Don't panic, just breathe

Anxiety in the workplace is a serious problem. When we are highly stressed, the part of our brain responsible for rational thinking is impaired which makes it difficult to regain control. Simple breathing techniques can help you gain some mastery over your mind and help you gain control, such as preparing for a presentation!

How does this work? Changing the rhythm of your breath can signal relaxation, slowing your heart rate and stimulating the vagus nerve, which runs from the brain stem to the abdomen, and is part of the parasympathetic nervous system, which is responsible for the body’s “rest and digest” activities (in contrast to the sympathetic nervous system, which regulates many of our “fight or flight” responses).

Triggering your parasympathetic nervous system helps you start to calm down. You feel better. And your ability to think rationally returns.

Taking the Fear out of Tabular Editor

There is a lot of talk about how as a professional Power BI developer, you should use Tabular Editor. Yet when you open it, it’s daunting. Where do you start, what do these buttons do, how long is it going to take for me to learn this, is it really worth it?

In this session, we will run through the core components of Tabular Editor in normal non programming language. We look at how you can utilise this software to save you time in working with Power BI.

Session Objectives:

- Understand the Tabular Editor 3 interface and its various elements
- Learn how to use Tabular Editor 3 to create and manage Tabular models
- Learn how to use key features of Tabular Editor 3, including the formula bar, expression editor, and DAX functions
- Understand how Tabular Editor 3 can be integrated with Microsoft Analysis Services and Power BI.

Session Plan:

Introduction:

- Brief overview of the session
- Introduce Tabular Editor 3 and its key features and functionalities

Tabular Editor 3 Interface:

- Demonstrate the Tabular Editor 3 interface and its various elements, including the tree view, formula bar, property grid, and expression editor
- Explain how to use the interface to create and manage Tabular models

Creating and Managing Tabular Models:

- Demonstrate how to create a new Tabular model using Tabular Editor 3
- Explain how to add tables, columns, and relationships to the model
- Discuss best practices for organizing and managing models

Using Key Features of Tabular Editor 3:

- Demonstrate how to use the formula bar and expression editor to create and edit DAX expressions
- Explain how to use key DAX functions, such as CALCULATE, SUMX, and AVERAGE
- Discuss other key features, such as the script editor, perspectives, and translations

Integration with Analysis Services and Power BI:

- Explain how Tabular Editor 3 can be integrated with Microsoft Analysis Services and Power BI
- Discuss the benefits of using Tabular Editor 3 with Analysis Services and Power BI
- Demonstrate how to use Tabular Editor 3 to deploy and manage Tabular models in Analysis Services and Power BI

Conclusion:

- Recap key points covered in the session
- Provide resources for further learning and exploration, such as documentation and online communities.

(50 mins)

Key Data Structures for Optimal Model Performance in Power BI

Recognise the key basic concepts behind different types of data
Understand the importance of data types
Learn how to effectively model data within Power BI
Understand what is meant by normalised data
The importance of a Star Schema
How the engine works

Take off with Tabular Editor

A fast paced session showing several quick wins on how to use Tabular Editor to speed up delivery.
We will cover creating measures, batch editing and renaming, copying and pasting objects, formatting, folder management, Best Practise Analyzer and an example of C# scripting and automation.
This session will show you how to use Tabular Editor to work with your model and enable you to take off and fly smoothly away.

20 minute session. All features will be suitable for Tabular Editor 2 and Tabular Editor 3. This session is a condensed version of a series of presentations delivered at Data Relay, at various User Groups, at Data Weekender and validated in front of Daniel Otykier.

Power BI, Excel and Paginated Reports – better together

Speaker Submission: Meeting Diverse Reporting Needs with Excel, Power BI, and Paginated Reports

Introduction:
In today's data-driven world, it's no secret that effective reporting is essential for successful decision-making. However, not all users have the same reporting preferences. Some prefer Excel, others prefer Power BI, and some require printed versions of the data. The good news is that recent updates to Excel, Power BI, and Paginated Reports allow for more integration and flexibility in meeting these reporting needs.

In this session, we will explore different ways to leverage the strengths of Excel, Power BI, and Paginated Reports to create powerful and insightful reporting solutions that cater to all users' needs.

Key Takeaways:

1. Understanding the strengths of Excel, Power BI, and Paginated Reports
We will begin by examining the unique features and benefits of each tool. Excel is a versatile and widely used tool for data analysis, while Power BI provides robust data visualization and exploration capabilities. Paginated Reports are optimized for printing and generating PDFs, making them ideal for users who require printed versions of the data.

2. Combining the strengths of Excel, Power BI, and Paginated Reports
By combining the strengths of these tools, we can create more powerful and insightful reporting solutions. For example, we can use Power BI datasets to create dynamic Excel files that offer different reporting capabilities. This approach ensures that users can access the same data in a format that suits their individual preferences. We will also show how these different reports can be combined within an App to allow easy access to each reporting method.

3. Creating dynamic Excel files using Power BI datasets
We will run through the step-by-step process of using Power BI datasets to create dynamic Excel files. This approach allows users to leverage the power of Power BI's data exploration and visualization capabilities while still accessing the data in a format that they are familiar with. This technique provides a significant advantage for users who require customized or ad hoc reports.

4. Leveraging Paginated Reports for printing and generating PDFs
We will also explore the benefits of using Paginated Reports for users who require printed versions of the data. Paginated Reports offer optimized layouts for printing and generating PDFs, making them ideal for users who need to distribute reports to stakeholders who require hard copies of the data. We will show how to build reports within the Power BI service and then how to customise in Report Builder.

Conclusion:

By combining the strengths of Excel, Power BI, and Paginated Reports, we can create more powerful and insightful reporting solutions that cater to all users' needs. Attendees of this session will leave with a comprehensive understanding of how to leverage the strengths of each tool to create effective reporting solutions that enable better decision-making.

Our goal is to provide attendees with the knowledge and tools they need to meet the diverse reporting needs of their organizations and stakeholders. Join us for an informative and engaging session that will help you take your reporting to the next level.

(50 mins) although can be scaled down to (20 mins)

Power BI dataflows to drive a Centre of Excellence

You try to compare reports to make a decision, only to find out that one report uses a financial year, another a calendar year.

Key measures are giving different results and quite frankly you’re not sure which is right and how to move forward.

In this session, we’ll discuss and create centralised dataflows that can be used throughout the organisation. Creating dataflows will use Power Query online and we’ll examine best practise when using Power Query to optimise speed.

We will look at Query Folding and examine what it is and when it is relevant. Key points to consider when designing queries. The session will also cover where the data is stored, security, refresh rates and possible complications.

(50 mins)

Query Folding

Query folding is a process in Power Query where the query engine tries to convert the user's query steps into a single optimized SQL statement that can be sent to the data source.

If the query engine can perform query folding successfully, it can reduce the amount of data that needs to be transferred over the network and improve the performance of the query.

It's worth noting that not all query steps can be folded, and some data sources may not support query folding at all. However, by understanding query folding and designing queries with query folding in mind, you can improve the performance and accuracy of your Power Query queries.

This session will demonstrate the key principles to enable query folding to happen and those that can reduce folding.

(50 mins)

Why I love Power Query

Power Query is a data transformation and data preparation tool developed by Microsoft. It is a part of the Microsoft Power BI suite and is also integrated into Microsoft Excel. Power Query allows you to connect to various data sources, transform and clean the data, and load it into Excel, Power BI, or other supported data analysis and reporting tools.

This session will show various tips and tricks for utilising Power Query when working with data that will save you time and make your reporting solutions more robust.

Cleaning and transforming data repetitively is boring. Doing it once and setting up a model that will do it for you is exciting and allows you to go on to more fun and insightful work. Life is too short to be doing boring data prep when Power Query will do it for you.

This session is aimed primarily at beginners and intermediate users of Power Query. Session duration can be varied according to allocated slot.

Soaring Through Data: An Intro to Python for Data Analysis

Take off on a data-driven journey with 'Soaring Through Data: An Intro to Python for Data Analysis.'

This 100-minute session is your pre-flight checklist for mastering Python's role in data analytics.
We'll start at the runway with the basics of Python syntax and programming constructs.
Ascend into the clouds as we explore essential data structures like lists and NumPy arrays.
Reach cruising altitude with the Pandas library, your cockpit for data manipulation. Navigate through data cleaning techniques and set your coordinates for basic yet powerful data analysis methods.
Finally, prepare for landing with a Q&A session, ensuring you're ready to pilot your own data projects.
Buckle up and prepare for takeoff into the world of Python for data analysis.

Target Audience - those attendees that are interested in understanding what Python is and how to use it.
The data set will be aviation themed.
This session hasn't been delivered previously, but in my previous life I've taught Python within the GCSE and A Level syllabus in the UK.

The session will be broken down into these areas:
Part 1: Introduction (10 mins)
• Brief on Python's importance in data analysis (3 mins)
• Agenda overview (2 mins)
• Required tools: Python, Jupyter Notebook (5 mins)
Part 2: Basics of Python (15 mins)
• Syntax, variables, and data types (5 mins)
• Control structures: loops, if-else (5 mins)
• Functions and libraries (5 mins)
Part 3: Data Structures (10 mins)
• Lists and dictionaries (5 mins)
• NumPy arrays (5 mins)
Part 4: Pandas Library (20 mins)
• DataFrames and Series (5 mins)
• Data import/export (5 mins)
• Basic operations: filter, sort, groupby (10 mins)
Part 5: Data Cleaning (15 mins)
• Handling missing data (5 mins)
• Data transformation (5 mins)
• Data visualization: Matplotlib/Seaborn basics (5 mins)
Part 6: Basic Analysis (15 mins)
• Descriptive statistics (5 mins)
• Correlation and basic inference (5 mins)
• Simple linear regression (5 mins)
Part 7: Q&A and Wrap-up (15 mins)
• Questions (10 mins)
• Summary and next steps (5 mins)

Jet-Setting with Data: Python for Quick Analysis

Fasten your seatbelts for a supersonic 50-minute ride through Python for data analysis with 'Jet-Setting with Data.' This session is your boarding pass to rapid data insights. From takeoff with Python basics to a smooth landing in basic data analysis, we've got your short-haul flight to data proficiency covered. No layovers—just direct flights to actionable skills.

A 50 minute session.
Target Audience - those attendees that are interested in understanding what Python is and how to use it.
The data set will be aviation themed.
This session hasn't been delivered previously, but in my previous life I've taught Python within the GCSE and A Level syllabus in the UK.

Session Plan
Part 1: Introduction (5 mins)
1. Quick pitch on Python and data analysis (2 mins)
2. Overview of the flight plan (3 mins)
Part 2: Python Basics (10 mins)
1. Syntax, variables, data types (3 mins)
2. Control structures: loops, if-else (3 mins)
3. Functions and libraries (4 mins)
Part 3: Pandas Library (15 mins)
1. DataFrames and Series (5 mins)
2. Data import/export (5 mins)
3. Basic operations: filter, sort (5 mins)
Part 4: Data Cleaning & Visualization (10 mins)
1. Handling missing data (3 mins)
2. Data transformation (2 mins)
3. Basic visualization with Matplotlib/Seaborn (5 mins)
Part 5: Wrap-up & Q&A (10 mins)
1. Quick analysis demo (5 mins)
2. Q&A and next steps (5 mins)

Python in a Flash: Data Analysis on the Fly"

In just 20 minutes, 'Python in a Flash' catapults you through the essentials of Python-based data analysis. This high-velocity session is designed for quick learning, skipping the fluff to focus on actionable skills. Perfect for those short on time but high on ambition.

20 minute session - broken down into:
Quick Intro (2 mins)
Python Essentials (5 mins)
Pandas Quick Dive (7 mins)
Fast-Track to Visualization (4 mins)
Wrap-up & Rapid Q&A (2 mins)