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Infigo

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Insights utilizes
the Metabase platform to visualize

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and utilize your platform's data

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in its tutorial, we'll take a look
at creating a basic question.

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This is Metabase terminology
giving you the means to generate

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informational data reports
using intuitive tools.

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A basic example
we'll see is creating a question

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looking at the total value of orders
taken on a singular storefront

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over the past 30 days.

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Now, in order to be able
to utilize this functionality,

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you will need one of the higher levels
of Insights

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bands. So Infinite Insights

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Standard will not allow you
to create reports in this fashion.

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However, pro, pro plus and enterprise

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will allow you to do so.

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So within the actual Metabase platform itself, I'm

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going to go to the top right
click on new and then question

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it. From this point, we're

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actually just using this screen here
to choose to format,

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to refine the data that we want to use
and show it in the format

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that we find useful
for our particular needs.

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The first thing we need to do on here
is to pick our starting data.

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Now you have the ability to select
between two different things.

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One of them is the actual
Infigo platform.

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Now this is named training in my case,
and this is due to the name

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of my particular platform, which is
training.infigosoftware.com

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Yours will be named something different
or you can utilize the outputs

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of any previous saved questions.

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In our case, we're going to click

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on the main bulk of the data,
which is in my case, training,

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and then we're going to

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select the initial database
that we want to use.

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So in this example will only use data from

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one of the available provided data tables.

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However, as we'll see in later
tutorials, multiple

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data tables can be utilized
in a single question.

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In this example, we're looking for
the value of orders received

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so we can feasibly use

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the order dataset.

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You'll see that

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a few extra
things have appeared on our screen. Now.

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We do also within this data section
that we've just placed something in.

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We do have this arrow button next to it.

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This is not a mandatory step.

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However,
the arrow can be used to refine the fields

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that are displayed
on the eventual dataset.

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So without refining the selected fields,

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all data will be displayed by default.

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So we'll see data by default
for every single one of these columns

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for every single bit of data.

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However, for all we interested in certain
pieces of data, we can refine this down.

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So for example,

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I might only be interested in things
such as the total

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and the storefront ID

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so I could choose
whatever information I wanted from here.

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Now, the purple section that we've got
is filtering, and this allows

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us to create filters to narrow down
our answers to these questions.

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So it filters allowing you

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to refine the displayed dataset
and cut out unnecessary noise.

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For example, in this instance,
we will apply to filters

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filter one will display order information
for only one storefront on our platform.

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So we're not mixing information
from different storefronts

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and filter
to ensure that only order information

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from the previous
30 dates has been included.

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So let's start off

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by refining down to a singular storefront.

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First of all,

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what I want
to do is say add filters to narrow answer,

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and we're searching
for a relevant filter in here.

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So this is a relevant piece of information
that we want to filter by.

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Well, looking for storefront.

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So if I start searching for this,
we do have an ID here,

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which is storefront ID,

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and then we want to actually type

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in the data that we want to filter by.

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So how you can filter
this field will be controlled

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by the type of data contained within it.

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So for example, here
we have sort of a numerical I.D.

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and as a result,
we're able to enter values to filter

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and then control
how these values are used.

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The default usage,
for example, is this is icon here.

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This means that

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only values all of that chosen
ID will be shown.

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Alternative things in here
include things such as

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is not greater than less than.

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So we can refine down and filter

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the data based on any of those selections.

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Now, in this particular case,
I'm just refining that to one storefront,

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which I know as a storefront ID of 66

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Click enter

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and that's my filter input.

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Now for our second filter,
we wish to refine display dates

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and for this we're able to select
two fields such as created date

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within the order table

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so I could search for something

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like dates just to see any relevant

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particular

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associated fields.

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There's a few I can choose from
within the order table itself,

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and I can select
whichever one is most relevant to me.

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So I'll say created date

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now because it's

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recognized this as a date field,
it will give us inputs

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allowing us to specify the dates
we want to consider.

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Now, this can be as general as today

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could be last month
or it could be in the last year.

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Or we can cover a specific time
period and timeframes.

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So I could go for specific dates
or relative dates.

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For example,

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if I want to say it's
within the last month,

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I can click on that.

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And then if I click back on that data,
I've got some

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capabilities there of refining that

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last month information even more
So for example, it's saying at the moment

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that's the last one month that's giving me
the last complete month by default.

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So it's show me the 1st of October
to the 31st of October.

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In my case, however, I could, for example,
say encode this month if I wanted to.

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Alternatively, if I didn't want one month,

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I could change it to a different time
period

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current or I can do future dates as well

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if that's relevant to a particular search.

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if that's relevant to a particular search.

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So next we can actually start
to visualize this data.

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So the data covered
by the current question being asked

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can be viewed at any time
by clicking on the Visualize

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button at the bottom of this section.

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And what we can see in our example
is that based on our refinement of

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displayed columns and filtering of data,
we've got three columns available.

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One is showing us the order ID,

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one is showing us the relevant storefront
that ID is associated with,

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and because we place the filter of 66,
that's always showing us

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and we have the associated price as well.

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That's the data
that is currently utilizing.

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If we want to
apply some additional filtering to this,

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if that's not quite the information
we want, we can go back to the editor

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with this icon over on the top right
hand side.

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So what we might want to do next,
the data that we have there is showing us

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the so by showing us the price of all of
the individual orders in the last month,

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what we want in our particular case
is a total price of all of those orders.

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So we want all of those summed

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and we can do this using these summarize
functionality.

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So summarize allows you to display
existing data in a more condensed way.

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So for our case, for example,
we're looking to display one order price

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for the entire month instead of data on
each individual order that's being placed.

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If I click summarize,

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there's a few different means by
which I can summarize the particular data.

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And obviously your choice would depend on
what exactly you're looking for.

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And you can enter your own custom
expressions as well

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if you have the technical skills to do so.

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In this case,
I'm just going to say sum of

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and then it's giving us

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the ability
to select the information that we want to.

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So in our case, as we've mentioned,
we want the sum of all of those

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individual order totals.

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I can say some of total.

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Let's go ahead and click Visualize.

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Yes. Again,

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and then we can see
that our answer has now been obtained.

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So we're seeing just a singular value
which is combining all of those order

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total bits of data
that we saw on our previous table.

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This is now giving us our required data.

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The order total over the past 30 days.

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So now this
particular question has been complete.

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We want to save it for later use.

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So on the top right hand side,
I'm just going to go and click Save

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within entering a name

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for this particular data,
an optional description.

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And then we're specifying a location
on our account

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where we want to save this information.

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There's a few sections
which are associated

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with your particular platform,
or you can save it to your own

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personal collection.

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Now here you'll see

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we have the ability to add this
to one of our dashboards.

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The saved questions can immediately
be added to a dashboard,

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which is a collection
of different questions and other

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data that you wish
to make readily available for review.

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At this particular point,
we're going to click on

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Not Now as well,
create dashboards in a later tutorial,

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and that's it.

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That's our first basic question created.