How to kill your Big Data initiative


Everyone is doing Big Data these days. If you don’t work on Big Data projects within your company, you are simply not up to date and don’t know how things work. Big Data solves all of your problems, really! Well, in reality this is different. It doesn’t solve all your problems. It actually creates more problems then you think! Most companies I saw recently working on Big Data projects failed. They started a Big Data project and successfully wasted thousands of dollars on Big Data projects. But what exactly went wrong? First of all, Big Data is often only seen as Hadoop. We live with the mis-perception that only Hadoop can solve all Big Data topics. This simply isn’t true. Hadoop can do many things – but real data science is often not done with the core of Hadoop. Ever talked to someone doing the analytics (e.g someone good in math or statistics)?. They are not ok with writing Java

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Strategies for Cloud Computing Application Deployment


As already mentioned in the last post, Application deployment in the Cloud is not an easy task. It requires a lot of work and knowledge, unless you use Platform as a Service. The later one might reduce this complexity significantly. In order to deploy your Applications to an Infrastructure as a Service Layer, you might need additional knowledge. Let us now built upon what we have heard from the last post by looking at several strategies and how they are implemented by different enterprises. Some years ago before joining IDC, I worked for a local Software Company. We had some large-scale deployments in place and we used Cloud Services to run our Systems. In this company, my task was to work on the deployment and iteration strategy (but not only on that ;)). We developed in an agile iteration model (basically it was Scrum). This means that our Team had a new “Release” every 2 weeks. During these two weeks,

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Starting a new Cloud Computing Project


More and more companies start Cloud Computing Projects, with a lot of Startups also among them. But what do you have to take into account when you start a new Cloud Computing Project? Is it save to just start or should you consider some best practices in project management? And if so, what do you need to do regarding Cloud Computing? In this article we will give a brief overview on what is necessary to get started with Project Management for Cloud Computing. Project Management itself consists of the following 5 Iterations: 1.Project Initialisation 2.Project Creation 3.Project Planing 4.Execution 5.Introduction Each Iteration contains some sub-processes which we will describe more detailed now. The first iteration, Project Initialisation, basically starts when someone realizes that there is a need for a project or someone has a business idea. Normally, you start building some KO-Criterias, like feasability or already existing products/platforms. If your project “passes” these KO-criterias, you might move on on evaluate

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