A few months back I had been working on an interesting proof of concept for a human resources client (Mary Smith) who is the HR manager in a major hardware chain. The firm has a “ServiceNow” installation, with tables that stores employee ”hours worked”.
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We have all learned to love and hate the trusty Bike shop database. Almost every demo or presentation pertaining to SQL Server we do, we use the AdventureWorks sample database. Almost every code sample on books online references AdventureWorks for illustrations and practical explanations of a feature. When SQL Server 2005 was released Microsoft replaced the old Pubs & Northwind Sample databases with a more complete and more feature rich database called AdventureWorks. Ever since we have been using this new sample database for almost everything we want to test. Microsoft has now given us an even better sample database called WorldWideImporters, which utilises almost every SQL Server feature I can think of from Temporal Tables to In-Memory table.
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A few weeks back I had been working on an interesting proof of concept for a client within the food/grocery industry. The objectives were to be able to provide the client with information on sales patterns, seasonal trends and location profitability. In our previous “get-together” we discussed how to create a tabular model project and how to create efficient and effective reports utilizing Excel.
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SQL Server Resource Governor was introduced in SQL Server 2008. This feature is used to control the consumption of the available resources, by limiting the amount of the CPU, Memory and IOPS used by the incoming sessions, preventing performance issues that are caused by resources high consumption.
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If you have an Azure SQL Database, it is possible to replicate the data in multiple locations. In this new chapter, we will explain how to do it. This article has 3 sections:
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SSIS Pipeline performance counters monitor the processes which are related to the execution of packages and the Data flow engine’s the most crucial feature, the (Data) Pipeline. Their measurements reveal in which way the memory resources are acquired during the execution of the SSIS packages, and also, show the amount of memory used during that events. The proficient monitoring of the SSIS Pipeline memory usage can mitigate the potential issues of memory and data leakage, data transformation interruptions and overall, avoid data integration damage.
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Have you ever been in a situation where you had to manage hundres of MSSQL Servers? Well, I am right on track here and believe me it does not get easier, even minor tasks take quite the time to do in large enterprise enviornments. One of the solutions I like and I’m using to ease the administration of standard maintenance jobs across my servers was ‘master – target’ jobs. Within the article to follow I will introduce you to the concept, the prerequisites and the limitations they have.
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SQL Server 2016 introduced officially on the 1st of June 2016. It comes with many new features such as Query Store that maintains the execution plans history for the queries with its performance data in order to detect any slowness in the query caused by the new plans, so that the administrator can force the use of the better old plan.
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Power BI is an extremely popular new Microsoft Tool to create reports. In a previous article, we talked about Power BI Cloud based services. In that article, we connected from a SQL Azure Data Warehouse database to the Power BI Cloud services. In this new article, we will work with the Power BI Desktop Tool from zero. The Power BI Desktop is a reporting software that can be installed in your Windows machine to create reports locally and connect to different data sources like Azure, SharePoint, Active Directory, Exchange, Facebook, Google Analytics and many other data sources. We will create Reports from a SQL Server database and finally we will extract information from Facebook. With Power BI, you can easily access to maps at street level around the world.
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In my article, Warehousing JSON Formatted Data in SQL Server 2016, we had a look at available T-SQL options for converting JSON data into rows and columns for the purposes of populating a SQL Server based data warehouse. The increased popularity of JSON in modern web applications may create a requirement for data teams to expose some of their data to client applications (i.e. reporting tools, web services etc.) in a JSON format. In this article we take a look at how such a requirement can be implemented by data teams using SQL Server 2016 FOR JSON clause
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A few weeks back I had been working on an interesting proof of concept for a client within the food / grocery industry. The objectives were to be able to provide the client with information on sales patterns, seasonal trends and location profitability. The client was an accountant and was therefore comfortable utilizing spreadsheets. This said, I felt that this was a super opportunity to build our proof of concept utilizing a SQL Server Tabular Solution and by exploiting the capabilities of Excel and Power Reporting for the front end.
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One of the most common wait type seen on SQL Server and definitely one that causes a lot of troubles to less experienced database administrators is the PAGEIOLATCH_SH wait type. This is one of those wait types that clearly indicates one thing, but which background and potential causes are much subtler and may lead to erroneous conclusions and worse, incorrect solutions
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Converting a delimited string into a dataset or transforming it into useful data can be an extremely useful tool when working with complex inputs or user-provided data. There are many methods available to accomplish this task; here we will discuss many of them, comparing performance, accuracy, and availability!
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Although there is no real standardized classification of SQL Server Integration Services performance counters, the two main types are:
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Since we have presented a way to review the history of committed changes using Git, Team Foundation Server and Subversion, let’s check how the same can be achieved when working with the Mercurial source control system.
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A couple of weeks ago I got this idea to capture twitter feeds and store it in a relational database structure. I wanted to be able to do some trend analysis, to see what days certain hashtags get used more than other as well as to be able to go back to certain tweets and see what I can learn from them. I tried to get the Twitter API to work for me, but had no luck. So I came across Microsoft Flow which seems to make this process very easy.
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This article will introduce some minor, but very handy improvements in SSMS 2016, such as options for preventing the appearance of a dialog box for saving queries, setting up color of the interface theme, highlighting the current line and checking for a new SSMS updates.
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SQL Server Policy-Based Management was introduced in SQL Server 2008, to make it easy for database administrators to define and enforce SQL Server best practices and company standards in the form of policies. This feature is available in both Enterprise and Standard SQL Server Editions.
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The whole process of encryption of SSIS packages in SSMS relies on the Import Package and Export Package options; specifically, the combination of performing both of mentioned options in particular order, while choosing and setting the appropriate ProtectionLevel in the process.
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In my organization, the developers send a lot of database generated emails for informational purposes to ensure that everything in the system is still working 100%.We can call them production messages. Normally the way the email is presented is not important as it is only meant for the developer to help with system health check, but every now and again a business user would ask for the report (which was never meant to be an actual report) and then we would include the business user in the distribution list for this email.
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SQL Server 2016 became publically available on the 1st of June 2016. Some might feel that a new SQL Server release every 2 years might be too frequent with many organization still lagging behind by running SQL Server 2012 or earlier.
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In this article, I continue to review the exciting features available in SQL Server 2016. One such feature is the long awaited T-SQL support for JSON formatted data. In this article we take a look at how JSON support will impact data warehouse solutions.
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With the release of Microsoft SQL Server 2016 a lot of new features were introduced, one of which was Temporal Tables, a feature that gives you the ability to view the state of your data at a given point in time. This means you can go back in time with your data. Another very popular feature is Stretch Databases which allows for remote archiving of data to Azure Stretch region.
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One of the new enhancements in SQL Server Management Studio 2016 (SSMS) is the Scroll Bars tab, in which can be set various of settings for vertical scroll bar.
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