The capstone course, Design and Build a Data Warehouse for Business Intelligence Implementation, features a real-world case study that integrates your learning across all courses in the specialization. In response to business requirements presented in a case study, you’ll design and build a small data warehouse, create data integration workflows to refresh the warehouse, write SQL statements to support analytical and summary query requirements, and use the MicroStrategy business intelligence platform to create dashboards and visualizations. In the first part of the capstone course, you’ll be introduced to a medium-sized firm, learning about their data warehouse and business intelligence requirements and existing data sources. You’ll first architect a warehouse schema and dimensional model for a small data warehouse. You’ll then create data integration workflows using Pentaho Data Integration to refresh your data warehouse. Next, you’ll write SQL statements for analytical query requirements and create materialized views to support summary data management. Finally, you will use MicroStrategy OLAP capabilities to gain insights into your data warehouse. In the completed project, you’ll have built a small data warehouse containing a schema design, data integration workflows, analytical queries, materialized views, dashboards and visualizations that you’ll be proud to show to your current and prospective employers.
Executive Interview with Tyler Wilson on BI Platform Capabilities at CPI Card Group
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En provenance du cours de University of Colorado System
Design and Build a Data Warehouse for Business Intelligence Implementation
170 notes
University of Colorado System
170 notes
Cours 5 sur 5 dans Specialization Data Warehousing for Business Intelligence
À partir de la leçon
Data Visualization and Dashboard Design Requirements
Module 5 presents the data visualization and dashboard design requirements for the fourth part of the case study.
Rencontrer les enseignants
Michael ManninoAssociate Professor
Business School, University of Colorado Denver
Jahangir KarimiProfessor
Information Systems University of Colorado Denver
Welcome Taylor, to our executive interview today.
Thank you for agreeing to participate in this interview.
So far you have talked about various aspects of
the data warehouse design and implementation within CPI Card group.
The focus of this interview is the range of CBIKP ready as CPI Card group.
Let me start by asking you about CPI technical architecture.
In particular, would you comment on an issue of source systems and
services such as integration, data management, information delivery,
consumption, reporting analytics.
>> Yeah, so currently we're looking at
six different source systems that we consume data from in our BI tool.
>> Okay.
>> Each of those applications or source systems right now,
are all on premise applications.
Even though our BI tool or cross product is in the cloud, we actually take
the data sources transform the data and move it into the cloud.
>> I see.
>> We really don't have a lot of integration occurring between our source
systems that's really our next phase in the middle of what we're trying to do
as we develop the CPI.
>> All right.
>> So, what we have really encountered once we brought up our BI system and
really got a consolidated view on all of our data,
is a lot of the data management aspects that we have been looking at.
So historically, a lot of our data was managed in silos based on the application,
based on the department, based on the crew.
Now we're trying to take a broader stroke across the entire business and
have a true data management strategy.
>> I see. >> And that's really starting with us and
our BI application.
And we're driving it down through that way.
>> What about delivery and consumption reporting and analytics?
>> Yes, so historically,
each of our source systems would have their own reporting mechanism out of them.
>> I see.
>> Whether it was through some sort of Crystal Reports, or
some inherent reporting tool that the application came with.
Now we're driving to have single source for all of our reporting.
Which is driven through our BI platform.
>> Okay.
Thanks for sharing this.
Would you tell us how these services are used for predictive analytics,
data discovery, also for inner price reporting, dash-porting and
also event analytics and transaction monitoring.
>> Yeah, so at the moment we haven't really moved into the predictive analytics
face through our BI platform.
We do have other tools in place right now that forecast based of algorithms and
other things.
So we haven't made it to that stage yet.
>> Okay. >> I do predict,
probably sometime next year, we'll get to that stage with our environment.
What we're focused on right now is forecasting actuals based on historical
information.
Just simple views into the past.
We're also very focused on driving operations through our analytics platform.
So, we've actually increased the frequency of our data load so
now we're getting a more real time picture on really what's coming off of all of our
machines because that the root of our business we are manufacture and
that's what drives our entire business.
We've also put a lot of monitors in place, all the way from the front end processes
to make sure that the way that our people are actually
inputing data into the system, we're able to capture any mistakes up front.
And it really serves as a better process throughout the entire business, and
that's what we're focused on right now.
>> Okay, will you also comment how did CPIBI capabilities has
helped decision making, especially in achieving strategic,
tactical and operational goals?
>> Yeah, if you look at what I said earlier,
before we got into our analytics platform and
what we were driving, there wasn't really a single source of the truth.
We had multiple systems reporting multiple versions of the same things.
So we spent a lot of time trying to figure out data,
instead of looking at the information and solving problems.
I think the biggest issue that we've resolved is we now have a single
source of truth.
We're all looking at the same data.
Everybody from our customer care managers at our individual sites,
all the way up to our executives, are looking at the same data.
Whenever we start out, we build off of a single fact or
dimension, bring all of that together.
And we create different user for that for whichever position you are in the company.
So there is no discrepancy in what we're seeing.
That's been the number one issue that we've resolved across the business.
So now, all the leaders are able to focus on what the information is telling them
instead of trying to figure out what the data behind the information really means.
>> Absolutely, yeah, that makes sense.
Would you also comment on the process that's typically used for
designing dashboards and a score card for example.
>> Yep, so I think at the highest level we always focus on what the executives want
from a KPI and a strategic point of view.
>> Right.
>> That's always going to be a number one priority for all of us.
But I think at the heart and
soul what we're trying to do we build from the bottom up.
Across all of our locations,
we have a group of people that run the entire operations.
So we want those people to have access to the correct information at the right time.
So, our strategy has been to work with the core users of not only the BI platform,
but also the source systems to make sure we understand what's going on and
we're meeting their needs.
So that's our really process, we started that level and we build up.
That way we're speaking the same language to everybody across the entire business.
So we may start with an analysis that ends up in a spreadsheet that could be 15,
20 columns long.
And that rolls up into a visual representation
that our executives want to see.
>> Okay.
So requirement definition is done at the lower level.
>> At the lowest level that we can get.
>> Yes, it comes out, okay.
In regard to that also would you tell us regarding number of KPIs for example.
How you come up with the KPIs that you need to use and
also, any particular tools that you use to
actually come up with the number of KPIs and define your requirements.
Like tools like strategy mapping and
trying to figure out how the goals are related from one level to the next level.
>> Yeah, so corporately every year we set our goals for the entire business and
that cascades down to lower levels.
So essentially we start at our entire strategic level with a handful of goals,
probably four or five.
>> Okay. >> And that cascades down into our
different market segment so
we may look in our financial market versus our prepaid market versus our UK market.
And then out of each of those segments come different KPIs
that drive back up into our strategic goals.
We do have tools that we use that cascade those goals down, so all the way down to
my departmental level we have goals that roll up into the highest level of goals.
So overall our focus, specially for my side,
my team's side, is to make sure that every KPI and requirement that we get from
the lowest level of roles backup into a corporate and strategic goal.
We try to stay aligned with the business as much as possible and
I think that's where we add more value than a lot of IT areas in the past
where they are not really aligning directly to corporate or strategic goals.
>> I see. Talking about the values,
will you expand on that?
And so that's actually, how KPI is actually add values or
will add values especially in terms of customer segmentation for example,
customer profitability, fraud detection, issues like that.
>> Yeah so this year we actually had a big change, well when I say this year,
we're in 2016, in 2015 towards the third quarter we actually went public.
Whenever we went public, we actually had to realign our
business on what we reported, especially to Wall Street.
So, BI has actually allowed us to report and to give a view into those segments and
areas that we don't necessarily or didn't align to previously at our source systems.
So we're able to actually create hierarchies and
maintain different definitions on the same data at different levels.
And give that immediately to all of our decision makers
to see what our position is in the market at any point in time with any customer.
>> Okay.
That concludes our interview.
I want to sincerely thank you for coming here.
I'm sure you are experience at CPI.
I'm sure our learners appreciate that a lot.
>> Yeah. >> Thank you very much.
>> Thank you for having me.
>> Thank you.
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