gets firedYou've heard that Business Intelligence projects are prone to failureYou know that a quick Bing search for "why do Business Intelligence projects fail?" produces a search result of 25 million hits!Despite all this… you're now Business Intelligence Project Manager – now what do you do?In this session, Jen will provide a "sparks from the anvil" series of steps and working practices in Business Intelligence Project Management. What about waterfall vs agile? What is a Gantt chart anyway? Is Microsoft Project your friend or a problematic aspect of being a BI PM? Jen will give you some ideas and insights that will help you set your BI project right: assess priorities, avoid conflict, empower the BI team and generally deliver the Business Intelligence project successfully! Dimensional Modelling Design Patterns: Beyond BasicsDate: Tuesday 12th November - Noon AEDT / 1:00 AM GMT / Monday 11th November 5:00 PM PSTSpeaker: Jason Horner, Josh Fennessy and friendsURL: https://attendee.gotowebinar.com/register/852881628115426561 This session will provide a deeper dive into the art of dimensional modeling. We will look at the different types of fact tables and dimension tables, how and when to use them. We will also some approaches to creating rich hierarchies that make reporting a snap. This session promises to be very interactive and engaging, bring your toughest Dimensional Modeling quandaries. Data Vault Data Warehouse ArchitectureDate: Tuesday 19th November - 4:00 PM PST / 7 PM EST / Wednesday 20th November 11:00 PM AEDTSpeaker: Jeff Renz and Leslie WeedURL: https://attendee.gotowebinar.com/register/1571569707028142849 Data vault is a compelling architecture for an enterprise data warehouse using SQL Server 2012. A well designed data vault data warehouse facilitates fast, efficient and maintainable data integration across business systems. In this session Leslie and I will review the basics about enterprise data warehouse design, introduce you to the data vault architecture and discuss how you can leverage new features of SQL Server 2012 help make your data warehouse solution provide maximum value to your users. 

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  • Warehouse Management per Endeca: disponibili i video su Youtube

    - by Claudia Caramelli-Oracle
    12.00 Il team di gestione del prodotto WMS ha registrato quattro video sulle estensioni Warehouse Management per Endeca – il programma che gestisce in tempo reale le operazioni di magazzino. Quasi un'ora di contenuti che copre: Introduzione alle estensioni WMS per Endeca Plan and Track Fulfillment Space Utilization Labor Utilization Tutti e quattro i video possono essere trovati cliccando qui. v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} 12.00 Normal 0 14 false false false IT X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} 12.00 Normal 0 14 false false false IT X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} 12.00 Normal 0 14 false false false IT X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Normal 0 14 false false false IT X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";}

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  • Asserting with JustMock

    - by mehfuzh
    In this post, i will be digging in a bit deep on Mock.Assert. This is the continuation from previous post and covers up the ways you can use assert for your mock expectations. I have used another traditional sample of Talisker that has a warehouse [Collaborator] and an order class [SUT] that will call upon the warehouse to see the stock and fill it up with items. Our sample, interface of warehouse and order looks similar to : public interface IWarehouse {     bool HasInventory(string productName, int quantity);     void Remove(string productName, int quantity); }   public class Order {     public string ProductName { get; private set; }     public int Quantity { get; private set; }     public bool IsFilled { get; private set; }       public Order(string productName, int quantity)     {         this.ProductName = productName;         this.Quantity = quantity;     }       public void Fill(IWarehouse warehouse)     {         if (warehouse.HasInventory(ProductName, Quantity))         {             warehouse.Remove(ProductName, Quantity);             IsFilled = true;         }     }   }   Our first example deals with mock object assertion [my take] / assert all scenario. This will only act on the setups that has this “MustBeCalled” flag associated. To be more specific , let first consider the following test code:    var order = new Order(TALISKER, 0);    var wareHouse = Mock.Create<IWarehouse>();      Mock.Arrange(() => wareHouse.HasInventory(Arg.Any<string>(), 0)).Returns(true).MustBeCalled();    Mock.Arrange(() => wareHouse.Remove(Arg.Any<string>(), 0)).Throws(new InvalidOperationException()).MustBeCalled();    Mock.Arrange(() => wareHouse.Remove(Arg.Any<string>(), 100)).Throws(new InvalidOperationException());      //exercise    Assert.Throws<InvalidOperationException>(() => order.Fill(wareHouse));    // it will assert first and second setup.    Mock.Assert(wareHouse); Here, we have created the order object, created the mock of IWarehouse , then I setup our HasInventory and Remove calls of IWarehouse with my expected, which is called by the order.Fill internally. Now both of these setups are marked as “MustBeCalled”. There is one additional IWarehouse.Remove that is invalid and is not marked.   On line 9 ,  as we do order.Fill , the first and second setups will be invoked internally where the third one is left  un-invoked. Here, Mock.Assert will pass successfully as  both of the required ones are called as expected. But, if we marked the third one as must then it would fail with an  proper exception. Here, we can also see that I have used the same call for two different setups, this feature is called sequential mocking and will be covered later on. Moving forward, let’s say, we don’t want this must call, when we want to do it specifically with lamda. For that let’s consider the following code: //setup - data var order = new Order(TALISKER, 50); var wareHouse = Mock.Create<IWarehouse>();   Mock.Arrange(() => wareHouse.HasInventory(TALISKER, 50)).Returns(true);   //exercise order.Fill(wareHouse);   //verify state Assert.True(order.IsFilled); //verify interaction Mock.Assert(()=> wareHouse.HasInventory(TALISKER, 50));   Here, the snippet shows a case for successful order, i haven’t used “MustBeCalled” rather i used lamda specifically to assert the call that I have made, which is more justified for the cases where we exactly know the user code will behave. But, here goes a question that how we are going assert a mock call if we don’t know what item a user code may request for. In that case, we can combine the matchers with our assert calls like we do it for arrange: //setup - data  var order = new Order(TALISKER, 50);  var wareHouse = Mock.Create<IWarehouse>();    Mock.Arrange(() => wareHouse.HasInventory(TALISKER, Arg.Matches<int>( x => x <= 50))).Returns(true);    //exercise  order.Fill(wareHouse);    //verify state  Assert.True(order.IsFilled);    //verify interaction  Mock.Assert(() => wareHouse.HasInventory(Arg.Any<string>(), Arg.Matches<int>(x => x <= 50)));   Here, i have asserted a mock call for which i don’t know the item name,  but i know that number of items that user will request is less than 50.  This kind of expression based assertion is now possible with JustMock. We can extent this sample for properties as well, which will be covered shortly [in other posts]. In addition to just simple assertion, we can also use filters to limit to times a call has occurred or if ever occurred. Like for the first test code, we have one setup that is never invoked. For such, it is always valid to use the following assert call: Mock.Assert(() => wareHouse.Remove(Arg.Any<string>(), 100), Occurs.Never()); Or ,for warehouse.HasInventory we can do the following: Mock.Assert(() => wareHouse.HasInventory(Arg.Any<string>(), 0), Occurs.Once()); Or,  to be more specific, it’s even better with: Mock.Assert(() => wareHouse.HasInventory(Arg.Any<string>(), 0), Occurs.Exactly(1));   There are other filters  that you can apply here using AtMost, AtLeast and AtLeastOnce but I left those to the readers. You can try the above sample that is provided in the examples shipped with JustMock.Please, do check it out and feel free to ping me for any issues.   Enjoy!!

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  • PASS Summit Preconference and Sessions

    - by Davide Mauri
    I’m very pleased to announce that I’ll be delivering a Pre-Conference at PASS Summit 2012. I’ll speak about Business Intelligence again (as I did in 2010) but this time I’ll focus only on Data Warehouse, since it’s big topic even alone. I’ll discuss not only what is a Data Warehouse, how it can be modeled and built, but also how it’s development can be approached using and Agile approach, bringing the experience I gathered in this field. Building the Agile Data Warehouse with SQL Server 2012 http://www.sqlpass.org/summit/2012/Sessions/SessionDetails.aspx?sid=2821 I’m sure you’ll like it, especially if you’re starting to create a BI Solution and you’re wondering what is a Data Warehouse, if it is still useful nowadays that everyone talks about Self-Service BI and In-Memory databases, and what’s the correct path to follow in order to have a successful project up and running. Beside this Preconference, I’ll also deliver a regular session, this time related to database administration, monitoring and tuning: DMVs: Power in Your Hands http://www.sqlpass.org/summit/2012/Sessions/SessionDetails.aspx?sid=3204 Here we’ll dive into the most useful DMVs, so that you’ll see how that can help in everyday management in order to discover, understand and optimze you SQL Server installation, from the server itself to the single query. See you there!!!!!

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  • Using R on your Oracle Data Warehouse

    - by jean-pierre.dijcks
    Since it is Predictive Analytics World in our backyard (or are we San Francisco’s backyard…?) I figured it is well worth the time to dust of some old but important news. With big data (should we start calling it “any data analytics” instead?) being the buzz word and analytics the key operative goal, not moving data around is becoming more and more critical to the business users. Why? Because instead of spending time on moving data around into your next analytics server you should be running analytics on those CPUs. You could always do this with Oracle Data Mining within the Oracle Database. But a lot of folks want to leverage R as their main tool. Well, this article describes how you can do this, since 2010… As Casimir Saternos concludes in the article; “There is a growing awareness of the need to effectively analyze astronomical amounts of data, much of which is stored in Oracle databases. Statistics and modeling techniques are used to improve a wide variety of business functions. ODM accessed using the R language increases the value of your data by uncovering additional information. RODM is a powerful tool to enable your organization to make predictions, classify data, and create visualizations that maximize effectiveness and efficiencies.” Happy Analysis!

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  • PASS Summit Preconference and Sessions

    - by Davide Mauri
    I’m very pleased to announce that I’ll be delivering a Pre-Conference at PASS Summit 2012. I’ll speak about Business Intelligence again (as I did in 2010) but this time I’ll focus only on Data Warehouse, since it’s big topic even alone. I’ll discuss not only what is a Data Warehouse, how it can be modeled and built, but also how it’s development can be approached using and Agile approach, bringing the experience I gathered in this field. Building the Agile Data Warehouse with SQL Server 2012 http://www.sqlpass.org/summit/2012/Sessions/SessionDetails.aspx?sid=2821 I’m sure you’ll like it, especially if you’re starting to create a BI Solution and you’re wondering what is a Data Warehouse, if it is still useful nowadays that everyone talks about Self-Service BI and In-Memory databases, and what’s the correct path to follow in order to have a successful project up and running. Beside this Preconference, I’ll also deliver a regular session, this time related to database administration, monitoring and tuning: DMVs: Power in Your Hands http://www.sqlpass.org/summit/2012/Sessions/SessionDetails.aspx?sid=3204 Here we’ll dive into the most useful DMVs, so that you’ll see how that can help in everyday management in order to discover, understand and optimze you SQL Server installation, from the server itself to the single query. See you there!!!!!

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  • New Exadata Book Available Soon

    - by Rob Reynolds
    Oracle Press is set to released the first book on data warehouse performance and Exadata on March 14th. Achieving Extreme Performance with Oracle Exadata , by my colleagues Rick Greenwald, Robert Stackowiak, Maqsood Alam, and Mans Bhuller will be available at your favorite booksellers next week. I've seen a sneak peak of the content in this book and its a great way to fully grasp the power of Exadata and how to best apply it to achieve extreme data warehouse performance. From the publisher's description: Achieving Extreme Performance with Oracle Exadata and the Sun Oracle Database Machine is filled with best practices for deployments, hardware sizing, architecting the database machine environments for maximum availability, and backup and recovery. Oracle Database 11gR2 features used within these offerings, as well as migration options and paths for Oracle and non-Oracle databases to Oracle Exadata are covered. This Oracle Press guide also discusses architecture, administration, maintenance, monitoring, and tuning of Oracle Exadata Storage Servers and the Sun Oracle Database Machine. If your company is considering Exadata, or if you need more horsepower out of your data warehouse, I highly recommend grabbing a copy of this book next week.

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  • How to extract data from Google Analytics and build a data warehouse (webhouse) from it?

    - by nkaur301
    I have click stream data such as referring URL, top landing pages, top exit pages and metrics such as page views, number of visits, bounces all in Google Analytics. I am required to build a data warehouse from scratch(which I believe is known as web-house) from this data. My questions are:- 1)Is it possible? Every day data increases (some in terms of metrics or measures such as visits and some in terms of new referring sites), how would the process of loading the warehouse go about? 2)What ETL tool would help me to achieve this? Pentaho I believe has a way to pull out data from Google Analytics, has anyone used it? How does that process go? Any references, links would be appreciated besides answers.

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  • Data Warehouse ETL slow - change primary key in dimension?

    - by Jubbles
    I have a working MySQL data warehouse that is organized as a star schema and I am using Talend Open Studio for Data Integration 5.1 to create the ETL process. I would like this process to run once per day. I have estimated that one of the dimension tables (dimUser) will have approximately 2 million records and 23 columns. I created a small test ETL process in Talend that worked, but given the amount of data that may need to be updated daily, the current performance will not cut it. It takes the ETL process four minutes to UPDATE or INSERT 100 records to dimUser. If I assumed a linear relationship between the count of records and the amount of time to UPDATE or INSERT, then there is no way the ETL can finish in 3-4 hours (my hope), let alone one day. Since I'm unfamiliar with Java, I wrote the ETL as a Python script and ran into the same problem. Although, I did discover that if I did only INSERT, the process went much faster. I am pretty sure that the bottleneck is caused by the UPDATE statements. The primary key in dimUser is an auto-increment integer. My friend suggested that I scrap this primary key and replace it with a multi-field primary key (in my case, 2-3 fields). Before I rip the test data out of my warehouse and change the schema, can anyone provide suggestions or guidelines related to the design of the data warehouse the ETL process how realistic it is to have an ETL process INSERT or UPDATE a few million records each day will my friend's suggestion significantly help If you need any further information, just let me know and I'll post it. UPDATE - additional information: mysql> describe dimUser; Field Type Null Key Default Extra user_key int(10) unsigned NO PRI NULL auto_increment id_A int(10) unsigned NO NULL id_B int(10) unsigned NO NULL field_4 tinyint(4) unsigned NO 0 field_5 varchar(50) YES NULL city varchar(50) YES NULL state varchar(2) YES NULL country varchar(50) YES NULL zip_code varchar(10) NO 99999 field_10 tinyint(1) NO 0 field_11 tinyint(1) NO 0 field_12 tinyint(1) NO 0 field_13 tinyint(1) NO 1 field_14 tinyint(1) NO 0 field_15 tinyint(1) NO 0 field_16 tinyint(1) NO 0 field_17 tinyint(1) NO 1 field_18 tinyint(1) NO 0 field_19 tinyint(1) NO 0 field_20 tinyint(1) NO 0 create_date datetime NO 2012-01-01 00:00:00 last_update datetime NO 2012-01-01 00:00:00 run_id int(10) unsigned NO 999 I used a surrogate key because I had read that it was good practice. Since, from a business perspective, I want to keep aware of potential fraudulent activity (say for 200 days a user is associated with state X and then the next day they are associated with state Y - they could have moved or their account could have been compromised), so that is why geographic data is kept. The field id_B may have a few distinct values of id_A associated with it, but I am interested in knowing distinct (id_A, id_B) tuples. In the context of this information, my friend suggested that something like (id_A, id_B, zip_code) be the primary key. For the large majority of daily ETL processes (80%), I only expect the following fields to be updated for existing records: field_10 - field_14, last_update, and run_id (this field is a foreign key to my etlLog table and is used for ETL auditing purposes).

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  • Oracle Adattárház Referencia Architektúra, a legjobb gyakorlatból

    - by Fekete Zoltán
    Hogyan építsünk adattárházat, hogyan kapcsoljuk össze a rendszereinkkel? Mi legyen az az architektúra, mellyel a legkisebb kockázattal a legbiztosabban érünk célba? Ezekre a kérdésekre kaphatunk választ az Oracle Data Warehouse Reference Architecture leírásból. Letöltheto a következo dokumentum: Enabling Pervasive BI through a Practical Data Warehouse Reference Architecture

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  • How to write these two queries for a simple data warehouse, using ANSI SQL?

    - by morpheous
    I am writing a simple data warehouse that will allow me to query the table to observe periodic (say weekly) changes in data, as well as changes in the change of the data (e.g. week to week change in the weekly sale amount). For the purposes of simplicity, I will present very simplified (almost trivialized) versions of the tables I am using here. The sales data table is a view and has the following structure: CREATE TABLE sales_data ( sales_time date NOT NULL, sales_amt double NOT NULL ) For the purpose of this question. I have left out other fields you would expect to see - like product_id, sales_person_id etc, etc, as they have no direct relevance to this question. AFAICT, the only fields that will be used in the query are the sales_time and the sales_amt fields (unless I am mistaken). I also have a date dimension table with the following structure: CREATE TABLE date_dimension ( id integer NOT NULL, datestamp date NOT NULL, day_part integer NOT NULL, week_part integer NOT NULL, month_part integer NOT NULL, qtr_part integer NOT NULL, year_part integer NOT NULL, ); which partition dates into reporting ranges. I need to write queries that will allow me to do the following: Return the change in week on week sales_amt for a specified period. For example the change between sales today and sales N days ago - where N is a positive integer (N == 7 in this case). Return the change in change of sales_amt for a specified period. For in (1). we calculated the week on week change. Now we want to know how that change is differs from the (week on week) change calculated last week. I am stuck however at this point, as SQL is my weakest skill. I would be grateful if an SQL master can explain how I can write these queries in a DB agnostic way (i.e. using ANSI SQL).

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  • OWB és heterogén adatforrások, Oracle Magazine, 2010. május-június

    - by Fekete Zoltán
    Megjelent az Oracle Magazine aktuális száma (naná, az aktuális számnak ez a dolga. Oracle Magazine, 2010. május-június. Ebben a számban sok érdekes cikk közül válogathatunk: cloud computing, Java, .Net, új generációs backup, párhuzamosság és PL/SQL, OWB,... Ajánlom a Business Intelligence - Oracle Warehouse Builder 11g Release 2 and Heterogeneous Databases cikket, melyben megtudhatjuk, hogyan használhatunk heterogén adatforrásokat az Oracle Warehouse Builder ETL-ELT eszközzel, hogyan tudunk például SQL Serverhez csatlakozni, és nagy teljesítménnyel adatokat kinyerni. Az Oracle adatintegrációs weblapja. Ez a gazdag heterogenitás az OWB az Oracle Data Integrator testvér termékbol jön. Az adatintegrációs SOD azt mondja, hogy ez a két Java alapú termék, az OWB és az ODI egy termékben fognak egyesülni.

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  • Is there a Google 3d Warehouse API?

    - by Jayesh
    Does anyone know if there is an official or unofficial API for Google 3D warehouse. I know of the iPhone app NaviCAD, which shows Collada models from Google Warehouse - it has search, most-viewed, most-recent functionality; so I guess it is using some sort of API to get that data. But I couldn't find any auch api after searching around. Do you know if there is any?

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  • Building a Data Warehouse

    - by Paul
    I've seen tutorials articles and posts on how to build datawarehouses with star and snowflakes schemas, denormalization of OLTP databases fact and dimension tables and so on. Also seen comments like: Star schemas are for datamarts, at best. There is absolutely no way a true enterprise data warehouse could be represented in a star schema, or snowflake either. I want to create a database that will server for reporting services and maybe (if that isn't enough) install analisys services and extract reports and data from cubes. My question was : Is it really necesarry to redesign my current database and follow the star/snowflake schemas with fact and dimension tables ? Thank you

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  • Oracle data warehouse design - fact table acting as a dimension?

    - by Elizabeth
    THANKS: Both answers here are very helpful, but I could only pick one. I really appreciate the advice! our datawarehouse will be used more for workflow reports than traditional analytical reports. Our users care about "current picture" far more than history. (though history matters, too.) We are a government entity that does not have costs or related calculations. Mostly just counts of people within given locations and with related history. We are using Oracle, and I have found distinct advantage in using the star join whenever possible and would like to rearchitect everything to as closely resemble the star schema as is reasonable for our business uses. Speed in this DW is vital, and a number of tests have already proven the star schema approach to me. Our "person" table is key - it contains over 4 million records and will be the most frequently used source in queries. It can be seen at the center of a star with multiple dimensions (like age, gender, affiliation, location, etc.). It is a very LONG table, particularly when I join it to the address and contact information. However, it is more like a dimension table when we start looking at history. For example, there are two different history tables that have a person key pointing to the person table. One has over 20 million records and the other has almost 50 million and grows daily. Is this table a fact table or a dimension table? Can one work as both? If so, is that going to be a big performance problem? Is it common to query more off of a dimension than a fact? What happens if a DIFFERENT fact table that uses the person table as a dimension is actually only 60,000 records (much smaller.). I think my problem is that our data and use of it does not fit with the commonly use examples of star schemas. CLARIFICATION: Some good thoughts have been added below, but perhaps I left too much out to really explain well. Here's some more info: We handle a voter database. We don't have any measures except voter counts by various groups: voter counts by party, by age, by location; voter counts by ballot type and election, by ballot status and election, etc. We do have a "voting history" log as well as an activity audit log (change of address, party, etc.). We have information on which voters are election workers and all that related information. I figure I'll get to the peripheral stuff later. For now I'm focusing on our two major "business processes": voter registration(which IS a voter.) and election turnout. In the first, voter is a fact. In the second, voter is a dimension, along with party, election, and type of ballot. (and in case anyone is worried - no we don't know HOW people vote. Just that they do. LOL ) I hope that clarifies things a bit.

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