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Instructor: When it comes to connecting to
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and transforming data,
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the query editor is our cockpit.
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Now, in Power BI, from the Home tab,
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we've already seen that you can launch the Query Editor
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and that there's a lot going on here.
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We're gonna be spending most of our time in this section
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right here in the editor itself.
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But let's take a minute and break down
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the components of this interface.
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Right up there at the top,
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we've got our query editing tools.
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This is where we'll find a lot of the tools
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that we'll use to shape and transform our data.
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Right beneath that, you'll see this formula bar
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and it's got some unfamiliar code in there.
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This is called M Code, and I didn't actually write it.
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This is code that's automatically generated
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as you apply different procedures
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or transformation steps to your table.
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For those of you who are advanced Excel users,
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this is exactly what VBA does
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as it automatically generates Visual Basic code
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while you record a macro.
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Now, don't get nervous
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because you don't need to even know M Code
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to use the query editor.
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In fact, we're only gonna touch it a little bit
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in a lecture or two.
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But just know that you can write custom M code from scratch
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or you can edit the M code that's automatically
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been generated for you,
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but you don't need it in order to use all of the tools
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that we're going to cover in this section.
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All right, so on the left side of the query editor,
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we've got our queries pane that lists out
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all of our queries.
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Here you can see that I've got nine individual connections
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or data queries in place, and you can click through
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each query to see previews of your data.
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You can edit the properties, change the applied steps,
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basically any modifications that you wanna make
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to an existing query, you can do so here.
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As you select the individual queries,
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you'll see this data preview
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in the middle of the screen update.
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This is where we can spot check and QAR data
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and do things like change column types and update headers.
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On the right side, we've got our properties pane,
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and the most important thing to call out here
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is the table name.
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Now, it's really important to be strategic and clear
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with your table names right off the bat.
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One thing to keep in mind is that your table names
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should be human readable, like territory space lookup.
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Power BI doesn't really care about spaces in between words
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and doesn't require the use of underscores or camel case.
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So there's no need to create your table and column names
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like you would in a SQL or a relational database.
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Point here, just try and be strategic
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with your table names from the get-go.
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And then last, but certainly not least,
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the applied steps pane here in the low array.
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This is really powerful because what's happening here
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is that every time you make a change to your data,
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every time you apply some sort of shaping
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or transformation operator,
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Power BI will record an applied step using M code
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and add it to the list here.
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And what that means is that every time
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this connection is refreshed,
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Power BI will run through these same set of applied steps
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to shape and transform your data.
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And this is a fantastic way to automate data cleansing
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and ETL processes instead of having to manually
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run the same process over, and over, and over again
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each time you connect to the data.
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So the query editor really automates the process for you
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and you can see each transformation as an applied step.
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Perhaps one of the most meaningful things here
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is that none of this is actually set in stone.
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You can click on the X
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next to any of these individual steps to remove it.
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You can click through each of your applied steps
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to actually visually see the impact
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that it's having on your table,
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or you can click the gear icon to the right
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and modify the individual steps within this process.
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So moving on to the Query Editor tools
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I wanna just take another minute here
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and introduce the three primary tabs or categories.
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First, we've got our Home tab.
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This includes some general settings, data source settings,
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parameters, table properties, et cetera,
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as well as some of the most common table transformations.
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The next tab, the Transform tab
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includes additional tools
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that allows you to modify your existing columns.
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You can split our group columns,
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you can transpose your table, extract text, and much more.
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And then finally, the Add column tools
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actually create brand new columns within your table
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and you can define those new columns
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based on things like conditional rules,
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text operations calculations, data operators, et cetera.
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All right, so up next
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we're gonna actually get our hands dirty
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with some basic table transformations.
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