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 James Gualke on the State of BI Maturity and Strategy at PDC Energy
Loading...
Из курса от партнера University of Colorado System
Design and Build a Data Warehouse for Business Intelligence Implementation
210 оценки
Посмотрите похожие видео
В Coursera собрались лучшие преподаватели мира. Вот несколько рекомендаций лично для вас:
University of Colorado System
210 оценки
Курс 5 из 5 — Specialization Data Warehousing for Business Intelligence
Из урока
Wrap Up and Project Submission
This is an extension of Module 5. The peer assessment from module 5 is moved to module 6 to give you more time completing the assignments in prior modules as well as for you to do your peer assessment in this module.
Познакомьтесь с преподавателями
Michael ManninoAssociate Professor
Business School, University of Colorado Denver
Jahangir KarimiProfessor
Information Systems University of Colorado Denver
Welcome to our final executive interview on BI Maturity and Strategy.
We are at CU Denver Business School's, JPMorgan Center for Commodities.
I am happy to introduce to you Mr. James Gaulke.
Mr. Gaulke is the Vice President of Information Technology at PDC Energy.
Welcome James.
>> Welcome.
>> Thank you very much for agreeing to participate in this interview today.
Just a quick overview PDC Energy is an exploration and
production company headquarter in Denver, Colorado.
It's operation includes production, development, exploration,
and marking of crude oil, natural gas, and natural gas liquids.
As EVP of information technology, James is responsible for establishing
the company's technical vision, and leading all aspects of its development.
James, as you know, Gartner's maturity model provides a framework for
assessing an enterprise beyond maturity and a strategy.
According to Gartner, the five maturity levels are called unaware,
opportunistic, standardized, enterprise, and transformative levels.
Let me start by asking you this, how would you classify
the set of BI maturity within PDC energy, and why?
>> I would call our cells in that standardized section of the model.
Right where I think we should be, not quite where I would want to be.
BI is a journey.
And that model really provides a roadmap for the journey that PDC
has gone through and that other companies are going to go through.
So we started out probably about three years ago in that unaware model or
unaware stage.
A lot of spreadsheets, a lot of individual analysts
that would combine data on spreadsheets, provide answers back to management.
>> Right. >> And a good example of the anarchy that
reigned throughout PDC at that time was we would have
meetings to discuss the results of those spreadsheets.
But, 35 to 40% of that meeting would be analyzing the numbers,
making sure they were correct.
Another 30% to 40% would be discussing the numbers, and
then maybe you were doing 10% to 20% action on them, and go forward.
We then started down the path of trying to standardize some of that into
departmental silos if you will, Microsoft Access.
Other database mechanisms where people could combine information and
use them across the department.
So you had groups of analysts within the departments that would share information,
but you still had meetings with the same results when you cross departments.
People would question the numbers, nobody was sure,
you'd go through rectification of those numbers.
>> Right. >> And
then you come back with maybe 20 to 30% of that meeting being actionable items.
With the standardized, the model we're in now we've got a standardized warehouse.
We have some data marks that are set up.
Our meetings are much more productive in terms
of having good conversations about numbers in the results.
>> Mm-hm.
>> I would love to get into that enterprise stage with enterprise metrics
and good established business owners and everything else.
But it's maturity curve, and
it's part of the maturity curve that PDC still has to go through.
>> So data being integrated, kind of centralized.
>> Yes. >> In terms of data marks and going up.
>> Correct, yeah, we have a warehouse now, we have our extract transformation,
load stages, we pull from our core applications.
So I've got my accounting.
I've got my financials.
I have my production in terms of how much oil I'm producing on a daily basis,
got my capital drilling programs.
And we're taking that and putting that all into a warehouse, and
then we're developing our marts based upon the different business processes or
business functions that the company goes through.
One being those financial results.
The other one being how much I'm producing.
But then I've also got marts that get into well management, and
what our basically customer would be from an oil and gas standpoint, that well and
information about it, both subsurface and surface information.
>> Thanks for sharing the state of maturity within PDC Energy.
What do you think the most important challenges for
PDC Energy to move, to more pervasive and more transformative.
>> Yeah, we're actually probably in an transition phase right now.
So we have executive management that is getting interested in the analytics and
the dashboards that we're producing.
So, we're trying to get away from the departmental dashboards, if you will, and
get into more cross company things, so good example is we're an oil and
gas company.
>> Right. >> We produce oil and gas,
production is a good number that we should be sharing back and forth and
that's one of the dashboards we're developing.
So that our field guys who are actually producing it, are seeing the same numbers
that our reserve guys who are interested in how much are coming out of the ground.
And the same that our CIO,
or C-suite, is actually seeing, are all lined, all the same.
So, for us to continue on it is that enterprise visibility.
>> Right. >> Right, and
it is somebody who sits in that senior management team, who actually can sponsor
that cross cultural aspect of the data and cross cultural aspect of the metrics.
There needs to be somebody who can, I hate to use the word referee, but
I can't think of a better one, when there's discrepancies between systems.
And discrepancies between the data that's being produced by those systems.
And they're not integrated to a point of having the same information.
Somebody who can look at it and say, okay, I own this, I will resolve it,
here's the way that we want to move forward with that particular member, and
then come up with what the results should be.
>> This leads very well to our next question.
Will you please also comment on the BI strategy within PDC Energy,
particularly in terms of the use of BI, strategic, tactical, and operational.
>> Yeah, sure.
So from a BI standpoint,
we didn't start out saying we wanted Business Intelligence.
>> Right. >> What we started out saying was we
had particular problems to solve.
And the first one that we had to solve was our expenses in producing the oil and
gas that come out of the ground.
So in our world, we call it our least operating expenses.
But how much is it costing me per barrel of oil at each one of my wells?
And the way we had our system set up, it was difficult to get that piece of
information, the way my operations guys wanted to see it.
There was definitely a lease operating expense report, the way the accountants
wanted to see it, but that didn't align with how the operations guys wanted it.
They wanted to understand not only the cost structures but be able to kind of
pull it apart by the pumpers that produce it, by the swab crews that went in,
by any of the different groups that actually touched and managed that well.
And, some of the things the accountants had in terms of this lease operating
expenses didn't necessarily agree with what the operations guys had because
there is travel time between wells, and you would consider it down time for
a pumper as he's in his truck driving from location to location.
>> Right. >> But our ops
guys wanted to see that heaven number associated with it.
So we started down let's solve that problem.
And that's what lead towards our data warehousing aspects and being able to
understand that in order to produce this I needed the financials from my ERP package.
I also needed some of my production information from my
field gathering package.
And I needed some information for my HR package in terms of who was playing, or
who was working in the fields, what the capabilities were, and everything else.
>> So you moved to a tactical.
>> Exactly, so that kind of helped us from a tactical standpoint,
to start combining information.
>> Yes.
>> And then having grown up in the retail world, I worked for
25 years in credit cards for a national retailer before getting into oil and gas.
I've learned the value of data.
Data for us on the retail side was real good in terms of, or
trying to anticipate consumer actions.
Spending patterns, those types of things.
And it's one of those if you know there is value in the data,
bring that over to the oil and gas world, right?
Which historically had not looked at technology as something that was
strategic.
It was a back office function, necessary to do it but
strategy was pulling resource out of the ground.
So at this whole process kind of helped us in terms of getting data standardized or
centralized.
And now it gave us a mechanism to add in data as we solve other problems.
So from some of the tactical aspects on it over the operational aspects,
Colorado is very big in environmental awareness.
And there are a lot of greenhouse gas emissions rules and
other items that Colorado has basically put forth, that the rest of nation looks
to as leaders in terms of environmental management of oil and gas wells.
For us producers, it requires a lot of reporting.
Understanding how equipment is functioning, what run rates are,
what burn rates are, and as we started solving that greenhouse gas reporting
issue, we also started capturing some of that surface information in our warehouse.
So again, not necessarily looking at the warehouse as something that I wanted to
build start to finish, but knowing I needed to do this incrementally
as we were solving different business problems.
I don't know if I could say that we have a strategic decision that has been made yet
with our Business Intelligence platform in our warehouse.
But that doesn't surprise me based on the capability model.
On that capability model, we're at that point in that model where I'm
just starting to get into- >> To the next-
>> Right, and having the strategic
information, right?
The business transformation processes,
the stuff that we do to continue to change what's happening from a business function.
>> Right. >> So right now,
I'm kind of stuck in the operational tactical, but
that's not a bad thing because I'm solving key business problems.
Helping PDC grow and helping PDC.
>> Absolutely, if you don't have a good view of operation or tactical,
you cannot be strategic.
>> Exactly, exactly, and the information that we provided, PDC has done many deals
throughout 2015 to reposition it for this downturn that we're seeing in 2016.
We have let go of non-profitable wells.
We have closed out non-profitable fields and we are focused in Colorado for
our growth because we know we can get oil and gas effectively out of the ground
based on the reports and based on the numbers that we were provided.
>> That's very impressive.
Thank you, thank you for that.
Would you also please comment on some of the business goals.
You mentioned some of them, but some of the more specific business goals
that drive discovery of the BI strategy within PDC.
>> Yeah, our business model is pretty simple right.
We want to be a low cost oil and gas producer.
>> Right. >> We want to continue growing in terms of
what we do and what we produce.
And we want to be safe.
And we want to make sure our employees go home at night.
>> Right. >> Right.
>> So I think through what we do from the Business Intelligence standpoint what
we've going after.
That growth aspect really translates into how much oil, how much gas am I producing.
>> Okay. >> And that's what I think helps
drive the overall aspects of the Business Intelligence site.
We drove down to that reporting deal and were very focused on the production
aspect, so that we can help ensure that management is talking
strategically about what they want to do in those fields and what they want to
do on the walls to keep the process going and to keep the business oriented.
We are starting to layer in now our EH&S, our environmental health and
safety information, that talks about employees and employee productivity.
So going back to the previous example of pumper drive time.
>> Right. >> Right.
We can track incidents in terms of safety or accidents, and
how many miles are actually being driven without accidents,
or how many instances per barrel of oil are being created.
Be it an environmental instance, be it a occupational hazard, in terms of somebody
accidentally cutting themself on a piece of equipment or something else.
So we've got those stats and we can show that the company's growing at a phenomenal
rate, but we're also reducing these incidences,
both on an environmental standpoint, so we are not spilling,
as well as occupational safety, so our employees are going home at night.
>> As you know, the BI framework is essential for enabling BI a strategy.
Would you please also comment on the BI framework
in terms of the technical architecture, data governance,
data integration, data security, and end-user information.
>> Yeah, it's all part of the maturity life cycle,
to answer a lot of those questions, right.
The easiest part to answer is the technical architecture.
>> Right.
>> PDC's a company with 365 employees.
IT is probably about 5% of that number.
So we want to stick on one technical architecture.
We want to be able to support all of the applications that PDC runs.
The obvious answer for us based on past investment was Microsoft.
So our entire BI strategy as well as our ERP function, as well as all of these
environmental health safety, production, everything else is all Microsoft based.
>> All, everything?
>> Exactly. So
we have standardized on Microsoft SQLs from a database stand point.
We're using the SSAS and RS packages to do our application integrations,
do our reporting and capabilities.
>> Okay. >> Makes it easier for
18 people to support a $800 million company, right?
With a little over 1.5 billion in market cap.
But to bring all those numbers together and keep us a strong company,
and allow us to leverage our resource, right?
I think in terms of what we do for the data governance, and the data aspect.
That's actually part of our material process.
>> Right. >> Right.
So, being in that standards center of the model, data governance is emerging for us.
We definitely have things in terms of data cleansing, and capabilities to look at
data and understand if my well names don't agree on systems, how do I fix that?
So that we can combine data back and forth, but in overall governance
architecture it's actually something that we're laying in right now.
Who owns it, who's on the committee in terms of delineating who has access
to it and that leads into the security aspect, you were talking about.
>> Right. That's right.
>> Right, because right now if you don't have the particular package that we need
in order to produce reports,
you don't really see them unless someone gives them to you.
Right, as we start going into self service BI and self service capabilities and
continue to eliminate spreadsheets, security becomes a lot more important.
>> Mm-hm. >> But not only security of the tool but
security of the data that you're allowed to see in your job role.
Because not everybody in the company should have unequivocal,
equal access to all data that the company possesses.
>> Right. >> Right, and
all those questions have to be designed and we're still kind of playing on that.
We're still kind of asking those questions of ourselves.
We've got very rudimentary aspects in place but it's all going to
continue to be built on the Microsoft tools in the Microsoft security aspects.
>> So do you find that easy to work with in your strategy?
I'm talking about the framework being flexible.
>> Yeah, without turning it into a Microsoft commercial, definitely, right.
It is something where given that decision it lends clarity to my developers
about what they can do.
>> Yes. >> And it lends clarity to the business
community about what tools we'll accept and what tools IT can support.
And it's probably less about acceptance and it's more about can we maintain it,
and can we support it, and can we function with it, right?
because that's the key for all these tools and capabilities.
>> Absolutely.
>> Yes, so for us coming through as a framework allows you to make coordinated
decisions for a lack of a better word and that decision process has actually helped
speed us along in terms of what we're adopting and what we're actually using.
>> Considering the BI frames what we just talked about, could you tell us,
actually you already pointed out, what are the most critical success factor for
implementing BI strategy within PDC Energy?
>> Yeah, I think you know for any company outside of PDC Energy as well,
the first is it's an understanding that BI is a process and it's a journey.
It's not going to be solved with one major investment.
Right, I like to look at it as it's a bunch of business problems that I'm
solving.
But with each one of those business problems that I'm trying to solve it's
additional capture and usage of data to go through.
For us to keep going down that journey and start getting into the enterprise zone and
actually getting into the transformative zone of the model.
It's going to be critical on us to start getting some true strong senior
management sponsorship.
Right now with CIO, I'm kind of sponsoring a lot of the sub development.
Garnering that the budget that we need,
the build out aspects, kind of working through the reporting deals.
But as we go through this, some of the management that is responsible for
cross enterprise metrics and reporting.
Are becoming aware of what we're giving, becoming aware of the numbers and
they're getting behind it, if you will.
And that emergence of a true sponsor is going to be critical
to getting into that next phase.
The data governance aspect is another one that we're going to need to kind of hit
that enterprise level.
Because part of that enterprise aspect is going across departments, right?
And trying to manage that void between the departmental silos and fill it in.
And it's critical to have senior management help you with that, and
be able to navigate through what's going on and what's happening.
Continued usage and belief of the data we put together is another key factor, right?
So people have to feel comfortable that the numbers that come
out of that warehouse are accurate.
They may not like the story the numbers are telling, the may not like
the interpretation of the numbers, but there's not a question about the number.
And there's not a question about the combination and/or
representation of that number be it, like we were talking about safety of employee,
barrels of oil, or something else, right?
The data is good, the data is sound.
People find value in it and carry it forth.
The other one I think is now that people believe that data is continue decisions
based on that data.
>> Right. >> Right,
one of the things in business is people talk about gut feel and
all that kind of good stuff.
And I'm not discounting that, but it's good to have you guys feel supplemented by
the information the data and everything else.
>> Is there a lot of training going on in order to actually develop that competence
center, BI competence center within the PDC Energy for the users to know.
What they are supposed to be looking at, and how do you supposed to change
their mental model in order to make decisions based on data.
>> Yeah, there is,
there's a lot in terms of what we're doing from an IT standpoint right now,
in terms of how you build warehouses, how you build the marts and all that.
The beauty of going with Microsoft is a lot of stuff looks very Excelish.
>> Right. >> Right, so
the users are familiar with the tools, because it has that Excel look and feel,
and it has that Excel standpoint.
The training really comes around, the numbers, how to get to it, and
then as we go down this self-service BI aspect, how to combine information
from the different marts together, they get the numbers that they're looking for.
The tough part is going to be a lot of the infrastructure that they have built
already on the manual process, with the spreadsheets and
extracts from systems in combination, they have a lot of faith in.
So some of it is prying the fingers off the old tools and
allowing them to gain trust and comfort in those new tools.
And that's probably when I was alluding, I was taking a little longer than I thought
initially, is where I underestimated what was happening from that aspect.
That concludes our interview, on behalf of the learners,
I really sincerely want to thank you for spending your time with us this afternoon.
I'm sure they enjoyed a lot, they learned a lot from your insight.
And that's a lesson their going to take with them wherever they go.
>> Well, you're welcome.
>> Thank you.
>> And thank you guys for paying attention and listening.
>> Thank you very much.
>> Thank you.
Ознакомьтесь с нашим каталогом
Присоединяйтесь бесплатно и получайте персонализированные рекомендации, обновления и предложения.
Coursera делает лучшее в мире образование доступным каждому, предлагая онлайн-курсы от ведущих университетов и организаций.
© Coursera Inc., 2019 Все права защищены.
