ISSN: 2277-9655 [Fatima* et al., 7(5): May, 2018] Impact Factor: 5.164 IC™ Value: 3.00 CODEN: IJESS7 http: // www.ijesrt.com © International Journal of Engineering Sciences & Research Technology [561] IJESRT INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY RICH ANALYTICS WITH HADOOP TECHNOLOGY Dr.Shahnaz Fatima Amity Institute of Information Technology Amity University,Lucknow,India DOI: 10.5281/zenodo.1252936 ABSTRACT The period of ‘big data’ represents new challenges to businesses industry. Incoming data volumes are exploding in variety, speed, volume and complexity. It is not defined anywhere as such that how much volume of data will be considered as “big” data, but handling of such data requires lot of new tools and techniques to process it. To harness the power of Big data one needs an infrastructure and technologies which can deal with huge volume and variety of data as well as can draw inferences from it. There are various technologies for “Big Data Analysis” given by various vendors. The technologies are growing rapidly with the growing market of Big Data Analytics. The paper will provide you with a perspective on the technology platforms for big data and analytics. This paper presents an overview of Hadoop. KEYWORDS: Hadoop,Apache,Analytics,Big Data I. INTRODUCTION BIG DATA ANALYTICS Big data deals with the variety of a data. Different variety of data needs different analytic logic to produce results which work as an insight for the business[6].The data analysis is not at all a new concept in a business stream. It is essential for strategic planning in the business houses. The trend of analysis is to have an insight of the current market trends and customer demands. The big data technologies give you more and more accurate analytical results. This leads to the concrete data analysis as well. The robustness of big data can be best utilized by having an infrastructure which can manage multiple machines on the same time. The infrastructure should be capable of managing huge volume of structured and unstructured data, without compromising its security and privacy. Big data technologies can be classified into two main categories- a) Operational data b) Analytical data Operational data Operational data includes sales, service, order management, manufacturing, purchasing and billing. The applications working at the operational level require significant amount of data related to the product sales, customer and other related data like price, discounts etc. Analytical data Analytical data is all about planning and decision making. It works as a support system of the business. It gives a deep insight about the Customer market needs, Suppliers performance, Market tendency, Product behavior etc. II. BIG DATA TECHNOLOGIES There are a number of disruptive and transformative big data technologies and solutions that are rapidly emanating and evolving in order to provide data-driven insight and innovation[1].The variety of technologies is given by the various vendors for big data. Apache has given the set of following technologies like Apache hadoop, Apache Pig, Apache Hive, Apache Hbase, Apache Spark and many more. The paper will give an overview of Hadoop technologies.