in this video I'm going to show you how to use data connectors in Google Data
studio to connect to and extract data from different tools. And then I'm gonna
show you how to use calculated fields to clean and transform your data before visualization
Hi this is Ahmad from Siavak with another lesson from Google
Data Studio essentials In previous lesson we saw that to create a chart we
need to connect it to a data source and to create the data source we need to use
a data connector in this lesson I'm going to show you how to create a data
source using the diverse range of data connectors that are available in Google
Data studio. We're going to take a look at dimensions and metrics different
field types and we will learn how to create a calculated field using data
studio functions let's go ahead and get started
let's create a new data source to create a data source we first need to select a
data connector here we can see a list of all the data connectors that are
available in data studio there are two types of data connectors Google
connectors and partner connectors Google connectors are built-in and free and
they allow us to connect to different products from Google like Google
Analytics Google sheets Google at Google search console or Google bigquery with
Google connectors we can also connect to my sequel database or simply upload a
CSV file for everything else to our partner connectors partner connectors
are created by third parties and are usually paid but they allow us to
connect to different tools such as Facebook Ads activecampaign AdRoll Adobe
Analytics Amazon Microsoft ads or many other tools and serums let's use the
Google Analytics connector to connect to the Google Analytics team account I'm
going to choose them account and choose the property in review and also at the
top give my data source a name and then click connect what just happened in a
background is that the data connector made a connection to the Google
Analytics demo account to create this data source this data source will stay
updated according to the data freshness so every 12 hours it will get fresh data
from the GA d'marco you can also click on it and set another interval for the
data freshness for example four hours so every four hours it will get new data
from the GM a data source can have many fields in this case we can see that this
Google Analytics data source has more than 500 fields there are two types of
fields in data studio dimensions and metrics dimensions are properties of
something and I used to describe data think of dimensions as categories of
Zeta the values within the dimensions are the titles or properties of a
category for example age is a dimension because it describes a property of a
user their age and it can be used to categorize users into different age
ranges similar to that seems like browser city campaign country page URL
device category or transaction ID these are all dimensions because they are used
to describe something about the user or a page or a session or a transaction
dimensions are usually in a string or text format but date is also a dimension
metrics however are numbers and are used to measure subject for example the
number of users the number of pageviews the number of transactions these are all
metrics on metrics because their numbers we can perform mathematical functions we
can sum them up we can calculate their average or their maximum or minimum each
field has a data type which shows what kind of data is a stored in that field
for example the data type for metrics can be numbers percentages or durations
in seconds a metric can also represent a currency such as US dollars euros or
British pounds dimensions however are mostly in the text format but they can
also be used to store values such as date and time or boolean which is true
or false or a geographic location such as a country or city or region apart
from the fields that are already in the data source like the ones that we see
here data studio also allows us to create new metrics and new dimensions
called calculated fields calculated fields retain a value by applying the
function to one or more existing fields in the data source so for example we can
do basic maths with metrics or manipulates these imagines let's see
some examples to create a calculated field we have to click on add a field
here and first give our field a name like my new field and then use a formula
to create our new field so for example I'd like to divide revenue by the number
of users to come up with a new metric a ratio that we can call revenue per user
it doesn't really make sense in this case but we can also multiply them or
sum them up or subtract them from each other an example of working with
dimensions would be to return the value of another field in the upper case or
lower case format let's take a look so we can use upper as the function and for
example put source medium in there so from now on this calculated field that
we created always returns the value of source medium but in upper case or we
can use lower instead to convert the value to lower case another example
would be to append the values of two dimensions together for that we can use
the function concatenate so for example we can join hostname to the page URL so
we can return the complete URL of the page data studio has many functions that
we can use to create these kind of calculated fields we can find a complete
list of these functions in the data studio documentation when we are happy
with our function you can click Save to save this calculated field from that
point forward this field will be available in our data source now that we
have created this data source we can always find it in the data sources tab
into data studio home and then we can click on it again to come back to the
screen and configure its settings we can use this data source in any report that
we create in the future or even on this screen we can click on the create report
button to create a new blank report which is connected to this data source
let's try so in this lesson we learn what are the different types of data
connectors in data studio and how we can use them to create data sources
that's it in the next lesson we learn how to configure the data and installed
properties of a chart to visualize data exactly the way we want it did you learn
anything new today feel free to test your knowledge by taking the quiz for
this lesson or continue to the next lesson you can find those links in the
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any questions please feel free to leave a comment looking forward to seeing you
in the next lesson