Insert/Update a SQL Server table using Merge Join in SSIS

I was asked a question awhile back on the easiest way to do an incremental load from one SQL Server table into another SQL Server table. This is common in data warehouses or reporting tables as you wouldn’t want to truncate a large table and perform a full insert. Instead, you would want to only copy the changes from the source to the destination. This could be an insert or an update. The easiest way, IMO, is SSIS. Let’s take a look.

Here’s how my environment is setup. I have two databases appropriately named Transactional (for transactional data) and Reporting (for static report data). Two tables, Source and Destination.

I also added some dummy data as you see below. I’ve highlighted what is different and will need to be changed in the destination table.

Let’s open SSIS and create a new SSIS project.
Drag and drop a Data Flow task into the design window, right click, Edit:

Next, drag and drop two OLE DB source components into the design window. I’m going to rename mine Source and Destination to match my table names.

Configure the two OLE DB sources to match the source table and the destination table. Below is a screenshot of my source connection manager.

Once your connection managers are configured let’s drag and drop two Sort components below each OLE DB Source and connect them to each source. We will be using a merge join next and the merge join component needs to have data sorted in ASC or DESC order. I always choose to sort on the Primary Key for each table.

In my example, I’ll choose to sort on my primary key, ID.

Next, drag the Merge Join transformation into the Design window and drag the data path from the Sort component to the Merge Join. When you attach the arrow to the transformation, the Input Output Selection dialog box appears, displaying two options: the Output drop-down list and the Input drop-down list. The Output drop-down list defaults to Source Output, which is what we want. From the Input drop-down list, select Merge Join Left Input, as shown below. We’ll use the other option, Merge Join Right Input, for the other connection.

Next, connect the data path from the other Sort component to the Merge Join transformation. This time, the Input Output Selection dialog box does not appear. Instead, the Input drop-down list defaults to the only remaining option: Merge Join Right Input.

Now, let’s configure the Merge Join transformation.

The first setting in the Merge Join Transformation Editor is the Join type drop-down list. From this list, you can select one of the following three join types:

  • Left outer join: Includes all rows from the left table, but only matching rows from the right table. You can use the Swap Inputs option to switch data source, effectively creating a right outer join.
  • Full outer join: Includes all rows from both tables.
  • Inner join: Includes rows only when the data matches between the two tables.

For our example, we want to include all rows from left table but only rows from the right table if there’s a match, so we’ll use the Left outer join option.

You now need to select which columns you want to include in the data set that will be outputted by the Merge Join transformation. For this exercise, we’ll include all columns. To include a column in the final result set, simply select the check box next to the column name in either data source.

Almost finished, but first let’s add a Conditional Split transformation. This will allow us to insert new records or update previous records.

In the Conditional Split Editor, I created two outputs. If (Destination) ID is NULL then the record doesn’t exist so we’ll perform an INSERT. If the ModifiedDate is different between the two tables then we know something has been updated since the last execution and we need to update the record. See below.

Since we can perform and INSERT or an UPDATE we’ll need two destinations. First, for the INSERT, we’ll simply be doing an INSERT into the table so we can drag the OLE DB Destination component into the window, choose “INSERT” in the Input Output selection window, and use the Reporting connection manager.

I’m going to check the “Keep Identity” box since the ID column is an identity column.

Next, for the UPDATE statement we’ll drag the OLE Command component into the window and configure it. Select “UPDATE” in the Input Output Selection window.

In the Connection Managers tab, assign the connection manager for Reporting.

In the Connection Managers tab, assign the connection manager for Reporting.

In the column mappings tab, assign parameters:

Final package should look like the following:

Save and execute. You can see that we updated two records and inserted one record:

Going back to our query you can see that everything matches up now:

Using Bookmarks in Power BI

Using bookmarks in Power BI help you capture the currently configured view of a report page, including filtering and the state of visuals, and later let you go back to that state by simply selecting the saved bookmark.

You can also create a collection of bookmarks, arrange them in the order you want, and subsequently step through each bookmark in a presentation to highlight a series of insights, or the story you want to tell with your visuals and reports.

In this post we’ll quickly go over how to create a few bookmarks and view them as a slideshow if you will.

I’m going to use my March Madness Report I created in an earlier post. Once my report is opened in Power BI Desktop, I’m going to click on the View tab in the ribbon and select “Bookmarks Pane”

Bookmarks Pane

This should bring up a new Bookmarks pane inside PBI Desktop:


Remember, bookmarks are used to capture the current view of the report so I’m going to use the default view where I’m showing all data and I’m going to name the bookmark “Home”. Make sure all filters are selected to show all data and click Add under the bookmark pane. This will create a new Bookmark, named Bookmark 1. Click the ellipsis and select rename to rename the bookmark appropriately.

Next, I like North Carolina, so I’m going to go to my Team Filter and choose North Carolina which will show me data for only this team.

Team Filtered Power BI Report

In my bookmark pane, I’m going to click Add again and rename to North Carolina.

Next, I want to view data on North Carolina from 2000 to present so I’ll change the Year Filter.

Team and Year Filtered Power BI Report

In my bookmark pane, I’m going to click Add again and rename to North Carolina 2000-present.

Now, if I click on any of bookmarks, it will take me to the data that was saved for each. This is a great way to present data in a meeting/conference so you don’t have to manually change the filters during the engagement.

We can also click the View button in the Bookmark pane to view a slideshow using the arrows at the bottom to navigate:

Creating a Dynamic Date Range Title in Power BI

Creating a dynamic title in Power BI helps present the data and let’s the viewers know what the data is filtered on. In this post I’ll go over how to do this…

I have a sales report that I’d like to add a title that is based on the Order Date Slicer. Currently, the title is static text “Sales Report”

Sales Report

To create my dynamic title, I’ll first need to create a measure table that has my Order Date data. In this case, that table is FactInternetSales and the column is OrderDate.

To create a measure, click New Measure in the Power BI Desktop ribbon

Power BI Desktop Ribbon

Next, you’ll see a window where you can type code. In this example, I’ll use the following DAX

Next, you’ll see a window where you can type code. In this example, I’ll use the following DAX

Order Date Title = “Sales For ” &
MIN ( FactInternetSales[OrderDate] ) & ” to “
& MAX ( FactInternetSales[OrderDate] )

Let’s walk through this real quick.

The first line (Order Date Title = “Sales For “ &) is basically naming the measure and adding the beginning text for the title.
The second line (MIN ( FactInternetSales[OrderDate] ) & “ to “) is finding the minimum order date from FactInternetSales.OrderDate and then adding the “to” text.
The last line (MAX ( FactInternetSales[OrderDate] ) is finding the maximum order date from FactInternetSales.OrderDate.

This one was pretty easy. Once I’ve typed my DAX, hit the checkmark to make sure there are no errors and the click off screen.


Our measure has been created! Let’s go back and find it under the FactInternetSales fields pane.

Power BI Fields

Next, let’s click on the Card Visualization and move and size it appropriately to fit in our title space.

Card Visualization

While the card is highlighted, click on the new measure from the Fields pane and it will populate the card with the measure we created.

The only thing left to do is format the title and we’re all set! If we change the Order Date Slicer, you’ll notice the title changes with the date. See live example at the beginning of this post.

March Madness Power BI Dashboard

At the beginning of the year I set a goal to learn something new. I’ve always loved business intelligence and bringing data to life in the form of dashboards and charts so for the 1st half of the year I wanted to focus on Microsoft’s Power BI. I’m not going to explain what Power BI is, but if you want to read up on it go here:

This post is just going to show off my dashboard. 😊 See live example above.

I’m a huge sports fan and the best time of the year happens to fall in March. Besides my birthday being in March, it’s also March Madness. Hours and hours of basketball. I could of used AdventureWorks for my dataset, but I wanted to use something I’m interested in. I found some data containing every NCAA tournament game result since 1985 (when the tournament was expanded to the 64 team bracket). The dataset contains the year, round (1-6), seed of the teams (1-16), region (1-4) and the scores. Perfect. Let’s use this to create a dashboard.

There’s not a ton of data, but I used what I could and tried to answer some questions around wins and upsets. Here’s a screenshot of the final product:

March Madness Power BI Dashboard

You can see Wins By Team (Duke with 93, North Carolina with 78, etc), Wins by Seed, National Championships, and Upsets vs Wins by Year. You can also see that a total of 2142 games have been played with 199 different teams in the tournament.

This was really fun and answers a lot of the questions I was thinking in my head while designing. The top left corner also has slicers which help filter the data. For example, if I wanted to see only the data for 2015 I could change the Year slicer to 2015 and it would update all my visualizations:

March Madness Power BI Dashboard filtered by year 2015

You can see that Duke won the National Championship from the National Championships visualization. If you hover over the Wins and Upsets visualization, you’ll see there were 30 upsets out of 63 games.

Let’s say I want to view data for a certain Team. Let’s choose Alabama Crimson Tide. If I change the Team slicer to Alabama I can see some data based around this team.

March Madness Power BI Dashboard filtered by team Alabama Crimson Tide

Alabama has won 19 NCAA tournament games, 0 national championships, has been a 5 or 7 seed 21% of the time and they’ve had a few upsets along the way. Not bad for a football school.

What about data for the National Championship game? I can change the Round slicer to 6, which is the National Championship round and view the data this way.

March Madness Power BI Dashboard filtered by Championship game

I can see out of 34 games, there has only been 16 different teams make the National Championship. Duke leads the way with 6, followed by North Carolina and Connecticut with 4. The 1 seed has played in this game 59% of the time, and there were upsets in 1988, 1990, 1997, 2003, 2006, and 2016.

We can also click on the visualizations themselves to view data. For example, if we reset our slicers to show all data and click on the #1 seed in the Wins By Seed Donut Chart we see the following:

March Madness Power BI Dashboard filtered by #1 seed

We can see that the #1 seed has played in 419 games with a total of 41 different teams. Duke has won 51 games as the #1 seed while North Carolina has won 46. Duke has also won the National Championship 4 times as the #1 seed and in 1999 the #1 seed won 17 games which is the highest.

Really cool stuff. I loved working on this project and working with this data.

Using a DateTime Expression in a SSIS Destination

Recently, I’ve ran into a few situations where I needed to export some SQL data into a CSV on a daily basis. I also needed to keep these CSV files in an archive folder for reference in case a problem came up. Moving the files to an archive folder is not a problem using the “File System” task, but the CSV needs to be a unique name otherwise it will just overwrite the previous file. There are numerous ways to make the filename unique, but in the post I’ll describe adding a datetime stamp to each file which also helps determine when the file was created.

I’ll assume you already have a Data Flow task configured with a destination and a flat file source. In this example, I’m going to use the AdventureWorksDW2012 database and copy data from the DimProduct table to a CSV. I already have my OLE DB source task configured and now I’m going to configure the Flat Destination.

Right click the Flat File Destination and click Edit:

SSIS Expression Destination DateTime

In the Flat File Destination Editor, click New…

SSIS Expression Destination DateTime

Select Delimited and click OK.

I’ve created a blank CSV on my Desktop which we’ll use for now, but this will eventually change:

SSIS Expression Destination DateTime

Click OK and select Mappings and verify all the mappings from the source are correct:

4 - SSIS Expression Destination DateTime

Once this is verified, click OK. (For this example, I only want to copy the first 6 columns)

Next, we need to create an expression on the connection string so that it knows to add the datetime stamp. Click on the Flat File Connection Manager. Scroll down the Properties window until you see Expressions:

SSIS Expression Destination DateTime

Click the ellipsis beside Expressions and the Property Expressions Editor will appear:

SSIS Expression Destination DateTime

Under Property, select Connection String and click the ellipsis under Expression:

SSIS Expression Destination DateTime

You should now see the Expression Builder window. Here is where we will define our complete file name including file path. For this example, I want to create the CSV in a directory named CSV on the C: drive. The filename that I will use is Products_datetime stamp.csv so the final output should be C:\CSV\Products_20150417092331.csv

The expression I’ll use to achieve this is below:

"C:\\CSV\\Products_" + (DT_STR,4,1252)DATEPART( "yyyy" , getdate() ) + RIGHT("0" + (DT_STR,4,1252)DATEPART( "mm" , getdate() ), 2) + RIGHT("0" + (DT_STR,4,1252)DATEPART( "dd" , getdate() ), 2) + RIGHT("0" + (DT_STR,4,1252)DATEPART( "hh" , getdate() ), 2) + RIGHT("0" + (DT_STR,4,1252)DATEPART( "mi" , getdate() ), 2) + RIGHT("0" + (DT_STR,4,1252)DATEPART( "ss" , getdate() ), 2) + ".csv"

Type your expression in the Expression window of the Expression builder:

SSIS Expression Destination DateTime

Click Evaluate Expression to view the output:

SSIS Expression Destination DateTime

Now that the expression is built, click OK twice. You should now see the expression formula icon beside the Flat File Connection Manager:

SSIS Expression Destination DateTime

If we execute the package and look inside the CSV folder, you should see our new file:

SSIS Expression Destination DateTime

SQL Server Integration Services Connector for SalesForce


I have a list of contacts in my SQL Server database that I would like to import into Salesforce and keep Salesforce up to date as new contacts are entered daily into my database. I know there are a few different ways to accomplish this but I’d like to use a SSIS package so I can automate.


In my opinion, the best (and easiest) way to accomplish this goal is using SSIS packages and a component from CozyRoc called Salesforce Destination. CozyRoc provides advanced SSIS libraries of custom tasks, components and scripts for handling Zip, GZip, BZip2, Tar archives, enhanced script reuse and secure Internet communications. I always go to CozyRoc when I need a custom task. In this tip I’ll show you how to take a contact list from SQL Server and import it into SalesForce. I’ll also show you how to schedule this on a daily basis.

For this example, let’s say I have a contact table in my SQL Server database like the following:

SQL Server SSIS SalesForce

I need to import these records into my Contacts tab in SalesForce:

SQL Server SSIS SalesForce

Create SSIS package

First thing I’ll need to do is download the CozyRoc SalesForce component. This download can be found here:

I’ll download and install this component on the server or workstation that I plan on developing the package. Once installed, open SQL Server Data Tools and create a SSIS project:

SQL Server SSIS SalesForce

First, let’s create a connection to the SQL Server database that stores the contact information and the Salesforce destination:

Right click in Connection Manager and create “New OLE DB Connection”:

SQL Server SSIS SalesForce

Type Server Name, credentials, and select database from drop down that stores the contact information. In this example, I’m selecting my local server and Demo database:

SQL Server SSIS SalesForce

Test Connection and click OK. Right click on the Connection Manager again and click “New Connection”:

SQL Server SSIS SalesForce

If the Salesforce Destination component was installed properly, you should see a connection called “SFORCE”:

SQL Server SSIS SalesForce

Click Add. Type your UserName and Password + Security token. If you don’t know your security token click here to read more about resetting it.

SQL Server SSIS SalesForce

Once you have entered your login credentials, make sure to test connection.

You should now have two connections in Connection Managers:

SQL Server SSIS SalesForce

Now to designing the package:

From the Control Flow we will add our Data Flow Task and right click to configure.

SQL Server SSIS SalesForce

Add the OLE DB source and SalesForce Destination tasks to the designer:

SQL Server SSIS SalesForce

Configure OLE DB Source:

SQL Server SSIS SalesForce

To configure the SalesForce Destination right click and edit. Choose the connection manager you created earlier:

SQL Server SSIS SalesForce

Click the Component Properties tab and you’ll notice a few options under Custom Properties:


Action Description
Create Create a new record in the destination object
Update Update an existing record in the destination object. You must specify the appropriate object record identifier for the update to work.
Delete Delete an existing record from the destination object. You must specify the appropriate object record identifier for the delete to work.
Upsert Update and insert a record in the destination object. Selecting this value displays the dynamic parameter ExternalId.


Batch Size: Specify the number of rows to be sent as a batch. The maximum for regular mode is 200. The maximum for bulk-load is 10,000\.

Destination Object: Specify the destination Salesforce object from a dropdown where the data is to be loaded.

ExternalID: Specify the external identifier field for updating the foreign key lookup with an external identifier.


Value Description
Regular Process the data in regular mode
BulkData Process the data in bulk-load data mode
BulkBinary Process the data in bulk-load binary mode

SQL Server SSIS SalesForce

Since we are adding Contacts, we’ll select Create (Action) and Contact from the DestinationObject option.

Click the Column Mappings tab and make sure all the columns are mapped correctly (delete mapping between ID’s for this example):

SQL Server SSIS SalesForce

Run the package and if everything is setup correctly your Salesforce instance should new contacts in it:

SQL Server SSIS SalesForceSQL Server SSIS SalesForce

Run this package as daily job

To run this package as a daily job that will populate Salesforce hourly, daily, weekly, etc. we’ll need to create a SQL Agent job and set a schedule.

Next Steps:

  • Updating Salesforce is a little more complicated and requires a custom field in Salesforce. The video titled “Upsert with external ID” located here will help with this.
  • Check out com for your custom SSIS needs.

Collect SQL Server Performance Counters and Build Reports with SSRS

Third party tools are awesome for capturing performance metrics, but some small shops (and even large shops) don’t budget for this type of software leaving it up to the DBA to create their own monitoring solution.

There are a few different ways to capture certain performance metrics, but in this post I’ll focus on using the sys.dm_os_performance_counters DMV and how to view this data in a more readable form using SQL Server Reporting Services graphs. The DMV doesn’t include all the counters as Performance Monitor, but it does show the SQL Server related counters. (Note that some of the counters in this DMV are of cumulative values since the last reboot.)

You can query this DMV using the following query:

SELECT * FROM sys.dm_os_performance_counters

SQL Freelancer SQL Server Performance Counters SSRS

As you can see from the screenshot above, this can be hard to read. Also, it only shows the current values at the time the query is executed so you don’t know anything about the past and it makes it hard to see how the data fluctuates during the business day.

Collecting the SQL Server Monitoring Report Data

For the purpose of simplicity, this tip will focus on one counter, Page Life Expectancy (PLE). I’ll show you how to capture data and create a graph for analysis.

First, we’ll need to create a table that will store our metrics:

CREATE TABLE [dbo].[CounterCollections](
[ID] [int] IDENTITY(1,1) NOT NULL,
[object_name] [varchar](128) NOT NULL,
[counter_name] [varchar](128) NOT NULL,
[cntr_value] [bigint] NOT NULL,
[collection_datetime] [datetime] NOT NULL )

Next, we’ll need to create a script that will insert our data into the table we created above:

INSERT INTO CounterCollections
SELECT object_name, counter_name, cntr_value, GETDATE() collection_datetime
FROM sys.dm_os_performance_counters
WHERE object_name = ‘SQLServer:Buffer Manager’
AND counter_name = ‘Page life expectancy’

Finally, we’ll need to create a SQL Server Agent Job that will run the script above on a specified schedule:

SQL Freelancer SQL Server Performance Counters SSRS
I’ll run this job every 5 minutes:

SQL Freelancer SQL Server Performance Counters SSRS

Creating the SQL Server Monitoring Report

While the table gathers data we can switch over to Business Intelligence Development Studio (BIDS) or the SQL Server Data Tools (SSDT) and create a SSRS Report that will display our data.

In this example, I’m using SSDT. Choose File, New Project. On the New Project dialog choose Report Server Project and name the Project:

SQL Freelancer SQL Server Performance Counters SSRS
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Power Query for Excel

In this post, I’ll discuss the prerequisites and how to install and enable Power Query (Data Explorer) and I’ll show you how to use this new feature.


  • Requires Microsoft Office 2010 SP1 or Microsoft Excel 2013 32-bit or 64-bit
  • Requires Windows Vista (with .Net 3.5 SP1 or greater), Windows Server 2008 (with .Net 3.5 SP1 or greater), Windows Server 2008 R2, Windows 7 or Windows 8.


Download and install the preview from Microsoft Download Center

Once the feature is installed open Excel and go to File, Options, Add-Ins. Select COM Add-Ins and click Go.

SQL Freelancer SQL Server Excel Data Explorer Power Query BI
Check Microsoft “Data Explorer” Preview for Excel and click OK.
SQL Freelancer SQL Server Excel Data Explorer Power Query BI
Once Data Explorer has been enabled, the tab will appear above the Office ribbon.

SQL Freelancer SQL Server Excel Data Explorer Power Query BI

Now that we have Data Explorer installed and enabled we can get to the fun stuff.

To see a detailed list of each element you can visit Microsoft Data Explorer Help

If you click on the Data Explorer tab you will notice Get External Data. Just like Excel and PowerPivot, this is where our data source will come from. There are multiple data sources to choose from including websites, files, databases, Active Directory, and even Facebook. Yes….Facebook.

SQL Freelancer SQL Server Excel Data Explorer Power Query BI

In this tip, I’ll show you examples of two data sources. We’ll pull data from a website and create a map report using PowerView and we’ll pull data from Facebook and make a report using PowerPivot.

Web Data Source

In the first example, I’ll pull table data from the web using Wikipedia. Choose “From Web” from the Get External Data section and use the following URL:

SQL Freelancer SQL Server Excel Data Explorer Power Query BI

Click OK

In the Query Editor under Navigator, select Countries. This will display rank, country, population, date, % of world population and source. We can filter columns just like in Excel by selecting the header arrow and choosing the appropriate filter. In this example, we’ll filter Source to only includes records that are an official estimate.

SQL Freelancer SQL Server Excel Data Explorer Power Query BI
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Microsoft’s new 3D data visualization BI product – Power Map

Microsoft has introduced a new BI product that will provide 3D data visualization using Bing Maps. This product is still in beta and is codenamed “GeoFlow” but should be out late 2013 or early 2014. This preview will allow you to plot geographic and temporal data visually, analyze that data in 3D, and create visual tours. It is a really cool product and I can’t wait to use it in a business atmosphere.

In this post, I’ll discuss the prerequisites and how to install “GeoFlow” and I’ll give an introduction on how to use this feature.


  • Requires Microsoft Office Professional Plus 2013 or Office 365 ProPlus
  • Supports 32-bit or 64-bit machines
  • Requires Windows 7, Windows 8, or Windows Server 2008R2 (requires .NET Framework 4.0)
  • Requires internet access


Download and install the preview from Microsoft Download Center (make sure Excel is closed while installing)

Open Excel and “Maps” will appear as a new item in the “Insert” tab of the Excel ribbon:

SQL Freelancer SQL Server Excel GeoFlow Power Map BI
Now that “GeoFlow is installed, we can begin using the new feature.

For this tip, I’m using the AdventureWorks2012 database and the result set from the following query imported into Excel:

  FROM [AdventureWorks2012].[Sales].[SalesOrderHeader] soh
  JOIN [AdventureWorks2012].[Person].[Address] ps ON soh.ShipToAddressID = ps.AddressID
  JOIN [AdventureWorks2012].[Person].[StateProvince] psp ON psp.StateProvinceID = ps.StateProvinceID
  WHERE StateProvinceCode = 'CA'

SQL Freelancer SQL Server Excel GeoFlow Power Map BI
Once you have the data in Excel, click on the “Insert” tab on the Office ribbon and click Map. You should now see the “GeoFlow” globe:

SQL Freelancer SQL Server Excel GeoFlow Power Map BI
There are a few tabs you can use right away in the ribbon bar. Under the “Map” item you can change Themes and add Map Labels. I like to enable the Map labels so I can see a more detailed version of the map. You can also zoom in and out and move the map using the arrows and +/- buttons in the bottom right corner of the map.SQL Freelancer SQL Server Excel GeoFlow Power Map BI
On the right side you see the “Layer” pane. This is where you will choose your geography visualizations. For this example Ill select “PostalCode” under the range section and since we know that this column stores zip codes we’ll map it to “Zip” under the Geography section:

SQL Freelancer SQL Server Excel GeoFlow Power Map BI

Once the fields are selected, click Map It.

You might notice that 86 records were updated meaning that there are 86 unique zip codes in California and it placed a marker on each zip code:

SQL Freelancer SQL Server Excel GeoFlow Power Map BI
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Building Key Performance Indicators (KPIs) with PowerPivot

A KPI (Key Performance Indicator) is a graphical representation that displays progress against a predefined measure or business goal. KPIs make it easier for end users to evaluate the amount of progress without reading a bunch of data.

In this post, I’ll use AdventureWorksDW2012 sample data so you can follow along with me. The database can be downloaded here.

Let’s get started.

Enabling PowerPivot in Excel 2013

To enable PowerPivot, open Excel, go to File, Options, Add-Ins, select COM Add-ins and click Go. This will open up the COM Add-Ins dialog box. Click “Microsoft Office PowerPivot for Excel 2013” and hit OK. After successfully enabling PowerPivot, the tab should appear at the top of the Excel spreadsheet:

SQL Freelancer SQL Server PowerPivot KPI

Importing Data

Open Excel, click the PowerPivot tab, Manage:

SQL Freelancer SQL Server PowerPivot KPI
Upon clicking Manage, a new window should appear. From this window, you will import data. Click From Database and select From SQL Server:

SQL Freelancer SQL Server PowerPivot KPI
Type in the Server Name, Authentication mode, and browse to the AdventureWorksDW2012 database:
SQL Freelancer SQL Server PowerPivot KPIClick Next, choose “Select from a list of tables and views to choose the data to import” and click Next. The next screen is where we will select our data to import. For this example, choose FactInternetSales and click “Select Related Tables”. The Select Related Tables button enables you to automatically select every table that is related to the source table selected:

SQL Freelancer SQL Server PowerPivot KPI
After clicking Finish, the import will begin. Once the import finishes successfully you should be able to view all the tables separated into sheets:

SQL Freelancer SQL Server PowerPivot KPI

Creating PivotTable

Before creating a KPI we will need to slice and dice our data into a PivotTable. To do this, click PivotTable on the ribbon bar and choose New Worksheet:

SQL Freelancer SQL Server PowerPivot KPI
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