# Calculated Columns in PowerPivot

When importing data into PowerPivot, users often find the data is almost, but not quite what they need. Perhaps the name is not quite formatted as they need, or some calculation, not important in the stored data but very important to their work, is missing. For these situations PowerPivot offers Calculated Columns.

Calculated Columns provide a way for users to add that missing information they require into the source data. The calculations are done on a row by row basis, if you want to do something on the entire table, for example count the number of rows, you will instead need to create a measure in your PivotTable or PivotChart. Measures will be covered in a later post.

Let’s get started by using the same Excel 2010 workbook we ended with in the previous blog post. If you haven’t seen it, please go back and reference my post Combining Data from Multiple Sources in PowerPivot for the full details.

Our first task will be to address our customer names. In the source data, names are broken into five columns: Title, FirstName, MiddleName, LastName, and Suffix. For ease of use we wish to combine these distinct columns into one single column. Assuming you have opened the PowerPivot workbook, select the Customer table from the list of tabs at the bottom. Now go to the right-most column, ModifiedDate. Next to it you’ll see a blank column with the header “Add Column”. Click in it, then go up to the fx box right above the data.

The formula bar:

Into this formula bar we can create some fairly complex expressions. Let’s do one that shows some of the power of text formulas. Into the formula bar enter:

=[Title] & " " & [FirstName] & " " & IF(LEN([MiddleName]) > 0, [MiddleName] & " ", "") & [LastName] & IF(LEN([Suffix]) > 0, " " & [Suffix], "")

As with Excel, formulas need to begin with the equal sign. All literal string values are enclosed in double quote marks. Here we have two, a single space in the form of “ “ and an empty string in the form of “” (two double quotes right next to each other). The ampersand & character is used for concatenation. When using column names in the formulas, they must be enclosed in square brackets [ ] . Finally notice we’ve leveraged some standard Excel functions, first the LEN function which returns the length of the past in field. Then the IF function which evaluates the first statement (for example, LEN([MiddleName]) > 0 ). Then the area after the first comma ([MiddleName] & " " ) is returned if the statement was true, otherwise the area after the second comma ("" ) is returned.

After pressing enter on our formula PowerPivot will then calculate the values for each individual row in the dataset. The downside is this could take quite a while depending on the size of your data. A 100 million rows of data is going to take a while, even on a fast machine. The benefit though is this is the only time the calculation is done, unless of course the underlying data changes. Values are now calculated and available at analysis time.

You may notice the column name changes from Add Column to CalculatedColumn1. Since this is not something we’d want to show other users, or work with ourselves, simply right click on the column header, pick Rename Column, and give our new column a meaningful name. In this example I used FullName.

A quick side note, in the sample data the MiddleName and Suffix columns are not populated very often, as is often true with real data. However it can make browsing through our data a bit difficult. To validate our calculation, click the drop down menu triangle next to the MiddleName column, go to the bottom and uncheck the “Blank” option for data filtering. This will then remove all rows from the viewed data that are missing a middle name.

Note this doesn’t delete the rows, this is merely a filtering option in PowerPivot to help you view only the data you want. The other rows are still there, to prove it just click the menu arrow again and pick the “Clear filter from MiddleName” menu option and all rows will again be visible. For more information on filtering, see my post Import Filters in PowerPivot. The same filtering tools that apply to the data import process also work once the data is imported.

In addition to textual manipulation, PowerPivot also supports complex math calculations. Let’s do a simple example in the SalesOrderDetail tab. For simplicity, let’s decide that our base profit for any sale is 20 percent of the Line Total. However, for each item ordered we gain an extra 2 percent of profit. We’ll click in the Add Column area of the SalesOrderDetail tab and enter the following calculation:

=(.2 + ([OrderQty] * .02))*[LineTotal]

Now we can rename the column to EstimatedProfit using the rename menu option as described above.

We also have the power of the Excel math functions at our disposal. Let’s do something simple, and decide that we want to round the value of our EstimatedProfit column up to the next whole value. Even if the value was 1.01, it would round up to 2 dollars. To accomplish this we can use Excel’s ROUNDUP function:

=ROUNDUP((.2 + ([OrderQty] * .02))*[LineTotal], 0)

Yields these new results:

As you can see, they have indeed been rounded up to the next whole value. The 0 at the end of the formula indicated how many decimals should remain, I indicated none so we could see the results in whole dollars.

We’ve only just begun to explore the value in Calculated Columns. Not only can they fill in missing data, but they can also speed calculations when you reach the Pivot Table stage of your analysis by making aggregations much easier.

# Combining Data from Multiple Data Sources in PowerPivot

Seldom does the user of PowerPivot have all of the data they need in one nice, neat data source. More than often it will be necessary to import data from a variety of sources and make that data work together. It’s time to start building on what we’ve learned over the last few days to accomplish this feat.

First, launch Excel 2010 and use the PowerPivot import wizard to import the following tables from the AdventureWorksLT2008 database: Address, Customer, CustomerAddress, Product, ProductCategory, SalesOrderDetail, SalesOrderHeader. (Note, for a refresher on importing data please see my blog post, Import Filters in PowerPivot.)

Now we need a second source of data. Follow the instructions in my post Creating Tables in PowerPivot to enter the data below into Excel 2010, copy and paste it into a new PowerPivot table.

If you recall when we import data from a relational database, PowerPivot examines the foreign key relationships found in the database to create relationships between the tables it imports. In this situation though, the CountryInfo data didn’t get imported from a database, instead it was pasted in from a manually entered spreadsheet. Thus, PowerPivot has no information with which it can implicitly create a relationship.

We do want to create one however, so we can link the longer country name in the Address table to the CountryInfo data and thus be able to use the briefer country abbreviations. As PowerPivot was designed to work with many sources of data, it has an easy way to create these relationships.

In the PowerPivot window, click on the Table tab at the very top. All the way to the right you will notice a button group named Relationships. Click the Create Relationship button.

As the above dialog shows, this allows you to create a relationship, or a link between two tables in PowerPivot. Here we are creating a link between the Address table and the CountryInfo table on the CountryRegion field. When complete just click Create to create the relationship.

If you want to verify the relationship was indeed created, or review any of the relationships PowerPivot inferred when it imported the tables from the AdventureWorksLT2008 database, just click the Manage Relationships button in the Table Toolbar’s Relationships group.

On the very first row you’ll see the newly created relationship between the Address and CountryInfo tables. You’ll also see the other relationships that were created during the import process from the SQL Server database. The three buttons at the top let us Create new relationships, Edit existing ones, or Delete ones no longer needed. Note that the altering or deleting of relationships has no effect what so ever on the original source data (SQL Server or the Excel 2010 spreadsheet). It only affects the tables as stored in PowerPivot.

Now let’s see the new relationship in action. Close the Manage Relationships window, and on the PowerPivot Home tab create a new PowerPivot table (Pivot Table, Single Pivot Table). Go ahead and put it in a new worksheet.

In the Gemini Task Pane, go to the SalesOrderHeader table and drag the LineTotal field into the Values area. Next, drag the Name field from the Product table into the Row Labels area. Now for the magic, in the CountryInfo table drag the CountryAbbr field into the Column Labels area. Your pivot table should look something like this:

Because of the relationships that were inferred or that we created, PowerPivot was able to link the data like so:

To validate this for yourself, just return to PowerPivot and look at the Manage Relationships dialog to see all the links.

The need to combine data from many sources is a common task, one that will most certainly be done by users of PowerPivot. Using the techniques shown here, you can create and manage the relationships that will link data from these disparate sources together and leverage the power of PowerPivot.

# Creating Tables in PowerPivot

PowerPivot has the ability to import data from a wide variety of sources. But you could run across a situation where you don’t have that data stored anywhere. Perhaps it’s on a piece of paper, or in a text file, or it’s just in the user’s brain and needs to be typed in. Logically then you would want to create a new table in PowerPivot.

Except you can’t. PowerPivot itself doesn’t provide the ability to create tables and enter data directly into it. Now, before you start the usual rending of garments and gnashing of teeth plus a little wailing, there is a simple to implement solution.

Create a new Excel 2010 workbook. In sheet 1 (or any sheet) let’s enter the following information.

Now highlight the above cells and Copy them to the clipboard. Next, launch the PowerPivot window by going to the PowerPivot tab in Excel 2010 and clicking the PowerPivot window button.

Once PowerPivot is open, if you look in the middle group of buttons you’ll see a set named Paste from Clipboard The To New Table button should be activated now that you have data in your clipboard.

Click the To New Table button. When you do, the Paste Preview dialog appears.

This is similar to the preview window you see with the Import Table wizard, only not quite as much functionality. Here, we can view the data and validate that it is correct, which it is. We can also indicate if the first row contains our column headers, which in our case it does so we can just leave that option checked on. Click OK to import the data.

Above is our new data, now pasted into PowerPivot. We have the same abilities with it we have with any other table, we can sort, rename our columns, add new calculated columns, and more. As you will note from the tab at the bottom of the picture, the data was pasted into a table with the rather uninformative name of Table. We can do better than that, so right click on the Table tab and pick Rename from the menu. Overwrite Table with CountryInfo.

Now you can see how easy it is to create new data from scratch and paste it into PowerPivot. In this example I used a limited number of rows for illustrative purposes, but it’s quite possible to import massive amounts of data. In addition, you can add to your table later. In this example all we would have had to do is Paste Append from the toolbar.

In the next blog post we’ll build on what we’ve learned and look at how to combine data imported from multiple sources.

# Import Filters in PowerPivot

PowerPivot has the ability to import millions of rows of data into Excel 2010 for purposes of analyzing, slicing and dicing. However, even though you can import vast amounts of data you may not always want to. There are many reasons for this.

You may wish to limit the amount of data for security reasons. Perhaps bringing in all of the data may put an unneeded strain on the server. Most likely though, is you simply do not need all of the data. As an analyst you may be interested in only the data for a segment of your organization, such as a single plant or department.

Fortunately filtering data is an easy task. If you are not familiar with importing data into PowerPivot, may I suggest you first review my step by step posted yesterday.

Launch Excel 2010 and go to the PowerPivot tab, then launch the PowerPivot window. Select the "From Database" to start the import process, and for this example we’ll use SQL Server. Now, like in my previous blog post enter your credentials to connect to a SQL Server. For this example we’ll just pick one table, SalesOrderDetail from the AdventureWorksLT2008 database.

With the SalesOrderDetail picked, look in the lower right side of the dialog. You will see a button labeled "Preview & Filter".

When you click that button you should see a new dialog appear.

Here you can see a subset of your data, only the first few rows. It’s enough to give you an idea of what the data looks like, but it won’t show you every single row. Considering the fact that PowerPivot is capable of importing millions of rows, this is probably a good thing.

Within this dialog we can do some pretty powerful things. Let’s start by eliminating a column we don’t need in the data we want to import. Scroll to the right until you see the rowguid column and uncheck the box next to the column header, as you see below.

By unchecking this box this column will not be imported into our Excel 2010 PowerPivot table.

Recall though that the name of this dialog was Preview & Filter. We can also do some review of our data to ensure it’s what we want. Let’s say we want to look to see the range of values for our line totals. Click the downward facing triangle button to the right of the LineTotal column header. A drop down menu will appear. Select "Sort Smallest to Largest"

Scrolling through the data you’ll notice that the data has indeed been sorted. Also note the menu icon to the right of the column name changes to indicate a sort has been applied to this column. (Remember though it’s not showing all rows, just the first few sorted in order.) An important thing to note tough, this sorting applies only to the data as you see it in the Preview & Filter area, once you click the Finish button on the Table Import Wizard the sort is removed. While the preview options in this dialog are not saved, filters are. If you had pressed Finished, you’d have seen that rowguid is not included in the result set. But don’t click Finish yet, we’re not quite done filtering.

For our next filter, let’s decide for purposes of this report we are only interested in large orders. We’ll define large as "Line Total greater than 1,000 dollars". Once again open the menu to the right of the LineTotal column header and select "Number Filters". A pop out menu will appear, from it select "Greater Than…"

When the Custom Filter pops up, enter 1000 next to the is greater than box and click OK.

Clicking OK will reveal lesser amounts have been removed. Other filters besides numeric filters are available. For text data, you have "is equal to" and "is not equal to" available. Date filters work the same, having the "is equal to" and "is not equal to" available. I’m hopeful that for date types further functionality will be added in the future, such as date ranges or "is greater/less than" types of functionality.

Let’s click the OK button on the Preview & Filters window to return to the Table Import Wizard. You’ll now see an Applied filters link in the row with the table name, click it to see what filters are in effect.

When you click the link you’ll see:

While you cannot edit this information, it is nice to see it all in one location. Click OK to close and return to the previous window.

Click Finish to complete the import. You will see the data you asked for, only rows with LineTotal greater than 1000 and without the rowguid column.

Hopefully you’ve seen how powerful the filtering tools included with PowerPivot are. Using them you can remove unwanted rows and columns, limiting not only the amount of data you have to pull across the network but that you have to store locally in the PowerPivot Excel 2010 spreadsheet. Limiting your data will ensure only the rows required for the analysis are included, saving time and enhancing security.

# Introducing Microsoft PowerPivot

What is PowerPivot? Well according to Microsoft:

“PowerPivot is Microsoft Self-Service Business Intelligence”

I can see from the glazed looks you are giving your monitor that was clear as mud. So let’s step back a bit and first define what exactly is Business Intelligence.

Business Intelligence, often referred to as simply “BI”, is all about taking data you already have and making sense of it. Being able to take that information and turn it from a raw jumble of individual facts and transform it into knowledge that you can take informed actions on.

In every organization there is already someone who is doing BI, although they may not realize it. Microsoft (and many IT departments) refer to this person as “that guy”. A power user, who grabs data from anyplace he (or she) can get it, then uses tools like Excel or Access to slice it, dice it, and analyze it. This person might be an actual Business Analyst, but more often it’s someone for who BI is not their main job. Some common examples of people doing their own BI today are production managers, accountants, engineers, or sales managers, all who need information to better do their job. Let’s look at an illustration that will make it a bit clearer.

In this example, put yourself in the role of a sales manager. You have gotten IT to extract all of your sales orders for the last several years into an Excel spreadsheet. In order to determine how well your sales people are doing, you need to measure their performance. You’ve decided that the amount sold will be a good measure, and use Excel to give you totals.

In BI terms, the column “Total Sales” is known as a measure, or sometimes a fact, as it measures something, in this case the sales amount. The grand total sales amount is often called an aggregation, as it totals up the individual rows of data that IT gave us. But now you might be wondering why Andy’s sales are so low? Well, now you want to dig deeper and look at sales by year.

In BI terms, the names of the sales people are a dimension. Dimensions are often either a “who” (who sold stuff) or a “what” (what stuff did we sell). Places (where was it sold) and dates (when was it sold) are also common dimensions. In this case the sales dates across the top (2007, 2008, 2009) are a date dimension. When we use two or more dimensions to look at our measures, we have a pivot table.

Now we can see a picture emerging. It’s obvious that Andy must have been hired as a new salesperson in late 2008, since he shows no sales for 2007 and very small amount in 2008. But for Paul and Kimberly we can look at something called trends in the BI world. Kimberly shows a nice even trend, rising slowly over the last three years and earns a gold star as our top performer.

By being able to drill down into our data, we spot another trend that was not readily obvious when just looking at the grand totals. Paul has been trending downward so fast the speed of light looks slow. Clearly then we now have information to take action on, commonly known as actionable intelligence.

So remind me, why do we need PowerPivot?

As you can see in the above example, “that guy” in your company clearly has a need to look at this data in order to do his job. Not only does he need to review it, he also has the issue of how to share this information with his co-workers. Unfortunately in the past the tools available to “that guy” have had some drawbacks. The two main tools used by our analyst have been either Excel, or a complete BI solution involving a data warehouse and SQL Server Analysis Services.

Excel’s main limitations center around the volume of data needed to do good analysis. Excel has limits to the number of rows it can store, and for large datasets a spreadsheet can consume equally large amounts of disk space. This makes the spreadsheet difficult to share with coworkers. In addition mathematical functions like aggregations could be slow. On the good side, Excel is readily available to most workers, and a solution can be put together fairly quickly.

A full blown BI solution has some major benefits over the Excel solution. A data warehouse is created, and then SQL Server Analysis Services (often abbreviated as SSAS) is used to precalculate aggregations for every possible way an analyst might wish to look at them. The data is then very easy to share via tools like Excel and SQL Server Reporting Services. While very robust and powerful solution, it does have some drawbacks. It can take quite a bit of time to design, code, and implement both the data warehouse and the analysis services pieces of the solution. In addition it can also be expensive for IT to implement such a system.

Faster than a speeding bullet, more powerful than a locomotive, it’s PowerPivot!

PowerPivot combines the best of both worlds. In fact, it’s not one tool but two: PowerPivot for Microsoft Excel 2010, and PowerPivot for SharePoint 2010. What’s the difference you ask? Good question.

PowerPivot for Microsoft Excel 2010

PowerPivot acts as an Add-on for Excel 2010, and in many ways is quite revolutionary. First, it brings the full power of SQL Server Analysis Services right into Excel. All of the speed and power of SSAS is available right on your desktop. Second, it uses a compression technology that allows vast amounts of data to be saved in a minimal amount of space. Millions of rows of data can now be stored, sorted, and aggregated in a reasonable amount of disk space with great speed.

PowerPivot can draw its data from a wide variety of sources. As you might expect, it can pull from almost any database. Additionally it can draw data from news feeds, SQL Server Reporting Services, other Excel sheets, it can even be typed in manually if need be.

Another issue that often faces the business analyst is the freshness of the data. The information is only as good as the date it was last imported into Excel. Traditionally “that guy” only got extracts of the database as IT had time, since it was often a time consuming process. PowerPivot addresses this through its linked tables feature. PowerPivot will remember where your data came from, and with one simple button click can refresh the spreadsheet with the latest information.

Because PowerPivot sits inside Microsoft Excel, it not only can create basic pivot tables but has all the full featured functionality of Excel at its disposal. It can format pivot tables in a wide array of styles, create pivot charts and graphs, and combine these together into useful dashboards. Additionally PowerPivot has a rich set of mathematical functionally, combining the existing functions already in Excel with an additional set of functions called Data Analysis eXpressions or DAX.

PowerPivot for SharePoint 2010

PowerPivot for Excel 2010 clearly solves several issues around the issue of analysis. It allows users to quickly create spreadsheets, pivot tables, charts, and more in a compact amount of space. If you recall though, creation was only half of “that guys” problem. The other half was sharing his analysis with the rest of his organization. That’s where PowerPivot for SharePoint 2010 comes into play.

Placing a PowerPivot Excel workbook in SharePoint 2010 not only enables traditional file sharing, but also activates several additional features. First, the spreadsheet is hosted right in the web browser. Thus users who might not have made the transition to Excel 2010 can still use the PowerPivot created workbook, slicing and filtering the data to get the information they require.

Data can also be refreshed on an automated, scheduled basis. This ensures the data is always up to date when doing analysis. Dashboards can also be created from the contents of a worksheet and displayed in SharePoint. Finally these PowerPivot created worksheets can be used as data sources for such tools as SQL Server Reporting Services.

Limitations

First, let me preface this by saying as of this writing all of the components are either in CTP (Community Technology Preview, a pre-beta) or Beta state. Thus there could be some changes between now and their final release next year.

To use the PowerPivot for Excel 2010 components, all you have to have is Excel 2010 and the PowerPivot add-in. If you want to share the workbook and get all the rich functionality SharePoint has to offer, you’ll have to have SharePoint 2010, running Excel Services and PowerPivot 2010 Services. You’ll also have to have SQL Server 2008 R2 Analysis Services running on the SharePoint 2010 box. Since you’ll have to have a SQL Server instance installed to support SharePoint this is not a huge limitation, especially since SSAS comes with SQL Server at no extra cost.

One thing I wish to make clear, SharePoint 2010 itself can run using any version of SQL Server from SQL Server 2005 on. It is the PowerPivot service that requires 2008 R2 Analysis Services.

One other important item to note: at some point the load upon the SharePoint 2010 server may grow too large if especially complex analysis is being done. Fortunately SharePoint 2010 ships with several tools that allow administrators to monitor the load and plan accordingly. At the point where the load is too big, it is a clear indication it’s time to transition from a PowerPivot solution to a full BI solution using a data warehouse and SQL Server Analysis Services.

What does PowerPivot mean for business users?

For business users, and especially “that guy”, it means complex analysis tools can be created in a short amount of time. Rich functionality makes it easier to spot trends and produce meaningful charts and graphs. It also means this information can be shared with others in the organization easily, without imposing large burdens on the corporate e-mail system or local file sharing mechanisms.

No longer will users be dependent on IT for their analysis, they will have the power to create everything they need on their own, truly bringing “self service BI” to fruition.

What does PowerPivot mean for Business Intelligence IT Pros?

The first reaction many BI developers have when hearing about PowerPivot is “oh no, this is going to put me out of a job!” Far from it, I firmly believe PowerPivot will create even more work for BI Professionals like myself.

As upper management grows to rely on the information provided by PowerPivot, they will also begin to understand the true value BI can bring to an organization. Selling a new BI solution into an organization where none currently exists can be difficult, as it can be hard to visualize how such a solution would work and the value it brings. PowerPivot allows BI functionality to be brought into an organization at a low development cost, proving the value of BI with minimal investment. Thus when there is a need to implement a larger, traditional BI project those same managers will be more forthcoming with the dollars.

Second, as users pull more and more data, they are going to want that data better organized than they will find in their current transactional business systems. This will in turn spur the need to create many new data warehouses. Likewise the IT department will also want data warehouses created, to reduce the load placed on those same transactional business systems.

I also foresee PowerPivot being used by BI Pros themselves to create solutions. The database structure of many transactional database systems can be difficult to understand even for experienced IT people, much less users. BI Pros can use PowerPivot to add a layer of abstraction between the database and the users, allowing business analysts to do their job without having to learn the complexity of a database system.

BI Pros can also use PowerPivot to implement quick turnaround solutions for customers, bringing more value for the customer’s dollar. When a BI Pro can prove him (or her) self by providing rich functionality in a short time frame it’s almost always the case they are brought back in for multiple engagements.

PowerPivot also provides great value to BI Pros who are employed full time in an enterprise organization. They can create solutions much quicker than before, freeing them up to do other valuable tasks. In addition PowerPivot solutions can provide a “stop gap” solution, pushing the date at which the organization needs to spend the dollars for a full blown BI solution and allowing IT to plan better.

Finally I see great value in PowerPivot as a prototyping tool for larger BI projects. Now users can see their data, interact with it, analyze it, and ensure the required measures and dimensions are present before proceeding with the larger project.

I’ll reiterate, if anything I believe PowerPivot will create an explosion of work for the Business Intelligence Professional.