Setting alternate row colors in SSRS (SQL Server Reporting Services) is an important visualization configuration for end-users so that they can easily view their reports. However, setting alternate colors in SSRS is not a click of a button configuration like in the Microsoft Excel.
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In the previous article, I gave an overview of Execute SQL Task in SSIS and we illustrated some of the differences between writing an expression to evaluate SqlStatementSource property and writing this expression within a variable and change the Execute SQL Task Source Type to variable.
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Decision trees, one of the very popular data mining algorithm which is the next topic in our Data Mining series. In the previous article Introduction to SQL Server Data Mining, we discussed what data mining is and how to set up the data mining environment in SQL Server. Then in the next article, Microsoft Naïve Bayes algorithm was discussed. In this Article, Microsoft Decision Trees are discussed with examples. The Microsoft Decision Trees algorithm is a classification and regression algorithm that works well for predictive modeling. The algorithm supports the prediction of both discrete and continuous attributes.
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This article explores Row Sampling Transformations in SSIS and Percentage Sampling Transformations in SSIS packages
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This article explores the Character Map Transformation in SSIS package with available configurations.
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In this article, I will give an overview of Execute SQL Task in SSIS and I will try to illustrate some of the differences between writing an expression to evaluate SqlStatementSource property or writing this expression within a variable and change the Execute SQL Task Source Type to a variable.
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In the article, SQL Server CHECKPOINT, Lazy Writer, Eager Writer and Dirty Pages in SQL Server, we talked about the CHECKPOINT process for SQL Server databases. This article is about CHECKPOINT in SSIS package.
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This article explains the process of configuring Error handling in SSIS package.
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SQL Server Integration Services or SSIS is used as an ETL tool to extract-transform-load data from heterogeneous data sources to different databases. After extracting data from the different sources, most often there are a lot of transformations needed. One of the frequent transformations is SSIS Conditional Split.
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This article explores the Term extraction transformation in SSIS and its usage scenario.
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In this article, I will give an overview of SSIS OLE DB Destination and SQL Server Destination and I will try to illustrate some of the differences between both destination components based on my personal experience, SSIS official documentation and some other experts experience in this domain.
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We will explore Lookup Transformation in SSIS in this article for incremental data loading in SQL Server.
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In this article, I will first give an introduction about SSIS expressions, then I will describe briefly the Expression Task and how to Evaluate a variable as expression. Then I will do a comparison between these two features to illustrate the similarities and differences between them.
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This article gives an overview of the different methods of SQL Server SSIS Package Logging.
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This article explores the SSIS Multicast Transformation for creating different logical copies of source data.
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SQL Server Integration Services provides a wide variety of features that helps developers to build a robust Extract, Transform, and Load process. After many years contributing to SSIS-related tags on Stackoverflow.com, I can say that many developers have some misunderstandings about SSIS features (SSIS OLE DB Source, SSIS Expressions, SQL Server destination …) especially those which are very similar and have some common usability.
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This article explores the SSIS Conditional Split Transform task to split data into multiple destinations based on the specified conditions.
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While building and deploying an SSAS OLAP cube, there are two processing orders that you can choose from when you create a process operation:
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In this article, we will walk through Microsoft Naive Bayes algorithm in SQL Server.
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This is the fifth article of a series dedicated to discovering geographic map tools in Power BI.
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Prediction, is it a new thing for you? You won’t believe you are predicting from the bed to the office and to back to the bed. Just imagine, you have a meeting at 9 AM at the office. If you are using public transport, you need to predict at what time you have to leave so that you can reach the office for the meeting on time. Time may vary by considering the time and the day of the week, and the traffic condition etc. Before you leave your home, you might predict whether it will rain today and you might want to take an umbrella or necessary clothes with you. If you are using your vehicle then the prediction time would be different. If so, you don’t need to worry about the rain but you need to consider the fuel level you need to have to reach to the office. By looking at this simple example, you will understand how critical it is to predict and you understand that all these predictions are done with your experience but not by any scientific method.
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One shared characteristic among popular data visualization tools such as Power BI is the ease at which data can be extracted from a variety of disparate data sources, usually at a click of a button, as shown in Figure 1. Such convenience, though, tends to come at a cost as you often have little control over how background scripts used to extract data are generated. Yet, this should be of utmost concern for data architects and BI developers alike as rarely do you find auto-generated scripts that are efficient and optimal. In this article, join me as I put on my DBA hat and trace, monitor and review SQL batch statements that are auto-generated by the Get Data feature in Power BI using SQL Server Extended Events.
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Just over a year ago, I published How to migrate SQL Server 2017 Master Data Services Models into another server article, that essentially demonstrated the migration of a SQL Server Master Data Services (MDS) model from one MDS instance to another. Like many of my previously published articles, I have since used the aforementioned article as a technical reference (i.e. syntax lookup for using MDSModelDeploy.exe utility) during the implementation of MDS-related projects for my clients.
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Whilst Power BI continues to be the leading data visualisation tool in Gartner’s BI quadrant, Dynamics 365 for Customer Engagement (formerly Dynamics CRM) remains one of popular business platforms for driving sales and facilitating customer communications. Thus, an integration of Power BI into Dynamics 365 for Customer Engagement ensures that you get to explore your Dynamics 365 for Customer Engagement data via a powerful and rich data visualisation tool. However, as indicated in Figure 1, Dynamics 365 for Customer Engagement plans often come with a Power BI free license thereby limiting the type of Power BI features available to you. In this article, we look at how you can get the best out of your Power BI free license for the purposes of embedding Power BI artefacts into Dynamics 365 for Customer Engagement. Going forward, any references to Dynamics 365 for Customer Engagement plan in this article will be shortened to Dynamics 365.
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SQL server Integration services provides us with SSIS Web Service Tasks which assist us to drive web services.
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