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30-Jul-2016 13:01 by 9 Comments

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There are some new and powerful Business Intelligence options available to all of us, from scalable cloud platforms to the Excel on the desktop.So its a good time to demonstrate some of them and show where BI and Application Development meet.

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The set of “Power” components (Power Query, Power Pivot and Power BI) all sound a bit like the marketing guys won the naming battle again and don’t really help explain the technology nor where they fit so I avoided it for a long time.That is until this latest version of Office where you can’t really avoid it.So it came time to take Power Query and M by the scruff and learn it.First let’s put these new “Power” technologies in their relative places: So I set myself a goal to create a spreadsheet that auto updates with stock prices.First get a version of Excel (2010 or above) which supports Power Query and download the Power Query installer this is already embedded in the later versions of Excel but may need an update. s=" & symbol & #"from Date String" & #"to Date String" & "&ignore=.csv"),[Delimiter=",", Encoding=1252]), #"Source Headers" = Table. Transform Column Types(#"Source Headers","Date", type date}, {"Open", type number}, {"High", type number}, {"Low", type number}, {"Close", type number}, {"Volume", Int64.After installing you should get a set of new buttons like this. This will return the latest quote for the stock CPU. Type}, {"Adj Close", type number) in #"Typed" in historical First thing to note is the code structure now has a query in a query.

The New Query button replaces the previous Get External Data features of Excel and is the entry point to load data into the Power Query environment. AX with a number of fields identified by the f parameter. The outer query defines a function which injects some variables into the inner query.

Yahoo Finance have kindly exposed a number of APIs for requesting stock price information (if used for non-commercial purposes), current and historical for just about every instrument you can think of. AX&a=00&b=4&c=2014&d=07&e=01&f=2015&g=d&ignore=This will return historical prices between two dates. Both APIs are very well documented (counter intuitively) at Google Code Pulling this data into Power Pivot is really easy from which it’s even easier to post process and report. The New Query button has a huge number of different data sources. We’ve parameterised the stock symbol, and the number of days of history.

These APIs are simple web queries but predate the REST API conventions so don’t follow nice RESTful best practice. For this purpose, we’ll use simply “Web” and import the historical data service by pasting in the above URL. AX&a=00&b=4&c=2014&d=07&e=01&f=2015&g=d&ignore=.csv"),[Delimiter=",", Encoding=1252]), #"First Row as Header" = Table. Transform Column Types(#"First Row as Header","Date", type date}, {"Open", type number}, {"High", type number}, {"Low", type number}, {"Close", type number}, {"Volume", Int64. We also get to use some of the useful M library functions as defined in here Power Query Formula Library Specification to manipulate the dates.

This will query the service, display the data and launch the Power Query editor. Type}, {"Adj Close", type number) in #"Changed Type" Ah, now we get our first glimpse of M. Table to insert a table with two columns named Symbol and Days and name the table “Historical Parameters”. Move the Excel cursor down a few Cells to a clear area on the Worksheet.

Here’s our first glimpse of the new data staging area. The Web import wizard created a set of M code that queried the URL, determined the type of data returned (csv), determined the first row is headers and had a guess at the column types of the data and returned that data as a Table. Note we have just created an Excel Table which is different to a Power Query Table, although you can use a Power Query Table to load data into and read data from an Excel Table (confused yet? Then New Query= This will take the Historical Parameters table we created in Excel, pull out the data from the Symbol and Days columns. Close and Load that query into an Excel table called Historical.

There’s a whole lot of buttons here for transforming and massaging the returned data and everything that is done with the buttons in the GUI become M statements in an M query which can be a great way to learn the language. Breaking down the code: Now choose Close and Load To…. Year(from Date)), #"to Date String" = "&d=" & Text. I put both the Historical and the Historical Parameters tables on the same Worksheet so you can update the Symbol and the Days and see the result. To get the query to run with new data either hit the Data Refresh button in Excel or Right Click and Refresh on the Historical table.

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