Monday, 29 April 2013

10 reasons to choose Big Data Analytics


Big Data is a recent concept that has struck the IT industry in a hard and fast way. It is seen that all kinds of new technologies are first adopted by larger enterprises and then considered by midsized companies. With time, the amount of data to be processed is going to increase drastically. In order to mitigate the risk of managing loads of data, Big Data Analytics is said to be a feasible solution.

Before you choose any kind of analytics, here are the top 10 reasons you should consider

1) Enterprise wide real-time indexing of data from any machine
Big Data uses NoSQL databases like Hadoop. Hadoop uses file indexing instead of data indexing carried in typical relational databases. Thus, it is able to handle diverse data comprising of different sources. Here, data is stored as it comes with definition left to analysis stage.

2) Easy search and analysis of data
Data – real time or historical needs to be recalled quickly as possible for the sake of analysis. Big Data provides search tools for calling unstructured data using text search. Thus, faster responses can be provided.

3) Automatic knowledge discovery from data
Data mining and predictive analytics technologies discover the data to propose statistical models. Based on these models, continuous evaluation is automatically carried to find valuable insights.

4) Real time data monitoring-
Big Data provides continuous monitoring and processing of coming data. Based on any anomalies, real time alerts are passed out. This is essential for every business to flourish.


5) Powerful ad hoc query processing
Based on the requirements of management, different reports are needed, and ad hoc queries need to be passed. Big Data provides ad hoc analysis and report generation and aids in the short term decision making.

6) Ability to build custom dashboards and views
It is very difficult for having custom views for unstructured data. Big Data overcomes this problem by providing custom views. One can write custom Hive statements and get the necessary views.

7) Efficient data scaling
Big data analytics uses unstructured data storage, and data is stored as it comes without any problems of indexing.

8) Provide Role based security         
Data in Big Data Analytics is diverse and comprises of different segments. At this level, security regarding access of data becomes a crucial concern. Big Data provides Access control lists to maintain confidentiality of data stored.

9) Flexible deployment
When new technologies are adopted, a considerable time is spent to learn and experiment it. Big Data comes with a smooth learning curve utilizing minimum implementation time and faster deployment.

10) Portable interfacing
Big Data is versatile and can be interfaced with any programming API. Thus, different programs can be written based on capabilities of the developer.

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