Big Data Hadop Analytic
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Big Data is no vogue. The application of big data analytics has spread throughout the public and private sectors. Almost every day we read news articles about its capabilities and the effects it is having, and will have, on our lives. Our Smart phones, websites, chat bots are starting to talk to us, artificially intelligent computers are revealing the election trends, voters mind-set, likeliness of events and machine learning algorithms are diagnosing healthcare.

 This raises questions in our mind that big data has implications for privacy, data protection and the associated rights of individuals. Some countries have acted on it already. They have rights that will be strengthened, when the General Data Protection Regulation (GDPR) is implemented. Under the GDPR, stricter rules will apply to the collection and use of personal data. In addition to being transparent, organisations will need to be more accountable for what they do with personal data. This policy applies to big data, AI and machine learning that are adding fuel to Big Data. No doubt, a strong force behind, all these advances is big data – vast and essentially different datasets that are constantly and rapidly being multiplied from GB – TB – PB – ZB. (Gegabyte, Terabyte, Petabyte, Zetabyte).



Sometimes, we wonder, what exactly makes up these data-sets? Well, very often it is personal data. The online form we filled in for a contest, car insurance quote, images we posted on Instagram, tons of registration forms we will fill every other service we seek in our everyday life. The statistics election results generated, data complied from a sports event, or any social activity today leading to generation of data before it begins, during, and at the end. The sensors we passed when walking into the security check at the airport, train terminals, shopping malls. The social-media, articles, postings, info-graphics, videos, we posted today and last week. The list is unending..

Legacy systems store significant and valuable data. They are assets of the organizations. However, most systems were developed on older technology and have high storage and processing costs. Net2user provides services to design data structures based on Norton Hadoop,  framework integrate organization’s legacy infrastructure with Big Data. We offload voluminous data from existing data warehouses to the new cost effective solutions. Also, using commodity hardware for data storage enhances processing time and analytics’ capabilities.