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  • Blog Post: Machine Learning for the Business Intelligence developer

    Amy (the other half of the data duo in our team) and I have been gate crashing the Data Culture series and other events recently to see who’s interested in Azure Machine Learning (MAML) . It turns out that data scientists are pretty comfortable using their own tools and scripts be that in R and Python...
  • Blog Post: Azure Machine Learning – General Availability

    Today Microsoft Azure Machine Learning (MAML)goes from preview to general availability and it’s also undergone quite a few changes on the way. Before I get into what’s new (and there is quite a lot) I do occasionally get feedback that Azure services are evolving too quickly for everyone to keep up. I...
  • Blog Post: How to train your MAML–Redux

    Since I wrote this series we have taken on two computer science graduates in the evangelism team in the UK, Amy Nicholson and Bianca Furtuna. Both studied machine learning as part of their courses so I introduced them to this series on Azure ML to get them up to speed. They have taken this series apart...
  • Blog Post: How to train your maml – Publishing your work

    Before I get into my next post you may have noticed that ML has changed compared with a few weeks ago -the main page previews experiments differently, and the visualization of data has also changed.. One other problem hit me and that was some of the parts of my demo experiment didn’t work or ran really...
  • Blog Post: Future Decoded – with Data Science

    If you have been following my posts on Microsoft’s approach to data science with things like Machine Learning you’ll realise that it’s capable of making predictions. However to be honest it’s not going to tell you what devices and career you’ll have in five years time. To do that you need expert humans...
  • Blog Post: How to train your MAML

    In this fourth post in my Azure Machine Learning series we are actually going to do the training itself. I have tidied up my experiment from last time to get rid of the modules to export data to SQL Azure as that has now served it’s purpose .. Before we get stuck into training there’s still a bit more...
  • Blog Post: How to train your MAML – Looking at the data in SQL Azure

    In my last post we saw how to clean, transform and join datasets. I also mentioned I had trouble doing the join at all and even now it’s not quite right so how can we look at the data and find out what’s going on. The visualisation option only shows a few rows of the 2 million in the dataset and there...
  • Blog Post: How to Train your MAML–Refining the data

    In my last post we looked at how to load data into Microsoft Azure Machine Learning using the browser based ML Studio. We also started to look at the data around predicting delayed flights and identified some problems with it and this post is all about getting the data into the right shape to ensure...
  • Blog Post: How to train your MAML – Importing data

    In my last post I split the process of using Microsoft Azure Machine Learning (MAML) down to four steps: Import the data Refine the data Build a model Put the model into production. Now I want to go deeper into each of these steps so that you can start to explore and evaluate how this might be useful...
  • Blog Post: Adventure Works!

    My title for this post is a pun on the Adventure Works databases, and samples that have been in SQL Server since I can remember. There were also some data mining examples ( as referenced in this old post ) but this has not really moved on since 2011 when I last wrote about it so you might be forgiven...
  • Blog Post: Cast and Convert

    In SQL server the Cast and Convert functions change one type of data to another. A pod cast is the art of converting knowledge into sounds so that's the tenuous link for this post. Pod casting is not something I have ever tried, but the security expert on our team, Steve Lamb sees himself as the next...
  • Blog Post: Integration, Integration, Integration

    Microsoft is all about choice, so instead of having one way of shifting data between two different platforms we have three.  I get asked about two of these a lot but I also wanted to discuss the latest tool in this space to make sense of all them and understand when to use what: Integration Services...
  • Blog Post: Are we spending too much time with Excel?

    Despite my love of SQL Server and my respect for Oracle, and MySQL the worlds number one database is excel.  I know that many purists and DBA’s will shudder at me grouping a spreadsheet with a database, but look at this form the perspective of number of hours of users using excel and the volume...
  • Blog Post: Lean and Mean

    When you build a cube in analysis services it is very easy to expose every attribute in every dimension to the user. You can also add-in every measure and if you don't feel that's enough then you can create your own calculated members to add to the users' fun. Once you have given the users every thing...
  • Blog Post: Grain - The devil is in the detail

    Technorati Tags: BI , Business Intelligence , OLAP , SQL server 2008 Business Intelligence is just like digital photography, the more detail you want the more space you are going to use and in both cases we talk about grain and granularity. If you have ever worked with RAW files on a 'Prosumer' (an IT...
  • Blog Post: One Version of the Truth

    One of the most over used phrases in Business Intelligence is "one version of the truth" so I thought it would be good to discuss why it's important and what IT professionals can do to achieve it. In an imaginary organisation like adventure works there would be several line of business systems such as...
  • Blog Post: Hierarchies in Analysis Services

    Looking at that product dimension for my last post, I noticed that there were five hierarchies defined for the product dimension. A hierarchy is a very important part of any OLAP engine and allows users to drill down from summary levels down to detail levels much as you might want to zoom in on a virtual...
  • Blog Post: MetaData in the Microsoft BI stack

    Metadata is “data about data” and in the BI world this means two things: Definitions of terms, particularly calculations so that business users can understand what they are looking whether on screen or on paper.  Lineage to understand where and how the data in a report was derived. There are a number...
  • Blog Post: SQL Server 2008 Samples

    If like me, you are trying out the new stuff in SQL server 2008 you might need some data to work with. The standard Adventure Works sample databases for OLTP and data warehousing are not in the CTP nor is the the analysis services project. So you'll need to get them from Codeplex which not only has these...
  • Blog Post: Weather in Business Intelligence

    We are obsessed by the weather in this country, but I can’t say I have ever actually used it in a business intelligence solution.  I know that Iceland (the frozen food people not the country) have a model that identifies an ideal BBQ day i.e. not too hot or cold, no rain, low winds and so on, preceded...
  • Blog Post: Date for your Diary – How to go from data to decisions

    A key part of business intelligence is the collaboration between the business user and the BI IT professional and so Microsoft are running a one day seminar addressed to both of these audiences. The well renowned BI guru Rafal Lukawiecki is running this on 26th March at Microsoft’s office in Cardinal...
  • Blog Post: Using Oracle data with Microsoft Business Intelligence

    Before I joined Microsoft, I was working on a large project to build SQL Server 2005 analysis services cubes from data in Oracle 10g.  The fun we had trying to get the data out and setup the servers!  Getting the OLEDB drivers and the Oracle client tools working in a 64-bit environment is at...
  • Blog Post: Business Intelligence, Data Warehousing, and Data Marts

    The terms Business Intelligence, Data Warehousing, and Data Marts are used interchangeably by many people so I thought it would be good to explain the differences. The data warehouse is the repository for all the data to be analysed and reported on without the means to do so. A good analogy would be...
  • Blog Post: Getting Started with SharePoint and SQL Server Reporting Services – a guest post by Jess Meats

    One of the capabilities of SQL Server is the ability to create and publish rich reports on your data. One of the capabilities of SharePoint Server is the ability to store, manage and provide a portal to documents. Those documents could be your reports. So you have one system letting you create reports...
  • Blog Post: Making MDX interesting

    Chris Webb MVP can, to quote a friend of mine can, “Make MDX sound interesting”.  I have to say when I first when on a course on MDX the tutor went for the “Make MDX confusing and boring” approach. Chris has recently coauthored a book on Expert Cube Development with Microsoft SQL Server 2008 Analysis...