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  • OWB 11gR2 – Degenerate Dimensions

    - by David Allan
    Ever wondered how to build degenerate dimensions in OWB and get the benefits of slowly changing dimensions and cube loading? Now its possible through some changes in 11gR2 to make the dimension and cube loading much more flexible. This will let you get the benefits of OWB's surrogate key handling and slowly changing dimension reference when loading the fact table and need degenerate dimensions (see Ralph Kimball's degenerate dimensions design tip). Here we will see how to use the cube operator to load slowly changing, regular and degenerate dimensions. The cube and cube operator can now work with dimensions which have no surrogate key as well as dimensions with surrogates, so you can get the benefit of the cube loading and incorporate the degenerate dimension loading. What you need to do is create a dimension in OWB that is purely used for ETL metadata; the dimension itself is never deployed (its table is, but has not data) it has no surrogate keys has a single level with a business attribute the degenerate dimension data and a dummy attribute, say description just to pass the OWB validation. When this degenerate dimension is added into a cube, you will need to configure the fact table created and set the 'Deployable' flag to FALSE for the foreign key generated to the degenerate dimension table. The degenerate dimension reference will then be in the cube operator and used when matching. Create the degenerate dimension using the regular wizard. Delete the Surrogate ID attribute, this is not needed. Define a level name for the dimension member (any name). After the wizard has completed, in the editor delete the hierarchy STANDARD that was automatically generated, there is only a single level, no need for a hierarchy and this shouldn't really be created. Deploy the implementing table DD_ORDERNUMBER_TAB, this needs to be deployed but with no data (the mapping here will do a left outer join of the source data with the empty degenerate dimension table). Now, go ahead and build your cube, use the regular TIMES dimension for example and your degenerate dimension DD_ORDERNUMBER, can add in SCD dimensions etc. Configure the fact table created and set Deployable to false, so the foreign key does not get generated. Can now use the cube in a mapping and load data into the fact table via the cube operator, this will look after surrogate lookups and slowly changing dimension references.   If you generate the SQL you will see the ON clause for matching includes the columns representing the degenerate dimension columns. Here we have seen how this use case for loading fact tables using degenerate dimensions becomes a whole lot simpler using OWB 11gR2. I'm sure there are other use cases where using this mix of dimensions with surrogate and regular identifiers is useful, Fact tables partitioned by date columns is another classic example that this will greatly help and make the cube operator much more useful. Good to hear any comments.

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  • Text Expansion Awareness for UX Designers: Points to Consider

    - by ultan o'broin
    Awareness of translated text expansion dynamics is important for enterprise applications UX designers (I am assuming all source text for translation is in English, though apps development can takes place in other natural languages too). This consideration goes beyond the standard 'character multiplication' rule and must take into account the avoidance of other layout tricks that a designer might be tempted to try. Follow these guidelines. For general text expansion, remember the simple rule that the shorter the word is in the English, the longer it will need to be in English. See the examples provided by Richard Ishida of the W3C and you'll get the idea. So, forget the 30 percent or one inch minimum expansion rule of the old Forms days. Unfortunately remembering convoluted text expansion rules, based as a percentage of the US English character count can be tough going. Try these: Up to 10 characters: 100 to 200% 11 to 20 characters: 80 to 100% 21 to 30 characters: 60 to 80% 31 to 50 characters: 40 to 60% 51 to 70 characters: 31 to 40% Over 70 characters: 30% (Source: IBM) So it might be easier to remember a rule that if your English text is less than 20 characters then allow it to double in length (200 percent), and then after that assume an increase by half the length of the text (50%). (Bear in mind that ADF can apply truncation rules on some components in English too). (If your text is stored in a database, developers must make sure the table column widths can accommodate the expansion of your text when translated based on byte size for the translated character and not numbers of characters. Use Unicode. One character does not equal one byte in the multilingual enterprise apps world.) Rely on a graceful transformation of translated text. Let all pages to resize dynamically so the text wraps and flow naturally. ADF pages supports this already. Think websites. Don't hard-code alignments. Use Start and End properties on components and not Left or Right. Don't force alignments of components on the page by using texts of a certain length as spacers. Use proper label positioning and anchoring in ADF components or other technologies. Remember that an increase in text length means an increase in vertical space too when pages are resized. So don't hard-code vertical heights for any text areas. Don't be tempted to manually create text or printed reports this way either. They cannot be translated successfully, and are very difficult to maintain in English. Use XML, HTML, RTF and so on. Check out what Oracle BI Publisher offers. Don't force wrapping by using tricks such as /n or /t characters or HTML BR tags or forced page breaks. Once the text is translated the alignment will be destroyed. The position of the breaking character or tag would need to be moved anyway, or even removed. When creating tables, then use table components. Don't use manually created tables that reply on word length to maintain column and row alignment. For example, don't use codeblock elements in HTML; use the proper table elements instead. Once translated, the alignment of manually formatted tabular data is destroyed. Finally, if there is a space restriction, then don't use made-up acronyms, abbreviations or some form of daft text speak to save space. Besides being incomprehensible in English, they may need full translations of the shortened words, even if they can be figured out. Use approved or industry standard acronyms according to the UX style rules, not as a space-saving device. Restricted Real Estate on Mobile Devices On mobile devices real estate is limited. Using shortened text is fine once it is comprehensible. Users in the mobile space prefer brevity too, as they are on the go, performing three-minute tasks, with no time to read lengthy texts. Using fragments and lightning up on unnecessary articles and getting straight to the point with imperative forms of verbs makes sense both on real estate and user experience grounds.

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  • OWB 11gR2 - Early Arriving Facts

    - by Dawei Sun
    A common challenge when building ETL components for a data warehouse is how to handle early arriving facts. OWB 11gR2 introduced a new feature to address this for dimensional objects entitled Orphan Management. An orphan record is one that does not have a corresponding existing parent record. Orphan management automates the process of handling source rows that do not meet the requirements necessary to form a valid dimension or cube record. In this article, a simple example will be provided to show you how to use Orphan Management in OWB. We first import a sample MDL file that contains all the objects we need. Then we take some time to examine all the objects. After that, we prepare the source data, deploy the target table and dimension/cube loading map. Finally, we run the loading maps, and check the data in target dimension/cube tables. OK, let’s start… 1. Import MDL file and examine sample project First, download zip file from here, which includes a MDL file and three source data files. Then we open OWB design center, import orphan_management.mdl by using the menu File->Import->Warehouse Builder Metadata. Now we have several objects in BI_DEMO project as below: Mapping LOAD_CHANNELS_OM: The mapping for dimension loading. Mapping LOAD_SALES_OM: The mapping for cube loading. Dimension CHANNELS_OM: The dimension that contains channels data. Cube SALES_OM: The cube that contains sales data. Table CHANNELS_OM: The star implementation table of dimension CHANNELS_OM. Table SALES_OM: The star implementation table of cube SALES_OM. Table SRC_CHANNELS: The source table of channels data, that will be loaded into dimension CHANNELS_OM. Table SRC_ORDERS and SRC_ORDER_ITEMS: The source tables of sales data that will be loaded into cube SALES_OM. Sequence CLASS_OM_DIM_SEQ: The sequence used for loading dimension CHANNELS_OM. Dimension CHANNELS_OM This dimension has a hierarchy with three levels: TOTAL, CLASS and CHANNEL. Each level has three attributes: ID (surrogate key), NAME and SOURCE_ID (business key). It has a standard star implementation. The orphan management policy and the default parent setting are shown in the following screenshots: The orphan management policy options that you can set for loading are: Reject Orphan: The record is not inserted. Default Parent: You can specify a default parent record. This default record is used as the parent record for any record that does not have an existing parent record. If the default parent record does not exist, Warehouse Builder creates the default parent record. You specify the attribute values of the default parent record at the time of defining the dimensional object. If any ancestor of the default parent does not exist, Warehouse Builder also creates this record. No Maintenance: This is the default behavior. Warehouse Builder does not actively detect, reject, or fix orphan records. While removing data from a dimension, you can select one of the following orphan management policies: Reject Removal: Warehouse Builder does not allow you to delete the record if it has existing child records. No Maintenance: This is the default behavior. Warehouse Builder does not actively detect, reject, or fix orphan records. (More details are at http://download.oracle.com/docs/cd/E11882_01/owb.112/e10935/dim_objects.htm#insertedID1) Cube SALES_OM This cube is references to dimension CHANNELS_OM. It has three measures: AMOUNT, QUANTITY and COST. The orphan management policy setting are shown as following screenshot: The orphan management policy options that you can set for loading are: No Maintenance: Warehouse Builder does not actively detect, reject, or fix orphan rows. Default Dimension Record: Warehouse Builder assigns a default dimension record for any row that has an invalid or null dimension key value. Use the Settings button to define the default parent row. Reject Orphan: Warehouse Builder does not insert the row if it does not have an existing dimension record. (More details are at http://download.oracle.com/docs/cd/E11882_01/owb.112/e10935/dim_objects.htm#BABEACDG) Mapping LOAD_CHANNELS_OM This mapping loads source data from table SRC_CHANNELS to dimension CHANNELS_OM. The operator CHANNELS_IN is bound to table SRC_CHANNELS; CHANNELS_OUT is bound to dimension CHANNELS_OM. The TOTALS operator is used for generating a constant value for the top level in the dimension. The CLASS_FILTER operator is used to filter out the “invalid” class name, so then we can see what will happen when those channel records with an “invalid” parent are loading into dimension. Some properties of the dimension operator in this mapping are important to orphan management. See the screenshot below: Create Default Level Records: If YES, then default level records will be created. This property must be set to YES for dimensions and cubes if one of their orphan management policies is “Default Parent” or “Default Dimension Record”. This property is set to NO by default, so the user may need to set this to YES manually. LOAD policy for INVALID keys/ LOAD policy for NULL keys: These two properties have the same meaning as in the dimension editor. The values are set to the same as the dimension value when user drops the dimension into the mapping. The user does not need to modify these properties. Record Error Rows: If YES, error rows will be inserted into error table when loading the dimension. REMOVE Orphan Policy: This property is used when removing data from a dimension. Since the dimension loading type is set to LOAD in this example, this property is disabled. Mapping LOAD_SALES_OM This mapping loads source data from table SRC_ORDERS and SRC_ORDER_ITEMS to cube SALES_OM. This mapping seems a little bit complicated, but operators in the red rectangle are used to filter out and generate the records with “invalid” or “null” dimension keys. Some properties of the cube operator in a mapping are important to orphan management. See the screenshot below: Enable Source Aggregation: Should be checked in this example. If the default dimension record orphan policy is set for the cube operator, then it is recommended that source aggregation also be enabled. Otherwise, the orphan management processing may produce multiple fact rows with the same default dimension references, which will cause an “unstable rowset” execution error in the database, since the dimension refs are used as update match attributes for updating the fact table. LOAD policy for INVALID keys/ LOAD policy for NULL keys: These two properties have the same meaning as in the cube editor. The values are set to the same as in the cube editor when the user drops the cube into the mapping. The user does not need to modify these properties. Record Error Rows: If YES, error rows will be inserted into error table when loading the cube. 2. Deploy objects and mappings We now can deploy the objects. First, make sure location SALES_WH_LOCAL has been correctly configured. Then open Control Center Manager by using the menu Tools->Control Center Manager. Expand BI_DEMO->SALES_WH_LOCAL, click SALES_WH node on the project tree. We can see the following objects: Deploy all the objects in the following order: Sequence CLASS_OM_DIM_SEQ Table CHANNELS_OM, SALES_OM, SRC_CHANNELS, SRC_ORDERS, SRC_ORDER_ITEMS Dimension CHANNELS_OM Cube SALES_OM Mapping LOAD_CHANNELS_OM, LOAD_SALES_OM Note that we deployed source tables as well. Normally, we import source table from database instead of deploying them to target schema. However, in this example, we designed the source tables in OWB and deployed them to database for the purpose of this demonstration. 3. Prepare and examine source data Before running the mappings, we need to populate and examine the source data first. Run SRC_CHANNELS.sql, SRC_ORDERS.sql and SRC_ORDER_ITEMS.sql as target user. Then we check the data in these three tables. Table SRC_CHANNELS SQL> select rownum, id, class, name from src_channels; Records 1~5 are correct; they should be loaded into dimension without error. Records 6,7 and 8 have null parents; they should be loaded into dimension with a default parent value, and should be inserted into error table at the same time. Records 9, 10 and 11 have “invalid” parents; they should be rejected by dimension, and inserted into error table. Table SRC_ORDERS and SRC_ORDER_ITEMS SQL> select rownum, a.id, a.channel, b.amount, b.quantity, b.cost from src_orders a, src_order_items b where a.id = b.order_id; Record 178 has null dimension reference; it should be loaded into cube with a default dimension reference, and should be inserted into error table at the same time. Record 179 has “invalid” dimension reference; it should be rejected by cube, and inserted into error table. Other records should be aggregated and loaded into cube correctly. 4. Run the mappings and examine the target data In the Control Center Manager, expand BI_DEMO-> SALES_WH_LOCAL-> SALES_WH-> Mappings, right click on LOAD_CHANNELS_OM node, click Start. Use the same way to run mapping LOAD_SALES_OM. When they successfully finished, we can check the data in target tables. Table CHANNELS_OM SQL> select rownum, total_id, total_name, total_source_id, class_id,class_name, class_source_id, channel_id, channel_name,channel_source_id from channels_om order by abs(dimension_key); Records 1,2 and 3 are the default dimension records for the three levels. Records 8, 10 and 15 are the loaded records that originally have null parents. We see their parents name (class_name) is set to DEF_CLASS_NAME. Those records whose CHANNEL_NAME are Special_4, Special_5 and Special_6 are not loaded to this table because of the invalid parent. Error Table CHANNELS_OM_ERR SQL> select rownum, class_source_id, channel_id, channel_name,channel_source_id, err$$$_error_reason from channels_om_err order by channel_name; We can see all the record with null parent or invalid parent are inserted into this error table. Error reason is “Default parent used for record” for the first three records, and “No parent found for record” for the last three. Table SALES_OM SQL> select a.*, b.channel_name from sales_om a, channels_om b where a.channels=b.channel_id; We can see the order record with null channel_name has been loaded into target table with a default channel_name. The one with “invalid” channel_name are not loaded. Error Table SALES_OM_ERR SQL> select a.amount, a.cost, a.quantity, a.channels, b.channel_name, a.err$$$_error_reason from sales_om_err a, channels_om b where a.channels=b.channel_id(+); We can see the order records with null or invalid channel_name are inserted into error table. If the dimension reference column is null, the error reason is “Default dimension record used for fact”. If it is invalid, the error reason is “Dimension record not found for fact”. Summary In summary, this article illustrated the Orphan Management feature in OWB 11gR2. Automated orphan management policies improve ETL developer and administrator productivity by addressing an important cause of cube and dimension load failures, without requiring developers to explicitly build logic to handle these orphan rows.

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  • Text expansion software for Windows

    - by MagicAndi
    I am interested in using a text expansion application, such as Texter or Phase Express. Does anyone have any recommendations for the best text expansion application to use? I work on a number of Windows PCs (XP, Vista, Windows Server 2003 and Windows Server 2008); the application would need to work on all of these OS flavours. I am particularly interested in an application that is available for all of my programs, and that isn't program specific.

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  • select all values from a dimension for which there are facts in all other dimensions

    - by ideasculptor
    I've tried to simplify for the purposes of asking this question. Hopefully, this will be comprehensible. Basically, I have a fact table with a time dimension, another dimension, and a hierarchical dimension. For the purposes of the question, let's assume the hierarchical dimension is zip code and state. The other dimension is just descriptive. Let's call it 'customer' Let's assume there are 50 customers. I need to find the set of states for which there is at least one zip code in which EVERY customer has at least one fact row for each day in the time dimension. If a zip code has only 49 customers, I don't care about it. If even one of the 50 customers doesn't have a value for even 1 day in a zip code, I don't care about it. Finally, I also need to know which zip codes qualified the state for selection. Note, there is no requirement that every zip code have a full data set - only that at least one zip code does. I don't mind making multiple queries and doing some processing on the client side. This is a dataset that only needs to be generated once per day and can be cached. I don't even see a particularly clean way to do it with multiple queries short of simply brute-force iteration, and there are a heck of a lot of 'zip codes' in the data set (not actually zip codes, but the there are approximately 100,000 entries in the lower level of the hierarchy and several hundred in the top level, so zipcode-state is a reasonable analogy)

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  • Error : Member 'D-T-D' in the Period dimension has no value for the Period Type property

    - by RahulS
    Workaround for LCM EPMA deploy errors: Error : Member 'D-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'D-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'W-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'W-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'M-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'M-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'Q-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'Q-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'P-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'P-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'S-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'S-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'Y-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'Y-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'.  Error : Member 'H-T-D' in the Period dimension has no value for the Period  Type property.  Error : Member name 'H-T-D' in the Period dimension is only valid when Period  Type is set to 'DTS Time Period'. Fix 1. Edit the Period dimension LCM artifact (Keep the back up of the file before editing.)  2. Delete the DTS members (for example as mentioned below) in the Period dimension hierarchy section.   #root|D-T-D|True||||||||||||||||   #root|W-T-D|True||||||||||||||||   #root|M-T-D|True||||||||||||||||   #root|Q-T-D|True||||||||||||||||   #root|P-T-D|True||||||||||||||||   #root|S-T-D|True||||||||||||||||   #root|Y-T-D|True||||||||||||||||   #root|H-T-D|True||||||||||||||||   3. Delete the DTS members (for example as mentioned below) in the Period member hierarchy section,   D-T-D|True||||||||||||||||   W-T-D|True||||||||||||||||   M-T-D|True||||||||||||||||   Q-T-D|True||||||||||||||||   P-T-D|True||||||||||||||||   S-T-D|True||||||||||||||||   Y-T-D|True||||||||||||||||   H-T-D|True||||||||||||||||   4. Then save the edited Period dimension LCM artifact.   5. Then try to import the Period dimension using LCM.   6. Then Validate/Deploy the Planning application still the same issue. PS: This issue is fixed in 11.1.2.2.

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  • RAID 5 configuration and future expansion

    - by Alexis Hirst
    hi, I am building a PC to act as a file server among other things, and I was wondering whether it is a good idea to create 2 partitions on the RAID 5 array, one for OS one for data, or to have a separate disk for OS and use array for data. Also, one day i may want to add another disk to the array, so would there be any issues if I had the OS partition on the RAID5 array when it came to resizing the data partition?

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  • SSAS: Using fake dimension and scopes for dynamic ranges

    - by DigiMortal
    In one of my BI projects I needed to find count of objects in income range. Usual solution with range dimension was useless because range where object belongs changes in time. These ranges depend on calculation that is done over incomes measure so I had really no option to use some classic solution. Thanks to SSAS forums I got my problem solved and here is the solution. The problem – how to create dynamic ranges? I have two dimensions in SSAS cube: one for invoices related to objects rent and the other for objects. There is measure that sums invoice totals and two calculations. One of these calculations performs some computations based on object income and some other object attributes. Second calculation uses first one to define income ranges where object belongs. What I need is query that returns me how much objects there are in each group. I cannot use dimension for range because on one date object may belong to one range and two days later to another income range. By example, if object is not rented out for two days it makes no money and it’s income stays the same as before. If object is rented out after two days it makes some income and this income may move it to another income range. Solution – fake dimension and scopes Thanks to Gerhard Brueckl from pmOne I got everything work fine after some struggling with BI Studio. The original discussion he pointed out can be found from SSAS official forums thread Create a banding dimension that groups by a calculated measure. Solution was pretty simple by nature – we have to define fake dimension for our range and use scopes to assign values for object count measure. Object count measure is primitive – it just counts objects and that’s it. We will use it to find out how many objects belong to one or another range. We also need table for fake ranges and we have to fill it with ranges used in ranges calculation. After creating the table and filling it with ranges we can add fake range dimension to our cube. Let’s see now how to solve the problem step-by-step. Solving the problem Suppose you have ranges calculation defined like this: CASE WHEN [Measures].[ComplexCalc] < 0 THEN 'Below 0'WHEN [Measures].[ComplexCalc] >=0 AND  [Measures].[ComplexCalc] <=50 THEN '0 - 50'...END Let’s create now new table to our analysis database and name it as FakeIncomeRange. Here is the definition for table: CREATE TABLE [FakeIncomeRange] (     [range_id] [int] IDENTITY(1,1) NOT NULL,     [range_name] [nvarchar](50) NOT NULL,     CONSTRAINT [pk_fake_income_range] PRIMARY KEY CLUSTERED      (         [range_id] ASC     ) ) Don’t forget to fill this table with range labels you are using in ranges calculation. To use ranges from table we have to add this table to our data source view and create new dimension. We cannot bind this table to other tables but we have to leave it like it is. Our dimension has two attributes: ID and Name. The next thing to create is calculation that returns objects count. This calculation is also fake because we override it’s values for all ranges later. Objects count measure can be defined as calculation like this: COUNT([Object].[Object].[Object].members) Now comes the most crucial part of our solution – defining the scopes. Based on data used in this posting we have to define scope for each of our ranges. Here is the example for first range. SCOPE([FakeIncomeRange].[Name].&[Below 0], [Measures].[ObjectCount])     This=COUNT(            FILTER(                [Object].[Object].[Object].members,                 [Measures].[ComplexCalc] < 0          )     ) END SCOPE To get these scopes defined in cube we need MDX script blocks for each line given here. Take a look at the screenshot to get better idea what I mean. This example is given from SQL Server books online to avoid conflicts with NDA. :) From previous example the lines (MDX scripts) are: Line starting with SCOPE Block for This = Line with END SCOPE And now it is time to deploy and process our cube. Although you may see examples where there are semicolons in the end of statements you don’t need them. Visual Studio BI tools generate separate command from each script block so you don’t need to worry about it.

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  • Loading Hybrid Dimension Table with SCD1 and SCD2 attributes + SSIS

    - by Nev_Rahd
    Hello I am just in a process of starting a new task, wherein in i need to load Hybrid Dimension Table with SCD1 and SCD2. This need to be achieved as a SSIS Package. Can someone guide what would be the best way dealing this in SSIS, should i used SCD component or there is other way? What are the best practices for this. For SCD2 type, am using Merge statement. Thanks

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  • How to prevent filename expansion in for loop in bash

    - by cagri
    In a for loop like this, for i in `cat *.input`; do echo "$i" done if one of the input file contains entries like *a, it will, and give the filenames ending in 'a'. Is there a simple way of preventing this filename expansion? Because of use of multiple files, globbing (set -o noglob) is not a good option. I should also be able to filter the output of cat to escape special characters, but for i in `cat *.input | sed 's/*/\\*'` ... still causes *a to expand, while for i in `cat *.input | sed 's/*/\\\\*'` ... gives me \*a (including backslash). [ I guess this is a different question though ]

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  • TELERIK UNVEILS STRATEGIC EXPANSION PLANS, LAUNCHES NEW PRODUCT DIVISIONS

    Corporate and product portfolio expansion solidifies current .NET market leadership, highlights growing momentum in end-to-end productivity solutions space Waltham, MA, April 13, 2010 Telerik, a leading provider of development tools and solutions for the Microsoft? .NET platform, today announced the expansion of its product portfolio to include team productivity solutions and automated testing tools. The company is focusing efforts around four distinct product divisions addressing major cross-sections...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Unity3d: Box collider attached to animated FBX models through scripts at run-time have wrong dimension

    - by Heisenbug
    I have several scripts attached to static and non static models of my scene. All models are instantiated at run-time (and must be instantiated at run-time because I'm procedural building the scene). I'd like to add a BoxCollider or SphereCollider to my FBX models at runtime. With non animated models it works simply requiring BoxCollider component from the script attached to my GameObject. BoxCollider is created of the right dimension. Something like: [RequireComponent(typeof(BoxCollider))] public class AScript: MonoBehavior { } If I do the same thing with animated models, BoxCollider are created of the wrong dimension. For example if attach the script above to penelopeFBX model of the standard asset, BoxCollider is created smaller than the mesh itself. How can I solve this?

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  • multi-dimension array problem in RGSS (RPG Maker XP)

    - by AzDesign
    This is my first day code script in RMXP. I read tutorials, ruby references, etc and I found myself stuck on a weird problem, here is the scenario: I made a custom script to display layered images Create the class, create an instance variable to hold the array, create a simple method to add an element into it, done The draw method (skipped the rest of the code to this part): def draw image = [] index = 0 for i in [email protected] if image.size > 0 index = image.size end image[index] = Sprite.new image[index].bitmap = RPG::Cache.picture(@components[i][0] + '.png') image[index].x = @x + @components[i][1] image[index].y = @y + @components[i][2] image[index].z = @z + @components[i][3] @test =+ 1 end end Create an event that does these script > $layerz = Layerz.new $layerz.configuration[0] = ['root',0,0,1] > $layerz.configuration[1] = ['bark',0,10,2] > $layerz.configuration[2] = ['branch',0,30,3] > $layerz.configuration[3] = ['leaves',0,60,4] $layerz.draw Run, trigger the event and the result : ERROR! Undefined method`[]' for nil:NilClass pointing at this line on draw method : image[index].bitmap = RPG::Cache.picture(@components[i][0] + '.png') THEN, I changed the method like these just for testing: def draw image = [] index = 0 for i in [email protected] if image.size > 0 index = image.size end image[index] = Sprite.new image[index].bitmap = RPG::Cache.picture(@components[0][0] + '.png') image[index].x = @x + @components[0][1] image[index].y = @y + @components[0][2] image[index].z = @z + @components[0][3] @test =+ 1 end I changed the @components[i][0] to @components[0][0] and IT WORKS, but only the root as it not iterates to the next array index Im stuck here, see : > in single level array, @components[0] and @components[i] has no problem > in multi-dimension array, @components[0][0] has no problem BUT > in multi-dimension array, @components[i][0] produce the error as above > mentioned. any suggestion to fix the error ? Or did I wrote something wrong ?

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  • Desigual Extiende Uso de Oracle ® ATG Web Commerce para potenciar su expansión internacional en línea

    - by Noelia Gomez
    Normal 0 21 false false false ES X-NONE X-NONE MicrosoftInternetExplorer4 Desigual, la empresa de moda internacional, ha extendido el uso de Oracle® ATG Web Commerce para dar soporte a su expansión creciente de sus capacidades comerciales de manera internacional y para ayudar a ofrecer un servicio de compra más personalizado a más clientes de manera global. Desigual eligió primero Oracle ATG Web Commerce en 2006 para lanzar su plataforma B2B y automatizar sus ventas a su negocio completo de ventas, Entonces, en Octubre de 2010, Desigual lanzó su plataforma B2C usando Oracle ATG Web Commerce, y ahora ofrece operaciones online en nueve países y 11 lenguas diferentes. Para dar soporte a esta creciente expansión de sus operaciones comerciales y de merchandising en otras geografías, Desigual decidió completar su arquitectura existente con Oracle ATG Web Commerce Merchandising y Oracle ATG Web Commerce Service Center. Además, Desigual implementará Oracle Endeca Guided Search para permitir a los clientes adaptarse de manera más eficiente con su entorno comercial y encontrar rápidamente los productos más relevantes y deseados. Desigual usará las aplicaciones de Oracle para permitir a los usuarios del negocio ganar el control sobre cómo ofrece la compañía una experiencia al cliente más personalizada y conectada a través de los diferentes canales, promoviendo ofertas personalizadas a cada cliente, priorizando los resultados de búsqueda e integrando las operaciones de la web con el contact center sin problemas para aumentar la satisfacción y mejorar los resultados de las conversaciones. Desde que se lanzara en 2002, el minorista español ha crecido rápidamente y ahora ofrece su original moda en sus 200 tiendas propias , 7000 minoristas autorizados y 1700 tiendas de concesión en 55 países. Infórmese con mayor profundidad de nuestras soluciones Oracle Customer Experience aquí. /* 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-ascii- mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi- mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

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  • Managing Slowly Changing Dimension with MERGE Statement in SQL Server

    Slowly Changing Dimension (SCD) Transformation is a quick and easy way to manage smaller slowly changing dimensions but it has several limitations and does not perform well when the number of rows or columns gets larger. Arshad Ali explores some of the alternatives you can use for managing larger slowly changing dimensions. How to automate your .NET and SQL Server deploymentsDeploy .NET code and SQL Server databases in a single repeatable process with Red Gate Deployment Manager. Start deploying with a 28-day trial.

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  • Excel 2010 & SSAS – Search Dimension Members

    - by Davide Mauri
    Today I’ve connected my Excel 2010 to an Analysis Services 2008 Cube and I got a very nice (and unexpected) surprise! It’s now finally possibly to search and filter Dimension Members directly from the combo box window: As you can easily imagine, for medium/big dimensions is really – really – really useful! Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • Can a table be both Fact and Dimension

    - by PatFromCanada
    Ok, I am a newbie and don't really think "dimensionally" yet, I have most of my initial schema roughed out but I keep flipping back and forth on one table. I have a Contract table and it has a quantity column (tonnes), and a net price column, which need to be summed up a bunch of different ways, and the contract has lots of foreign keys (producer, commodity, futures month etc.) and dates so it appears to be a fact table. Also the contract is never updated, if that makes a difference. However, we create cash tickets which we use to pay out part or all of the contract and they have a contract ID on them so then the contract looks like a dimension in the cash ticket's star schema. Is this a problem? Any ideas on the process to resolve this, because people don't seem to like the idea of joining two fact tables. Should I put producerId and commodityId on the cash ticket? It would seem really weird not to have a contractID on it.

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  • Converting 3 dimension byte array to a single byte array [on hold]

    - by Andrew Simpson
    I have a 3 dimensional byte array. The 3-d array represents a jpeg image. Each channel/array represents part of the RGB spectrum. I am not interested in retaining black pixels. A black pixel is represented by this atypical arrangement: myarray[0,0,0] =0; myarray[0,0,1] =0; myarray[0,0,2] =0; So, I have flattened this 3d array out to a 1d array by doing this byte[] AFlatArray = new byte[width x height x 3] and then assigning values respective to the coordinate. But like I said I do not want black pixels. So this array has to only contain color pixels with the x,y coordinate. The result I want is to re-represent the image from the i dimension byte array that only contains non-black pixels. How do I do that? It looks like I have to store black pixels as well because of the xy coordinate system. I have tried writing to a binary file but the size of that file is greater than the jpeg file as the jpeg file is compressed. I am using c#.

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  • C Minishell Command Expansion Printing Gibberish

    - by Optimus_Pwn
    I'm writing a unix minishell in C, and am at the point where I'm adding command expansion. What I mean by this is that I can nest commands in other commands, for example: $> echo hello $(echo world! ... $(echo and stuff)) hello world! ... and stuff I think I have it working mostly, however it isn't marking the end of the expanded string correctly, for example if I do: $> echo a $(echo b $(echo c)) a b c $> echo d $(echo e) d e c See it prints the c, even though I didn't ask it to. Here is my code: msh.c - http://pastebin.com/sd6DZYwB expand.c - http://pastebin.com/uLqvFGPw I have a more code, but there's a lot of it, and these are the parts that I'm having trouble with at the moment. I'll try to tell you the basic way I'm doing this. Main is in msh.c, here it gets a line of input from either the commandline or a shellfile, and then calls processline (char *line, int outFD, int waitFlag), where line is the line we just got, outFD is the file descriptor of the output file, and waitFlag tells us whether or not we should wait if we fork. When we call this from main we do it like this: processline (buffer, 1, 1); In processline, we allocate a new line: char expanded_line[EXPANDEDLEN]; We then call expand, in expand.c: expand(line, expanded_line, EXPANDEDLEN); In expand, we copy the characters literally from line to expanded_line until we find a $(, which then calls: static int expCmdOutput(char *orig, char *new, int *oldl_ind, int *newl_ind) orig is line, and new is expanded line. oldl_ind and newl_ind are the current positions in the line and expanded line, respectively. Then we pipe, and recursively call processline, passing it the nested command(for example, if we had "echo a $(echo b)", we would pass processline "echo b"). This is where I get confused, each time expand is called, is it allocating a new chunk of memory EXPANDEDLEN long? If so, this is bad because I'll run out of stack room really quickly(in the case of a hugely nested commandline input). In expand I insert a null character at the end of the expanded string, so why is it printing past it? If you guys need any more code, or explanations, just ask. Secondly, I put the code in pastebin because there's a ton of it, and in my experience people don't like it when I fill up several pages with code. Thanks.

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  • 12c - SQL Text Expansion

    - by noreply(at)blogger.com (Thomas Kyte)
    Here is another small but very useful new feature in Oracle Database 12c - SQL Text Expansion.  It will come in handy in two cases:You are asked to tune what looks like a simple query - maybe a two table join with simple predicates.  But it turns out the two tables are each views of views of views and so on... In other words, you've been asked to 'tune' a 15 page query, not a two liner.You are asked to take a look at a query against tables with VPD (virtual private database) policies.  In order words, you have no idea what you are trying to 'tune'.A new function, EXPAND_SQL_TEXT, in the DBMS_UTILITY package makes seeing what the "real" SQL is quite easy. For example - take the common view ALL_USERS - we can now:ops$tkyte%ORA12CR1> variable x clobops$tkyte%ORA12CR1> begin  2          dbms_utility.expand_sql_text  3          ( input_sql_text => 'select * from all_users',  4            output_sql_text => :x );  5  end;  6  /PL/SQL procedure successfully completed.ops$tkyte%ORA12CR1> print xX--------------------------------------------------------------------------------SELECT "A1"."USERNAME" "USERNAME","A1"."USER_ID" "USER_ID","A1"."CREATED" "CREATED","A1"."COMMON" "COMMON" FROM  (SELECT "A4"."NAME" "USERNAME","A4"."USER#" "USER_ID","A4"."CTIME" "CREATED",DECODE(BITAND("A4"."SPARE1",128),128,'YES','NO') "COMMON" FROM "SYS"."USER$" "A4","SYS"."TS$" "A3","SYS"."TS$" "A2" WHERE "A4"."DATATS#"="A3"."TS#" AND "A4"."TEMPTS#"="A2"."TS#" AND "A4"."TYPE#"=1) "A1"Now it is easy to see what query is really being executed at runtime - regardless of how many views of views you might have.  You can see the expanded text - and that will probably lead you to the conclusion that maybe that 27 table join to 25 tables you don't even care about might better be written as a two table join.Further, if you've ever tried to figure out what a VPD policy might be doing to your SQL, you know it was hard to do at best.  Christian Antognini wrote up a way to sort of see it - but you never get to see the entire SQL statement: http://www.antognini.ch/2010/02/tracing-vpd-predicates/.  But now with this function - it becomes rather trivial to see the expanded SQL - after the VPD has been applied.  We can see this by setting up a small table with a VPD policy ops$tkyte%ORA12CR1> create table my_table  2  (  data        varchar2(30),  3     OWNER       varchar2(30) default USER  4  )  5  /Table created.ops$tkyte%ORA12CR1> create or replace  2  function my_security_function( p_schema in varchar2,  3                                 p_object in varchar2 )  4  return varchar2  5  as  6  begin  7     return 'owner = USER';  8  end;  9  /Function created.ops$tkyte%ORA12CR1> begin  2     dbms_rls.add_policy  3     ( object_schema   => user,  4       object_name     => 'MY_TABLE',  5       policy_name     => 'MY_POLICY',  6       function_schema => user,  7       policy_function => 'My_Security_Function',  8       statement_types => 'select, insert, update, delete' ,  9       update_check    => TRUE ); 10  end; 11  /PL/SQL procedure successfully completed.And then expanding a query against it:ops$tkyte%ORA12CR1> begin  2          dbms_utility.expand_sql_text  3          ( input_sql_text => 'select * from my_table',  4            output_sql_text => :x );  5  end;  6  /PL/SQL procedure successfully completed.ops$tkyte%ORA12CR1> print xX--------------------------------------------------------------------------------SELECT "A1"."DATA" "DATA","A1"."OWNER" "OWNER" FROM  (SELECT "A2"."DATA" "DATA","A2"."OWNER" "OWNER" FROM "OPS$TKYTE"."MY_TABLE" "A2" WHERE "A2"."OWNER"=USER@!) "A1"Not an earth shattering new feature - but extremely useful in certain cases.  I know I'll be using it when someone asks me to look at a query that looks simple but has a twenty page plan associated with it!

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  • Database warehouse design: fact tables and dimension tables

    - by morpheous
    I am building a poor man's data warehouse using a RDBMS. I have identified the key 'attributes' to be recorded as: sex (true/false) demographic classification (A, B, C etc) place of birth date of birth weight (recorded daily): The fact that is being recorded My requirements are to be able to run 'OLAP' queries that allow me to: 'slice and dice' 'drill up/down' the data and generally, be able to view the data from different perspectives After reading up on this topic area, the general consensus seems to be that this is best implemented using dimension tables rather than normalized tables. Assuming that this assertion is true (i.e. the solution is best implemented using fact and dimension tables), I would like to seek some help in the design of these tables. 'Natural' (or obvious) dimensions are: Date dimension Geographical location Which have hierarchical attributes. However, I am struggling with how to model the following fields: sex (true/false) demographic classification (A, B, C etc) The reason I am struggling with these fields is that: They have no obvious hierarchical attributes which will aid aggregation (AFAIA) - which suggest they should be in a fact table They are mostly static or very rarely change - which suggests they should be in a dimension table. Maybe the heuristic I am using above is too crude? I will give some examples on the type of analysis I would like to carryout on the data warehouse - hopefully that will clarify things further. I would like to aggregate and analyze the data by sex and demographic classification - e.g. answer questions like: How does male and female weights compare across different demographic classifications? Which demographic classification (male AND female), show the most increase in weight this quarter. etc. Can anyone clarify whether sex and demographic classification are part of the fact table, or whether they are (as I suspect) dimension tables.? Also assuming they are dimension tables, could someone elaborate on the table structures (i.e. the fields)? The 'obvious' schema: CREATE TABLE sex_type (is_male int); CREATE TABLE demographic_category (id int, name varchar(4)); may not be the correct one.

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  • Database warehoue design: fact tables and dimension tables

    - by morpheous
    I am building a poor man's data warehouse using a RDBMS. I have identified the key 'attributes' to be recorded as: sex (true/false) demographic classification (A, B, C etc) place of birth date of birth weight (recorded daily): The fact that is being recorded My requirements are to be able to run 'OLAP' queries that allow me to: 'slice and dice' 'drill up/down' the data and generally, be able to view the data from different perspectives After reading up on this topic area, the general consensus seems to be that this is best implemented using dimension tables rather than normalized tables. Assuming that this assertion is true (i.e. the solution is best implemented using fact and dimension tables), I would like to see some help in the design of these tables. 'Natural' (or obvious) dimensions are: Date dimension Geographical location Which have hierarchical attributes. However, I am struggling with how to model the following fields: sex (true/false) demographic classification (A, B, C etc) The reason I am struggling with these fields is that: They have no obvious hierarchical attributes which will aid aggregation (AFAIA) - which suggest they should be in a fact table They are mostly static or very rarely change - which suggests they should be in a dimension table. Maybe the heuristic I am using above is too crude? I will give some examples on the type of analysis I would like to carryout on the data warehouse - hopefully that will clarify things further. I would like to aggregate and analyze the data by sex and demographic classification - e.g. answer questions like: How does male and female weights compare across different demographic classifications? Which demographic classification (male AND female), show the most increase in weight this quarter. etc. Can anyone clarify whether sex and demographic classification are part of the fact table, or whether they are (as I suspect) dimension tables.? Also assuming they are dimension tables, could someone elaborate on the table structures (i.e. the fields)? The 'obvious' schema: CREATE TABLE sex_type (is_male int); CREATE TABLE demographic_category (id int, name varchar(4)); may not be the correct one.

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