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Big Data

This category contains 16 posts

Cloud Cipher Capabilities

Where I’m reviewing support for encryption in the context of IaaS|PaaS|SaaS cloud service offerings as well as concerning Hadoop. While the motivation for encryption might differ, the primary question is if systems support this (transparently) or if developers are forced to code this in the application logic. Continue reading

Elephant filet

In situations where Hadoop is used in a shared setup we witness two competing forces: the user expects performance vs. the view of the cluster owner who aims to optimise throughput and maximise utilisation. In the post, Michael elaborates a bit on challenges and solutions on this topic. Continue reading

MapR, Europe and me

You might have already heard that MapR, the leading provider of enterprise-grade Hadoop and friends, is launching its European operations. Guess what? I’m joining MapR Europe as of January 2013 in the role of Chief Data Engineer EMEA and will support our technical and sales teams throughout Europe. Pretty exciting times ahead! As an aside: … Continue reading

Hosted MapReduce and Hadoop offerings

Today’s question is: where are we regarding MapReduce/Hadoop in the cloud? That is, what are the offerings of Hadoop-as-a-Service or other hosted MapReduce implementations, currently? A year ago, InfoQ ran a story Hadoop-as-a-Service from Amazon, Cloudera, Microsoft and IBM which will serve us as a baseline here. This article contains the following statement: According to … Continue reading

MapReduce for and with the kids

Last week was Halloween and of course we went trick-or-treating with our three kids which resulted in piles of sweets in the living room. Powered by the sugar, the kids would stay up late to count their harvest and while I was observing them at it, I was wondering if it possible to explain the … Continue reading

Denormalizing graph-shaped data

As nicely pointed out by Ilya Katsov: Denormalization can be defined as the copying of the same data into multiple documents or tables in order to simplify/optimize query processing or to fit the user’s data into a particular data model. So, I was wondering, why is – in Ilya’s write-up – denormalization not considered to be … Continue reading

Interactive analysis of large-scale datasets

The value of large-scale datasets – stemming from IoT sensors, end-user and business transactions, social networks, search engine logs, etc. – apparently lies in the patterns buried deep inside them. Being able to identify these patterns, analyzing them is vital. Be it for detecting fraud, determining a new customer segment or predicting a trend. As … Continue reading

Linked Data – the best of two worlds

On the one hand you have structured data sources such as relational DB, NoSQL datastores or OODBs and the like that allow you to query and manipulate data in a structured way. This typically involves schemata (either upfront with RDB or sort of dynamically with NoSQL that defines the data layout and the types of … Continue reading

Why I luv JSON …

… because it’s simple, agnostic and an end-to-end solution. Wat? OK, let’s slow down a bit and go through the above keywords step by step. Simple Over 150 frameworks, libraries and tools directly support JSON in over 30 (!) languages. This might well be because the entire specification (incl. ToC, all the legal stuff and … Continue reading

Hosted NoSQL

I admit I dunno how I got here in the first place … ah, right, yesterday was Paddy’s day and I was sitting at home with a sick child. Now, I tinkered around a bit with a hosted CouchDB solution to store/query JSON output from a side-project of mine. Then I thought: where are we … Continue reading

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