By using Nextanalytics for Excel to load and pivot your data, you gain immediate access to information you can use. You don’t have to struggle with changing field formats, building transformation formulas or struggling with Excel’s complicated pivot tables.

Download sample data	We’ll start with a sample data set, downloaded here, that contains sales for bicycles and includes information about what, where and how much/how many. We’d like to understand what the trends are by territory and product, but we’d also like to see which products attributes appeal to different regions. Nextanalytics for Excel makes this a simple process.
Load compressed files	To get started, we’ll load the demonstration file that we downloaded. Note that Nextanalytics for Excel can load the zipped CSV file directly – no need to uncompress! As the file is loaded, is it automatically analyzed and a preliminary pivot operation is performed.
Automatic trending	Since trends are very popular, if there is a date column in the file, Nextanalytics for Excel will pivot it to the columns automatically and show you the most recent 7 periods. The main Nextanalytics for Excel form opens and hovers over the worksheet. This allows you to make changes in the form and immediately see the resulting worksheet. At any time, you could close the form and work with the results, using Nextanalytics for Excel simply to load and pivot the data.
	The results are automatically placed in the worksheet as simple text and numbers where they can be easily manipulated and formatted. For many people, this can be a vast improvement over the restrictions and complexity of the Excel pivot table.

Incoming data pre-analyzed	Once the data is loaded, we can check the columns listed in the Incoming box on the Pivot tab of the form. Note that a couple of them have been highlighted in red. Nextanalytics for Excel has determined that these columns are not likely candidates for an analysis report. You can still use them if you want – the product will not prevent you from working with your data the way you want – but they don’t lend themselves to summary reports.
	Nextanalytics for Excel will try to help you with your analysis, telling you about your source data, but it will not restrict what you can do.
Too many unique values	In this case, the Account column has been highlighted because it has 2820 values. It happens that this column is an account ID, or customer ID, code. If we were interested in finding out who the top customers were, we might want to use this in our analysis.
All the same value	The other column highlighted is the Category column. It was highlighted because it contains all the same value (“= Bikes”) and would be of limited use in an analysis. You still might use it if the data was pre-filtered or a subset of a larger data set and you need to know which group it came from.
Numbers or number-like?	You should also notice that the columns with numeric-looking values have been highlighted in green with “(numbers)” appended to them. In our example, this includes a column for the Size attribute of the bikes. It might be interesting to perform a numeric calculation with these values, like figuring out the average size of bike being sold. It is more likely that you would use the field in rows or columns as distinct values to see how many of a particular size were sold. When you do this, Nextanalytics for Excel will ensure the cells in the worksheet are formatted as text instead of numeric, avoiding a number of challenges working with the fields in Excel. This is especially important with things like numeric product codes.
	Numeric-looking data like product codes can be very difficult to work with in Excel. Nextanalytics for Excel places these values into text-formatted cells to make your work easier.