When we talk about the term Big Data we clearly are speaking about petabytes and exabytes of data which is very difficult to process by using traditional data processing systems. So in simple terms Big Data means the collection of data sets which are very large and complex & so difficult to process using traditional data processing systems.
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| Hadoop |
Hadoop Technology is one of the most talked technologies since its inception and the obvious reason is its ability to handle large & complex data.
Apache Hadoop is a parallel distributed processing middleware technology which is applied across various industry verticals to perform Big Data analytics. It is an open source framework for storing & processing large sets of data.
Hadop mainly invented to perform two tasks and that are massive data storage and quick processing.
Importance of Hadoop:
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| Importance of Hadoop |
Take a quick look at some of the facts that proves importance of hadoop :
- Provides a way to process large volume of unstructured data.
- Hadoop provides quick data processing in a cost effective way.
- Provides great flexibility. In traditional data processing systems you need to preprocess data before storing it but this is not the case with hadoop.
- It provides more scalability. One can grow their systems easily by simply adding more nodes.
Most data gathered by an organizations are unstructured data. Hadoop-based applications are hence applied by organizations that need real-time analytics from data such as audio, video, email, machine-generated data from a multitude of sensors and data from external sources such as the Internet and social media.
Hadoop-based applications are widely applied across business verticals with strong web-based business process for various customer related analysis such as clickstream analysis, marketing analytics, processing machine generated data, processing digital content and web text processing.
Scientific applications which require high degree of parallelism or need to operate on large volumes of data also benefit from MapReduce and Hadoop. Scientific applications are mostly used by companies in the Bioinformatics and Healthcare verticals.
Hadoop applications such as HDFS, Hive, Pig, and Hbase have also been developed by Apache Software Foundation to support loading, storing, and transforming data in a Hadoop cluster. These Hadoop applications ensure that organizations across various industry verticals can undertake a smooth transition from traditional analytics towards Hadoop-based big data analytics.
Economic Forecasts of Hadoop & Big Data Analytics Market:
The global Hadoop market revenue is expected to reach $13.95 billion by 2017 from $1.56 billion in 2012, at an estimated CAGR of 54.9% from 2012 to 2017.North America holds the largest share of the Hadoop market revenue in 2012 at $0.84 billion; and is expected to reach $6.92 billion by 2017, at a CAGR of 52.4% from 2012 to 2017.
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