Chapter 1 - Power BI Launch and a Start Database

1.01 What we’re here for… (10 min.) Sample Lesson
1.02 Installation and First Visualization (12 min.)
1.03 Five Minutes to Wow on an ARIES database (14 min.)
1.04 Customizing a Single Graph (8 min.)
1.05 Multi-Visualization Reports (17 min.)
1.06 Basic DAX and Modifying Data Connections, and The Service (14 min.)

Chapter 2 - Visualizations That Even a Landman Could Love

2.01 Deep Dive on the Front End (17 min.)
2.02 Lease Data and Moving Farther Upstream (10 min.)
2.03 Table Table (13 min.)
2.04 Matrix Tricks (8 min.)
2.05 Slicer City (13 min.)
2.06 Intro to DAX (19 min.)

Chapter 3 - Time Series Data for Fun and Profit

3.01 Data Janitorial Work in Power Query (23 min.)
3.02 Scattergories (21 min.)
3.03 Line Dancing (14 min.)
3.04 DAX for Production Calcs (18 min.)
3.05 DAX for Cumulatives and Finishing our Dashboard (26 min.)

Chapter 4 - Making Tables Your CEO Will Actually Read

4.01 Importing Data and the Date Hierarchy (19 min.)
4.02 OPEX Dashboard and Data Model Schemas (20 min.)
4.03 Vendor Coding and Drill Through Tables (19 min.)
4.04 Basic LOS and BYO Date Tables (28 min.)

Chapter 5 - Power BI Infrastructure and Architecture

5.01 The 31 Flavors of Power BI (16 min.)
5.02 The Power Platform Multiverse (12 min.)
5.03 Languages and the Service (17 min.)
5.04 Useful Resources (13 min.)

PowerBI For Oil & Gas / Chapter 1 - Power BI Launch and a Start Database

Lesson 1.01 What we’re here for…

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Transcript

01. Lesson 1.01: What we’re here for…02. Are you in the right class?!03. Chapter Outline 04. Chapter Outline (continued)05. BI Tools - Trend and Context 06. What do we mean by BI?07. Strengths for Power BI 08. Our Approach for this Class 09. Who we are

01. Lesson 1.01: What we’re here for…

Welcome! I'm Zack Warren with Velocity Insight. This is Power BI for Oil and Gas Lesson 1.01, What we're here for.

02. Are you in the right class?!

The first question, the most important question, are you in the right class? This is the right class for you if you want to use Power BI with oil and gas data. We'll teach skills you could certainly use in any other industry, but we'll do so using oil and gas data sets that will probably look familiar if you have experience in the industry.
Second, if you have intermediate or better skills with something like Excel or Spotfire, you certainly don't need to be an expert in those tools, but if you're already comfortable with formulas and graphs, then this class will go more easily for you.
And if you are beginner-to-intermediate level with Power BI, if you're expecting one of these guys to be your teacher, you're in the wrong class and frankly, you're probably in the wrong decade.
The chapters that we've designed are intended to be independent of each other. The lessons inside the chapters are dependent on each other, but you could skip to a future chapter if it's got material that's more relevant if you're already an intermediate or potentially even an advanced user.

03. Chapter Outline

So what do we mean by those chapters? Chapter 1: Power BI Launch and a Starter Database. We'll install the software, get things configured, and get you to your first visualizations.
Chapter 2: Visualizations That Even a Landman Could Love; matrixes, slicers, basic DAX formulas. We use a well list and a pretty typical lease list from the Bakken.
Chapter 3: Time Series Data for Fun and Profit. We'll have lots of new visualization types. We'll use a daily production and pressure dataset for that one.
And Chapter 4: Making Tables Your CEO Will Actually Read. We use an accounting dataset to demonstrate a really important concept of time intelligence and get you towards building a basic profit and loss statement.
Chapter 5 is a really useful one, even if you're not in, let's say, an IT or governance role. The Power BI infrastructure and architecture is really important to know about because Microsoft has built this whole ecosystem of different things around Power BI and understanding how those fit together is really useful to you as you reach more intermediate and advanced levels.

04. Chapter Outline (continued)

Chapter 6 and beyond: we'll have a deeper dive on DAX, we'll spend some time with Power Query, the mapping capabilities, predictive analytics like using Python or R scripts from inside of Power BI, paginated reports, enterprise Power BI governance for dummies. Doesn't that lecture sound exciting?
This will all build you up to the point where you can really achieve whatever it is you need to achieve from your career perspective and also in terms of your own business objectives.

05. BI Tools - Trend and Context

So business intelligence tools, what are the trends of these? What context are we in? Excel is far and away the world's most popular business intelligence tool. I think somebody first said that intending it as a joke, but it's totally true. There are hundreds of millions of Excel users out there, and none of the so-called modern business intelligence tools are anywhere close to that.
In late 2000s, Spotfire and Tableau and a number of other tools started to shake up that game. They built tools that were more source agnostic, that had more power and flexibility, better visualizations, and started to really eat into Microsoft's market share and the dominance of Excel across all kinds of reporting functions.
It took a little while, but eventually Microsoft clearly decided they weren't OK with that. And in 2015, they released Power BI. Since then, they've invested an enormous amount of money into building out the tool. You can see here on the Gartner survey, they show Microsoft as being far and away the leader for analytics and business intelligence platforms from sort of an industry-agnostic perspective.
I've also highlighted Tableau and TIBCO software, which makes Spotfire on this plot. Both of those have a lot of strengths and I personally have about a decade of experience with Spotfire. I really like Spotfire. There's still things that I prefer doing there to doing in Power BI. But if you look in the big picture in terms of price and performance and capability, I think it's pretty clear that Microsoft is in a very strong position to win this category.

06. What do we mean by BI?

So what do we mean by a business intelligence tool? BI tools have a lot of different use cases. That starts with data discovery. A lot of engineers and geoscientists will be familiar with this. You're cracking open a dataset, starting to look for some initial trends and maybe start to make initial conclusions about what's happening in that dataset.
The second big piece is reporting. I need to show my manager or my chief executives or maybe some peers in another department what we produced yesterday or how much money we spent last month. Those reporting functions are a really common use case for business intelligence tools.
The final is what I would call predictive analytics. What's going to happen tomorrow? What's going to happen next month? These predictions might be simplistic averages to predict the future. It might be AI or or a Python or an R script or something along those lines. The reason all of these different use cases interact with each other is because they require the same underlying capabilities of the tool. You've got to be able to connect to a lot of different sources, mix and match those so that they can provide the information that you need. Display results out to a user in a clean, easy to read, understandable, secure, well-governed format. And all of those different use cases end up requiring the same tools under the hood. And the more deeply you invest in one of those, the more the different use cases help each other out.
These use cases also have a lot of different users with different needs. You have engineers and geoscientists, landman, executives. They come to the table with a wide range of software and technology skills and they're often consuming the information that comes out of a BI tool in a lot of different formats. It might be on their smartphone when they roll out of bed in the morning, it might be in an emailed PDF or something like that. So BI tools end up having a lot of capabilities built into them. You probably won't need, I guarantee you won't need to know everything about what Power BI can do. I don't need to know all of it. The point is that there is an enormous set of capabilities and so there are portions of this class that might not be super relevant to you and then there's other portions that'll hit you exactly where you need.

07. Strengths for Power BI

Some particular strengths for Power BI in the marketplace: #1 it's really built to be a bridge between on-premises Excel and Azure up into the cloud. It works as having a really rapid learning curve for Excel users. The formulas and the programming language basically that is inside of Power BI is very, very similar to what you're used to working with if you're coming from Excel. And it also really queues organizations and individuals up for publishing things to the cloud and for getting comfortable with cloud security and the way that works. Microsoft has built particularly tight ties with Azure, but it is cloud-agnostic. You can also leverage AWS, Google Cloud, and other platforms to be able to ingest data into Power BI and report on it.
The second big strength is that it's very IT-friendly. It uses Active Directory and Microsoft's multi-factor authentication, so IT departments are pretty comfortable with the security side of it. Things like the mobile app basically don't require any setup at all. And this really matters for the soft costs, the total cost of ownership for something like Spotfire.
But the hard costs are also really appealing. The Desktop version that we're going to focus on in this class is free. The Pro version for web and mobile use is only $10 a user a month. And for a lot of organizations, it's also free because they already have Office 365 E5 licenses. The Premium version, which has a lot of extra stuff we'll talk about later like deployment pipelines and paginated reports, is only another $10 a user a month. So the total cost of ownership for Power BI is often 1/5 or even 1/10 the price of the competitors. That's a really big deal, especially when you're talking about large headcounts.

08. Our Approach for this Class

So our approach for this class is a mix of "tell", "show", and "do". The more "do" that you do, the faster you'll learn and the more permanently you'll learn, but you can certainly sit back and passively watch and listen to my dad jokes. You'll take home some real PBIX files, that's the extension for the desktop files, that work based on the public or anonymized datasets that we use here. And in the process of learning to build those PBIX files, you'll probably develop all the skills you would need to be able to build a similar set of reports on top of your own proprietary datasets. But most importantly, you'll have a lot of ideas about where to go next. You'll have examples of ways to get things done. You'll be aware of resources that can help take you to wherever you're trying to get in terms of your capabilities.

09. Who we are

So who are we? Velocity Insight is a full-stack, full-function data management and analytics consulting firm. We really help E&P companies and groups like that because we've got a lot of background with oil and gas. All of our people have 10+ years of experience, both with the legacy oil and gas tools as well as the more modern stuff like Power BI.
I'm Zack Warren. I'm a reservoir engineer by background, and a few years ago I moved into more of a data analytics role and really enjoyed it. So I formed this firm in the spring of 2021 and I'm really excited to bring this class to SAGA Wisdom. Thanks so much. I'll see you in Lesson 1.02.
Velocity Insight 2021 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms