With Big Data being one of the top trending fields in the world of infinite data that is continuously exchanged via the Internet of Things and social networking, the tools and frameworks that can process this (big) data are obviously in much need.
We have recently included this domain in our test catalog via our new quiz on Hadoop, one of the industry-leading technologies for implementing Big Data solutions. As emphasized by TechRepublic, Hadoop is an open source framework that implements MapReduce, a programming paradigm that allows for massive job execution scalability against thousands of servers or clusters of servers.
Nevertheless, Big Data is not about technology, it’s about Data and Information, mathematics and all the related fields. This is why we consider it useful to briefly portrait a Data Scientist.
Any Data Scientist should be endowed with the following three groups of skills:
- Business – for this is where the real value lies – knowing how to address business problems that can bring value to the organization is a major asset.
- Statistics and statistical programming – knowledge of R or Python programming languages.
- Computer science – knowledge of data storage, data processing technologies, machine learning etc.
Or, in other words: “Understand your data. Diagnose. Treat and prevent.”
Returning to our new quiz, it has been specially created to assess your knowledge of the Hadoop architecture, as well as your ability to solve Big Data problems using the parallel processing power of Hadoop MapReduce.
Built to process large amounts of data by connecting multiple computers in a cluster for them to work in parallel, Hadoop is a framework that allows distributed storage and distributed processing of very large data sets. Based on the MapReduce model, Hadoop can take a query over a dataset, divide it, and run it in parallel over multiple nodes. Data that is too large can thus fit onto a single machine thanks to distributed computation. Imagine that you can start with a single node that can scale up to thousands of nodes! Isn’t this great?
The main advantages of Hadoop?
- speed – due to its distributed system that works as a whole for a much rapid data processing.
- scalability – it can store and distribute large amounts of data sets across its system and also easily add more machines to the system.
- flexibility – it enables the easy access of businesses to new data for all kind of industries like telecommunications, social media, finance, government, healthcare, retail etc.
Here you can find out more information on why to use Apache Hadoop.
You can also take a quick look at our Python article, one of the most important languages for a data scientist to learn.