So let's assume your data has been preprocessed and is ready for analysis.
It is not raw anymore.
It is beautifully organized and as you go through it you can understand the information each entry conveys.
Great well dear analyst This means you are ready to enter the realm of business intelligence.
This is the point where all your data skills combine with your business knowledge and intuition to explain
the past performance of your company.
With Conviction you would confidently be able to answer questions such as what happened when did it
happen.
How many units did we sell in which region did we sell the most goods.
And many more.
A good business intelligence analyst does not look at a problem from only one angle.
She will be able to extract any and all information required to solve this problem.
She will be capable of answering simple questions from our manager.
Like what's the news regarding our e-mail marketing as well as more complex ones like how did our e-mail
marketing perform last quarter in terms of click through rates and revenue generated.
And how does that compare to the performance in the same quarter of last year.
The job of a business intelligence analyst is an important and interesting one.
It is a job that requires her to understand the essence of a business and strengthen that business through
the power of data.
Amazing.
Let's look at be-I from a technical viewpoint now.
And while we're at it let's introduce some relevant be-I terms.
OK so how do we measure business performance.
We start by collecting observations.
For instance you can observe variables such as sales volume or new customers who have enrolled in your
web site.
Each monthly revenue or each customer is considered a single observation.
This is all great.
However no mathematical manipulations can be applied to these observations.
What we must do is quantify that information.
Quantification is the process of representing observations as numbers.
For instance you can say your revenues from new customers for January February and March were 100 120
and $130 respectively while the corresponding number of new customers for the same three months or 10
15 and 25 fantastic Next let's discuss measure.
A measure is the accumulation of observations to show some information.
For example if you total the revenues of all three months to obtain the value of $350 that would be
a measure of the revenue of the first quarter of that year.
Similarly add together the number of new customers for the same period 50 and you have another measure
great now.
Are there other frequently used terms.
Do you know what a metric is a metric refers to a value that derives from the measures you obtain and
aims at gauging business performance or progress to compare.
If a measure is related to something like simple descriptive statistics of past performance a metric
has a business meaning attached.
Let's exemplify this.
If you estimate the average quarterly revenue per new customer which equals 350 divided by 50 that is
$7.
This is a metric.
Once again it is not just a number but a number that bears a business meaning metrics are very useful
for comparisons.
For instance you can track the average quarterly revenue per new customer every three months and thus
compare your customer retention and spending every quarter.
In a nutshell your observations lead to measures and your measures are used to create your metrics your
metrics have business applications.
Nice.
This is all fine.
However in a real business where the number of observations is significantly larger you can derive hundreds
or sometimes even thousands of metrics can we keep track of all possible metrics we can extract from
a data set.
Probably yes.
Does it make sense to do that.
No.
What you need to do is choose the metrics that are tightly aligned with your business objectives.
These metrics are called K.P. eyes Key Performance Indicators key because they are related to your main
business goals.
Performance because they show how successfully you have performed within a specified time frame and
indicators because their values or metrics that indicate something related to your business performance.
For instance a metric could indicate the traffic of a page from your Web site that was visited by any
type of user a KPI instead would show the volume of the same traffic however generated only from users
who have clicked on the link provided in your ad campaign thus you could check if the ads you have sent
are a source of motivation for your customers to click on the provided link and get to the specified
page of your website which will determine whether you will continue to spend on ads or not.
Awesome examining measures and calculating metrics and eyes are not the sole rules of the business intelligence
analyst.
Every quantitative meaning you can extract must be visualized.
General managers will want dashboards and reports with graphs diagrams maps and other easily digestible
visuals supported by the most relevant numbers.
Filtering out the boring metrics and turning the interesting and informative eyes into a easily understood
and comparable visualisations is an important part of the business intelligence analysts job.
Often dashboards are created about K.P. eyes only KPI dashboards looks similar to the ones containing
metrics.
However they allow executives and managers to stay focused on the main business objectives.
Of course you will learn how to create such dashboards are all on your own.
Later in the program this was all we have to say about business intelligence for the time being.
Thank you for watching.