Newcastle Fabric User Group: Profit & Loss Semantic Models

Profitability is a key metric; any profits can be distributed back to shareholders (owners) either directly or indirectly. A profit and loss (P&L) statement answers high level questions - such as “what was net profit last year?” - and summarises key revenue (i.e., product revenue) and expense (i.e., Research & Development) items. Unlike static reports, a P&L semantic model contains the detail; this allows end-users to ask questions such as “what was R&D spending broken down by a particular research project, fiscal period, or legal entity?.” A semantic model also allows end-users to consume information using Copilot prompts, Power BI reports, or Pivot Tables and formulas in Excel.

In this session, we will go through:

*Why you should build an income statement semantic model
*How to use an accelerator to speed up development.
*The key questions you need to ask stakeholders.
*The challenges in building a P&L income statement.

London Business Analytics Group: Profit and Loss semantic models in PBI

Profitability is a key metric; any profits can be distributed back to shareholders (owners) either directly or indirectly. A profit and loss (P&L) statement answers high level questions - such as “what was net profit last year?” - and summarises key revenue (i.e., product revenue) and expense (i.e., Research & Development) items. Unlike static reports, a P&L semantic model contains the detail; this allows end-users to ask questions such as “what was R&D spending broken down by a particular research project, fiscal period, or legal entity?.” A semantic model also allows end-users to consume information using copilot prompts, Power BI reports, or Pivot Tables and formulas in Excel.
In this session, we will go through:
Why you should build an income statement semantic model.
How to use an accelerator to speed up development.
The key questions you need to ask stakeholders.
The challenges in building a P&L income statement.

M365 summit: Data Modelling Considerations for Financial Reporting

Manchester Fabric User Group: P&L semantic models in PBI

Profitability is a key metric; any profits can be distributed back to shareholders (owners) either directly or indirectly. A profit and loss (P&L) statement answers high level questions - such as “what was net profit last year?” - and summarises key revenue (i.e., product revenue) and expense (i.e., Research & Development) items. Unlike static reports, a P&L semantic model contains the detail; this allows end-users to ask questions such as “what was R&D spending broken down by a particular research project, fiscal period, or legal entity?.” A semantic model also allows end-users to consume information using copilot prompts, Power BI reports, or Pivot Tables and formulas in Excel.
In this session, we will go through:
Why you should build an income statement semantic model.
How to use an accelerator to speed up development.
The key questions you need to ask stakeholders.
The challenges in building a P&L income statement.

Income statement (P&L) Sankey diagram solution for Power BI demo

Demonstration of a sankey diagram solution for Power BI. Covered why we use a sankey diagram, how we prepare our data, and a sankey diagram example

London Reactor Meetup I Build Recap Special

Parts of a 4 person panel taking Q&A at the event.

Data Modelling and Financial Reporting in Power BI

In person meeting at the Microsoft Reactor London

Overview of why Data Modelling is the #1 critical skill you need to develop effective financial reports in Power BI. In this session, we’ll help you:
1) Understand what Data Modelling is and why the methodologies are crucial to effective financial reporting in BI
2) Gain a practical understanding of the key concepts that will help you build effective models
3) Explain common vernacular enabling you to collaborate with others on projects
4) Provide a base understanding from which you can build and explore more advanced concepts

The Billion row Power BI P&L with Chris Barber

Learn how to produce P&Ls using native Power BI for complex real-life scenarios. We'll cover how to speed up development by using accelerators; these enable us to overcome various challenges such as ragged hierarchies, mixed formatting in the same DAX expression and working with billons of rows of data .

After the session, you should understand:
• What you need to get started with a P&L solution
• Key modelling principles and concepts for flexible and scalable solutions
• How to use free accelerators to speed up your development

Power BI P&Ls: The Fundamentals

> Learn about the different challenges in producing P&L statements in Power BI
> Discover the modelling solution to overcome the challenges of creating P&L
> Learn how to use the 4 types of calculations in Power BI
> Build financial statements by formatting String Calculation Groups
> Understand the value of excel integration

Power Platform Finance Conference 2022

Introduction to financial statements and the challenges faced by organisations

Power BI Wireframing

Congratulations! You have lots of reports across your organisation and you are driving adoption. However, each of these reports has their own look and feel and users are confused when switching from one report to another. Moreover, some of the reports seem to overlap with others, presenting the same information in a slightly different way.

To combat the above, we can use wireframing to outline each report and give each one a specific purpose and direction. These wireframes can be reused across the organisation and evolve over time to provide a range of layouts which can be adopted when building solutions. This drives consistency and standards.

Power BI: Applying Row and Object Level Security to an Organisational Hierarchy

During this session, Chris Barber shows how to take an organisational hierarchy and apply security so each individual only sees the information for which they are authorised. This will follow the rules of the hierarchy so managers can see their direct and indirect reports at any level.

This is an updated session on the previous Row Level Security (RLS) with Hierarchies from last year in which we'll cover both RLS and the newer functionality of Object Level Security which became generally available earlier this year. As such, we'll be touching on Power BI but also some of the external tools including Tabular Editor and DAX studio.

South Coast Summit 2021 Sessionize Event

Power BI: The Cash Flow Statement

In this third instalment of financial reporting we will build the Cash Flow statement. This will be done using the Indirect Method (which is permissible under both IFRS and US GAPP) and as such an understanding of the previous sessions would be helpful - these are available at https://www.youtube.com/channel/UCfXiJFEcztTpMmEDT0I8cPg

The Cash Flows indirect method starts with Profit Before Income and Tax from the Income Statement and then adjusts for all the non-cash items from the Income Statement and Balance Sheet.

Power BI: The Balance Sheet

Chris Barber shows how to build out a balance sheet in Power BI. This key financial report shows what a company owns (Assets) and what it owes (Equity and Liabilities). Chris uses data modelling, DAX and data visualisation and, in just a few clicks, explores this balance sheet data in Excel.

This continues on from Chris's session on the income statement in February (video recording at https://youtu.be/SH4UX4fGU9A).

Power BI: Slowly Changing Dimensions Types 0,1 & 2

Presented Online to Switzerland Power BI user group

In Power BI we frequently "slice and dice" data using dimensions. For instance, the date dimension allows us to view data by "month", "quarter" or "year". However, dimensions are often fluid; they change over time. This includes products which are slightly refined or employees who move in and out of our business and across the organisational spectrum.
During this session we will use Power BI to explore how to handle these slowly changing dimensions, a key element of the Kimball methodology.

Power BI: The Income Statement

The income statement (P&L) can be a tricky report to build within Power BI and - as such - there is much conflicting advice online about the best way to achieve this. In this session, Chris Barber will explain his preferred approach covering:

1) How to structure your data
2) How to create the data model
3) Using virtual relationships in DAX
4) Data Visualization

Chris will also show you how to create the report bridge. This allows you to easily explain variances and tell the data story about how you get from one value (budget / forecast) to the actuals.

Power BI: Ingesting Data using APIs

Being able to ingest clean and robust data into Power BI is fundamental to the success of any BI project. APIs are one of the key methods through which this can be achieved.

During this session we will demonstrate how to bring in data from the NASDAQ stock exchange including stock price, variations in expected earnings and data from the key financial statements including income statement, balance sheet and cash flow.

We will also demonstrate how you can utilise dataflows (and the Azure DL Gen 2 storage that sits behind it) to reduce the number of API calls made.

Basic Relationships in Power BI

Relationships are a core element of Power BI. In this introductory session we will explore the basics of relationships: how they work and why we use them. In doing so, we will cover:
• One-to-One;
• One-to-Many; and,
• Many-to-Many

We will also explore how relationships improve the user experience, resolve internal inconsistencies and reduce repetition of data.

Attendees based on number of sign ups - usually get circa 60% turn up.

Data Modelling: Slowly Changing Dimensions in Power BI

In Power BI we frequently "slice and dice" data using dimensions. For instance, the date dimension allows us to view data by "month", "quarter" or "year". However, dimensions are often fluid; they change over time. This includes products which are slightly refined or employees who move in and out of our business and across the organisational spectrum.

During this session we will use Power BI to explore how to handle these slowly changing dimensions; a key element of the Kimball methodology.

Row Level Security With Hierarchies in Power BI (Option 2)

During this session you will learn how to create reporting which enables everyone within your organisation to see only the information for which they are authorised.

The key benefits of this are:

Time saving - Maintenance of one set of data
Scale - The model is flexible as more individuals get added to the organisation
Secure - Leverages the current Microsoft infrastructure to maintain security by using the username of the logged in individual
Transparent - One set of data means that those who have the highest level of security can see exactly what everyone sees in the same report

We will be using a fictional hierarchy to create commission numbers for each individual, limiting them to see only their data and that of anyone who reports into them directly or indirectly.

Row Level Security With Hierarchies in Power BI (Option 1)

During this session you will learn how to create reporting which enables everyone within your organisation to see only the information for which they are authorised.

The key benefits of this are:

Time saving - Maintenance of one set of data
Scale - The model is flexible as more individuals get added to the organisation
Secure - Leverages the current Microsoft infrastructure to maintain security by using the username of the logged in individual
Transparent - One set of data means that those who have the highest level of security can see exactly what everyone sees in the same report

We will be using a fictional hierarchy to create commission numbers for each individual, limiting them to see only their data and that of anyone who reports into them directly or indirectly.

Visualising vaccination data in Power BI (Option 2)

During this session we examine a famous visualisation by the Wall Street Journal (http://graphics.wsj.com/infectious-diseases-and-vaccines/) and come up with an alternative approach in Power BI.

We will cover:
• Multiple Fact Tables
• Using a Junk Dimension in practice
• Creating dynamic confidence intervals

This is an intermediate session in Power BI covering the m language, data modelling,

Visualising vaccination data in Power BI (Option 1)

During this session we examine a famous visualisation by the Wall Street Journal (http://graphics.wsj.com/infectious-diseases-and-vaccines/) and come up with an alternative approach in Power BI.

We will cover:
• Multiple Fact Tables
• Using a Junk Dimension in practice
• Creating dynamic confidence intervals

This is an intermediate session in Power BI covering the m language, data modelling, DAX and the creation of dynamic confidence intervals.

Data Modelling: Disconnected Tables, Snowflake and Junk Dimensions (Option 2)

During this session we further investigate data modelling techniques. These are useful tools to have at your disposal when confronted with various reporting challenges.

We start with an overview of data modelling. We will then dive into 3 specific elements focusing on: 1) Disconnected Tables, 2) Snowflake Dimensions, and 3) Junk Dimensions.

Data Modelling: Disconnected Tables, Snowflake and Junk Dimensions (Option 1)

During this session we further investigate data modelling techniques. These are useful tools to have at your disposal when confronted with various reporting challenges.

We start with an overview of data modelling. We will then dive into 3 specific elements focusing on: 1) Disconnected Tables, 2) Snowflake Dimensions, and 3) Junk Dimensions.

Data Modelling: From single table to star schema

There is a broad range of skills you can choose to learn to enhance your report building capabilities in Power BI. These include DAX, M or even R and Python. Whilst these are all useful techniques, without appropriate data modelling you are likely to run into difficulties and challenges. These challenges may present themselves early on or latter down the line after you have deployed your solution.

We start with an overview of data modelling, looking at what data modelling is and why it is so important. We will then dive into 3 specific elements focusing on: 1) Star Schema Facts and Dimensions, 2) Role Playing Dimensions, and 3) Degenerate Dimensions.

Data Modelling: From single table to star schema

There is a broad range of skills you can choose to learn to enhance your report building capabilities in Power BI. These include DAX, M or even R and Python. Whilst these are all useful techniques, without appropriate data modelling you are likely to run into difficulties and challenges. These challenges may present themselves early on or latter down the line after you have deployed your solution.

We start with an overview of data modelling, looking at what data modelling is and why it is so important. We will then dive into 3 specific elements focusing on: 1) Star Schema Facts and Dimensions, 2) Role Playing Dimensions, and 3) Degenerate Dimensions.

Getting Started with Power BI

This event is suitable for beginners to Power BI. We will give a whirlwind tour of Power BI using a case study of a topical public dataset. We’ll demo how to import, analyse and visualise data with Power BI. We’ll make available all of the resources used in the demo after the session so that attendees can follow through and reproduce the demo in their own time.

This is the first of a series of events about analysing data in Power BI. In later sessions, we will build geographical maps, shape data so that it’s good state for visualisation, and explore case studies from football, the Titanic, financial share prices, politics, property sales, public health, and poverty in the UK.

Gathering data from APIs in Power BI

Gathering data from APIs is an effective time saving method to get up-to-date information. We’ll explore how to achieve this by pulling information from the Nasdaq stock market so you can track stocks in an automated way. Even if you don’t use stock market information, there is a plethora of data you can access via APIs and it’s an incredibly useful technique.

Whilst there is some relatively advanced m code - the code behind the query editor in Power BI, Excel and dataflows – we will walk you through this in a step-by-step manner.

Gathering data from APIs in Power BI

Gathering data from APIs is an effective time saving method to get up-to-date information. We’ll explore how to achieve this by pulling information from the Nasdaq stock market so you can track stocks in an automated way. Even if you don’t use stock market information, there is a plethora of data you can access via APIs and it’s an incredibly useful technique.

Whilst there is some relatively advanced m code - the code behind the query editor in Power BI, Excel and dataflows – we will walk you through this in a step-by-step manner.

Exploring the Human Development Index dataset with Power B

The Human Development Index (HDI) ranks countries in terms of life expectancy, education & income. We’ll analyse the HDI data with Power BI and solve a few data modelling and calculation challenges – for example the many-many problem (Armenia could be either Asia or Europe). We’ll also visualise the data, build a shape map and explain, for example, why changing the y-axis for scale is a bad idea and suggest other options to show the scale including conditional formatting.

Exploring the Human Development Index dataset with Power BI

The Human Development Index (HDI) ranks countries in terms of life expectancy, education & income. We’ll analyse the HDI data with Power BI and solve a few data modelling and calculation challenges – for example the many-many problem (Armenia could be either Asia or Europe). We’ll also visualise the data, build a shape map and explain, for example, why changing the y-axis for scale is a bad idea and suggest other options to show the scale including conditional formatting.

RLS with Hierarchies in Power BI

Finance and accounting teams deal with high volumes of sensitive and confidential information. Security within Power BI enables you to maintain a single source of the truth, but restrict that version of the truth to only those numbers each individual needs to see.

Scenarios include parent companies with their subsidiaries and affiliates, or travel costs rolling up from front line sales individuals to the CEO.

During this session we will run through an example looking at how commission calculations can be rolled up within the organisation whereby every individual has access to numbers which fall within their reporting line. This includes:

​1) Ingesting and transforming the data (M)
2) Writing the calculated columns and measures (DAX)
3) Building the data model
4) Please be aware this is an intermediate level session and you will need make sure you have a current version of Power BI