Alex Whittles
Alex is a Data Platform MVP, and is the owner and principle consultant at Purple Frog, a Microsoft Data Analytics consultancy in the UK with multinational clients in a variety of sectors. He specialises in all aspects of data warehousing, ETL, cubes, Machine Learning and Power BI using the Microsoft stack.
Alex is also the creator of Power BI Sentinel, a governance and disaster recovery tool for Power BI.
Alex has an MSc in Business Intelligence, is a chartered engineer, is on the organising committee for SQLBits, and leader of the Birmingham Data Platform Group. Alex is also a regular speaker at many Data events around the world including SQL Bits, Data Relay, Data Saturdays, Data Grillen, 24 HOP and the PASS Summit.
In his spare time he's also a qualified pilot.
Alex Whittles's Training Days
Business Intelligence in AzureSQLBits 2018
Learn how to architect hybrid business intelligence solutions using Microsoft Azure, including batch and real time data, small and big data, structured and unstructured data, using all the tools Azure has to offer.
Alex Whittles's Sessions
Prepare for Fabric with Power BI Governance, Auditing and DRSQLBits 2024
With the introduction of Microsoft Fabric, taking control of your rapidly growing Power BI estate provides an ever-increasing challenge. In this session we’ll look at how we can monitor activity, structure Power BI and Fabric for better management, and increase transparency. This will cover native Power BI functionality, additional Microsoft tools, as well as Power BI Sentinel.
SQLBits 2024 Opening KeynoteSQLBits 2024
The Opening Keynote
Power BI Calculation GroupsSQLBits 2022
Level up your Power BI capability by using calculation groups to simplify time intelligence (WTD, MTD, etc) and more
Machine Learning and Power BISQLBits 2020
In this session we’ll look at what ML tools are available in the Power BI and Azure worlds, and how you go about using these in your Power BI reports
So what's this Machine Learning all about?SQLBits 2019
Machine Learning is a popular buzzword, but what does it actually look like, and how can we use it? This session will show a number of high level examples of using ML to do some useful and fun stuff, including training a model to play a game
An Introduction to Machine LearningSQLBits 2018
Learn how to build an Azure Machine Learning model, how to use, integrate and consume the model within other applications, and learn the basic principles and statistics concepts available in the different ML algorithms.
Using PowerBI and DAX to predict and win Fantasy F1SQLBits 2015
Using PowerQuery, PowerPivot, PowerView and DAX to model, analyse and win a Fantasy Formula 1 league. Guarantee yourself eternal glory as a braniac petrol head, and become a PowerBI and DAX pro in the process.
MDX 101SQLBits 2014
In this session we'll look at the structure and basics of MDX, the Multi Dimensional query eXpression language for querying Analysis Services OLAP cubes. We'll start at the beginning, so no previous experience necessary.
Data Modeling for Analysis Services CubesSQLBits 2013
In this session we’ll look at a number of different data scenarios and explore ways of remodelling the data to optimise it for cubes and MDX. Sometimes a small ETL change can have a dramatic impact on the cube's functionality and simplicity.
Loading Data Warehouse Dimensions in SSISSQLBits 2012
This session looks at some of the different methods available to load slowly changing dimension data into a data warehouse, and compares the relative performance given different data scenarios and traditional storage compared with FusionIO
Automating SSAS cube documentation using SSRS, DMV and Spatial DataSQLBits 2011
This session will show how to use DMVs (data management views) to query the OLAP cube structure, and then use SSRS to create a set of interactive reports including the BUS matrix, and using spatial data to generate automated star schemas.
PowerPivot and QlikView 101SQLBits 2011
How to get started with PowerPivot and QlikView. Covering how to combine data sources, common pitfalls, adding some calculation logic and building a basic dashboard.
We’ll walk through the same example on both systems and compare the results.