If you are opening a CSV file or an Excel file with only one worksheet, the navigator screen will not appear. You'll want the downloaded data from the QuickBooks general ledger, so pick the third item, QuickBooks GL Report, and click Edit. When you open your Excel file in Power Query, you are presented with the Power Query Navigator dialog box, as shown in the screenshot "Navigator Dialog Box." The navigator lists all of the worksheets within the workbook file. If you're loading a CSV file, choose the second option, From CSV. If you're loading an Excel file, choose the top option, From Workbook. In Excel 2016, Power Query is accessed by clicking on the Data tab and then clicking on the drop- down arrow next to New Query in the Get & Transform group and then selecting From File. Transforming the file begins with opening a blank workbook. This will open a dialog box, as shown in the screenshot "Modify Report: Reconciliation Detail." Columns are chosen by clicking on the Customize Report button in the QuickBooks report button bar. The second advantage is that a CSV file writes all amounts as values, so no conversion of formulas is needed.īegin the report configuration process by choosing the columns to be included in the report. An Excel file that contains many rows and formulas will take a very long time to fully load. The first is that the file loads in seconds. I prefer to use a CSV file because it offers two important advantages over an Excel file. option in the Send Report to Excel dialog box to configure the file's format. The second step involves using the Advanced. The first step is to choose the columns that you want included in the report. In QuickBooks, this is done in two steps. In either case, it is a best practice to first configure as much of the data as possible in their native application before exporting them to Excel. ![]() The online version of QuickBooks exports data only as an Excel file. EXTRACTING THE FILEĭata can be exported from desktop versions of QuickBooks to Excel as either a CSV file or as an Excel file. This article describes the best way to extract data from a desktop version of QuickBooks and use Microsoft Excel's Power Query feature to transform the data so that they can be analyzed through an Excel table or PivotTable. They begin with a process called ETL, which stands for extract, transform, and load. Although the instructions in this article are geared toward QuickBooks, they can be adapted to other accounting systems.Įxperienced data analysts use a standard approach to data mining. Download the file via the January article or by clicking here. We will use the same Excel file that was used in the above- referenced article to demonstrate how Power Query works and illustrate its added functionality in more complex situations. While this article uses Excel 2016, the steps are similar in Excel 20. In Excel 2016, it is included under the Data tab in the Get & Transform group. Power Query is available in Excel 2010 and Excel 2013 as a free add- in downloadable from Microsoft's website at. While analysis is best done in PivotTables, Power Query cleans the data for best use by PivotTables. Power Query uses an Excel spreadsheet- like interface, so navigating its features becomes second nature to an experienced Excel user.Ī good way to think about when and why to use Power Query is to consider its relationship to PivotTables. While it can load data from a variety of data sources, such as Excel, comma- separated value (CSV), and text files, and SQL, MySQL, and Oracle server databases, this article focuses on loading data from a CSV or Excel file. Power Query is a powerful tool for modeling and shaping data. ![]() While it is a best practice to do as much data scrubbing and transforming in a native application, Power Query can still add value in cleaning raw data and modeling them in a fashion that facilitates further analysis. This article describes how Microsoft Power Query for Excel can be used to easily transform data and be applied in subsequent periods so that very little additional work has to be done to obtain clean data. Challenges occur when subsequent data are added to the general ledger, because it is time- consuming to repeat all the steps in the scrubbing process. The approach works very well for most analyses. The January 2017 JofA article " Data Mining Your General Ledger With Excel" presents a step- by- step, formula- based approach to extracting general ledger data and then scrubbing them so that they can be readily analyzed through the use of PivotTables.
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