Big Data & Data Science
Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time.Big data "size" is a constantly moving target, as of 2012 ranging from a few dozen terabytes to many petabytes of data. Big data is a set of techniques and technologies that require new forms of integration to uncover large hidden values from large datasets that are diverse, complex, and of a massive scale.
The challenge for large enterprises is determining who should own big data initiatives that straddle the entire organization
Advantage of Hadoop
Hadoop can handle all types of data from disparate systems: structured, unstructured, log files, pictures, audio files, communications records, email – just about anything you can think of, regardless of its native format. Even when different types of data have been stored in unrelated systems, you can dump it all into your Hadoop cluster with no prior need for a schema. In other words, you don’t need to know how you intend to query your data before you store it; Hadoop lets you decide later and over time can reveal questions you never even thought to ask.
By making all of your data usable, not just what’s in your databases, Hadoop lets you see relationships that were hidden before and reveal answers that have always been just out of reach. You can start making more decisions based on hard data instead of hunches and look at complete data sets, not just samples.
One of the cost advantages of Hadoop is that because it relies in an internally redundant data structure and is deployed on industry standard servers rather than expensive specialized data storage systems, you can afford to store data not previously viable. And we all know that once data is on tape, it’s essentially the same as if it had been deleted - accessible only in extreme circumstances.
What we Offer?
CLARO Technologies can help you build a tailor-made and easily deployable data platform best suited to your specific business requirements by leveraging a powerful big data platform. Our team has built expertise in developing large scale big data solutions.
Big data requires exceptional technologies to efficiently process large quantities of data within tolerable elapsed times. Suitable technologies include A/B testing, crowdsourcing, data fusion and integration, genetic algorithms, machine learning, natural language processing, signal processing, simulation, time series analysis and visualization.