David Chappell

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New Whitepaper: Introducing Azure Machine Leaning  
# Wednesday, August 05, 2015
 
Machine learning has become a big deal. The rise of big data and the massive computing power made possible by cloud computing have made this set of technologies much more useful.

But machine learning isn't especially simple. While the basics are fairly straightforward, they're cloaked in odd terminology, phrases like "training data" and "supervised learning". For data scientists, people with years of specialized training, this isn't a problem. For non-specialists, though, the topic can be off putting.

To perhaps help with this, I've written a Microsoft-sponsored introduction to Azure Machine Learning (ML) . The paper's subtitle is A Guide for Technical Professionals, and that's exactly what it is: an introduction to machine learning for ordinary mortals. Azure ML is likely to become a broadly used technology, and so knowing the basics of machine learning is important. The paper's goal is to help you do this, using Azure ML as a concrete example.


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New Whitepaper: Introducing Azure Search  
# Wednesday, April 15, 2015
 
For most of us, talking about search makes us think of Google (and maybe Bing). But for people who build applications, talking about search should bring something else to mind: the possibility of building a search box directly into a custom application's user interface. It's possible to do this with Google or Bing, but this approach has some limitations. Rather than relying on existing search services, creating a search UI for which you can control the results can have a lot of appeal.

One way to do this is to use Elasticsearch . A simpler option, though, is to use a managed search service such as Microsoft's recently announced Azure Search. Azure Search isn't designed for end users. Instead, it's accessed by applications via a RESTful interface. The goal is to make it straightforward for developers to add search to the UI of the applications they build.

I've written a Microsoft-sponsored introduction to Azure Search, available here, that explains why adding search to custom apps makes sense. The paper also walks through the basics of the technology, giving you a big-picture sense of what Azure Search does and how it works.

I don't know about you, but I love search UIs. If every application I use offered at least the option of search, I'd be a happy man. The availability of Azure Search is a step on the road to making this happen.


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New White Paper: Understanding NoSQL on Microsoft Azure  
# Sunday, December 28, 2014
 
Strictly speaking, this isn't a new whitepaper--it's an update of an earlier paper I wrote on this topic. But Azure's native support for NoSQL has gotten so much broader that the paper is almost entirely new.

The technologies it covers are:

  • DocumentDB, Azure's document store
  • Tables, Azure's key/value store
  • HBase, Azure's column family store, and
  • HDInsight, Azure's implementation of the Hadoop technology family.
As usual, my goal is to provide a big-picture introduction to these technologies. The paper won't provide details on how to use any of them, but I hope it will provide a place to start in deciding whether you need NoSQL and in choosing among the options.

If this sounds interesting to you, the paper is available here.


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The New Big Picture for Data  
# Friday, October 31, 2014
 
It's a heady time for data. We've seen more change in the last few years than in the previous couple of decades. Because of this, we need to think about data in some new ways.
For example, the traditional big-picture view of data technologies looks like this:
In this world view, the operational data that applications use is stored in a relational database. Over time, that relational data gets loaded into a relational data warehouse, where it becomes analytical data. Business intelligence (BI) applications then use that analytical data to help organizations make better decisions .
But things are changing. Here’s a more accurate big-picture view of the data world today:

Increasingly, applications are using relational and NoSQL databases for operational data. Turning this operational data into analytical data implies having both a relational data warehouse and an unstructured data lake. BI applications are then able to access both kinds of data to help their users.

And there’s another new piece: search data. As search services become more available (Amazon Web Services and Microsoft Azure both provide them today), building search into every application gets easier. Users love search, and with a managed search service in the cloud, the barrier to entry is significantly lower. But search data is different from either operational data or analytical data—it’s a new category. Accordingly, it’s staking out a new position in the data world.
Data technologies have shaken off decades of relational torpor; lots of new things are happening. It’s time to look at this world in a new way.


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Introducing DocumentDB: A NoSQL Database for Azure  
# Friday, September 12, 2014
 
Document databases are probably the most popular NoSQL stores today. MongoDB has lots of users, for example, as do RavenDB and others. If you'd like to run these on Azure, you certainly can: MongoDB and RavenDB are both available in the Azure store today.

Alongside these, Microsoft now offers DocumentDB, its own document database for Azure. Like most of what Microsoft adds to Azure today, DocumentDB is a managed service, so creating and using databases is relatively straightforward. And like MongoDB, DocumentDB stores JSON documents grouped into collections, although these two document stores also differ in some interesting ways.

I've written a Microsoft-sponsored introduction to DocumentDB, available here, that gives an overview of the technology. The target audience isn't NoSQL database experts, though. My goal was to explain this technology in a way that would make sense to a .NET developer who works in the relational world, a category that I'd argue is much larger today than the set of NoSQL experts. If that's you, and if you're interested in modern data technologies, you might find the paper worthwhile.


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Visiting Central and Eastern Europe  
# Wednesday, September 10, 2014
 
I'm returning to Europe later this month for a two-week speaking tour, sponsored by Microsoft. I'm doing a variety of talks in different cities, all related to Azure and cloud computing. Here are the cities and dates:

  • September 23: Bratislava
  • September 25: Vilnius
  • September 30: Kiev
  • October 2: Budapest
  • October 3: Prague
After visiting many times, I've become really fond of this part of the world. I'm looking forward to the tour.


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