Ajay S.

The data analysis starts of with initial task of having to classify data. There are various algorithm which one may employ to classify data. The single most simplest and widely used algorithm is the K-Means Clustering. This session talks about K-Means Clustering and how to do the same using Azure ML.

Most applications will certainly find the need to use big data in near future. With data storage on the cloud very cheap compared to what an RDBMS on premise/cloud would give. The option for move the application data to No SQL or Hadoop is a natural progression.
Having built a large enterprise architecture on Windows Azure, I did dwell on the need of Hadoop the debates stretching from RDBMS to cheap storage, new complexity and tribulations of accepting Hadoop with extreme experimentation has… عرض المزيد

Most applications will certainly find the need to use big data in near future. With data storage on the cloud very cheap compared to what an RDBMS on premise/cloud would give. The option for move the application data to No SQL or Hadoop is a natural progression.
Having built a large enterprise architecture on Windows Azure, I did dwell on the need of Hadoop the debates stretching from RDBMS to cheap storage, new complexity and tribulations of accepting Hadoop with extreme experimentation has been a vertical climb.
Below are the experiences, the learning's, mistakes during the past 3 months on the Hadoop Journey and we are still not quite there. عرض أقل

The Big Data Landscape is for ever changing. While studying what’s there in market and how do I really get a handle at understanding Big Data I come to find that every 2 weeks there is a new name in the landscape. Also the flip side is there names which would just vanish in a short time. It would be good to get a basic understanding of Big Data.

I have been closely reading the Azure CAT (Customer Advisory Team) which helps a lot of customer deliver large, complex projects. The Azure CAT site can be found here guidance on how to use different architectural artefacts in Azure. After some digging this what I have come to understand are some of the largest implementation on Azure Platform. This is however some amount of reverse engineering and research. Hope this is helpful to the readers.

Codename Narwhal is Obama secret data integration project which started 9 months has paid off. The team of data scientists , developers, and digital advertising experts, putting there heads together to really get big data to help the team make better decision.

The Service Bus is single most important component be it an Enterprise Integration scenario or a cloud (which by the way happens to be mass scale integration of massive number of applications). The expectation from Service Bus in the cloud are very many, when compared to an Enterprise scenario the Enterprise Service Bus does cater to a bare minimum of the following features

Messaging Services:
Management Services
Security Services
Metadata Services
Mediation Services… عرض المزيد

The Service Bus is single most important component be it an Enterprise Integration scenario or a cloud (which by the way happens to be mass scale integration of massive number of applications). The expectation from Service Bus in the cloud are very many, when compared to an Enterprise scenario the Enterprise Service Bus does cater to a bare minimum of the following features

Messaging Services:
Management Services
Security Services
Metadata Services
Mediation Services
Interface Service
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PaaS or Platform as a service as a concept has been well received, however one really needs to understand when is it likely to hit the mainstream. In this post I will start with the the basics of PaaS and IaaS, dig deeper into PaaS, notes on Windows Azure PaaS programming model & lastly what’s the roadmap of Windows Azure really looking like. As usual a disclaimer “ this post is my personal views I don’t write for MSFT”.

Architecting the Private Cloud shed light on real life scenario based on some of the customers experiences on what to ask, what are the steps on moving into Private Cloud and an example on mapping the services to cloud attributes. In the cloud we are governed by the cloud attributes to a large extent. In this post I want to take a dig into “what dwells into an average developer or architects mind on moving an on premise application on to the cloud”. The cloud can be private or public doesn’t… عرض المزيد

Architecting the Private Cloud shed light on real life scenario based on some of the customers experiences on what to ask, what are the steps on moving into Private Cloud and an example on mapping the services to cloud attributes. In the cloud we are governed by the cloud attributes to a large extent. In this post I want to take a dig into “what dwells into an average developer or architects mind on moving an on premise application on to the cloud”. The cloud can be private or public doesn’t matter , the assumption the private cloud architecture is in line with earlier post holds here.
What am addressing is post is “What are the software pattern & frameworks that are emerging in the cloud scenario” & What do customers do in practice.
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Private Cloud is next most abused term in current times after SOA. When we get into a conversation with CIO “ lets move onto private cloud” the prompt response comes in lets have a hypervisor and orchestrator and we are done, be it Cisco, VMware, MSFT they all talk the same jargon. I’d like to differ from the standard jargon take a step back. I have written this post based on actual customer interaction I have followed this process.

Competing models exists in nature everywhere. The idea behind most competing model is to create improvisation using competition. Essentially like a software developer writes zero defect code and testers job is to find bugs, the competition is to create software with best quality.

GAN or Generative Adversarial Model are consisting of two simultaneously trained models the Generator which generates fake data and Discriminator that tries to identify the fake data from the real data