Managing And Analyzing Big Data

Big data analytics is the process of analyzing large data to find useful information such as improving efficiency of business, market trends, customer’s preferences, information of competitors, and other useful business information. According to the IT Glossary, “Big Data is high-volume, high-velocity, and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.” In other words, it is an abundant array of information used to acquire insights and make business decisions.

Big Data is an expansive phrase for data sets so called big, large or complex that they are very difficult to process using traditional data processing applications. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. In common usage, the term big data has largely come to refer simply to the use of predictive analytics. Big data is a set of techniques and technologies that need or require new forms of integration to expose large invisible values from large datasets that are diverse, complex, and of a massive scale. When big data is effectively and efficiently captured, processed, and analyzed, companies

As a result of the appearance of big data in our world, conventional data warehousing and data analysis methods no longer have the process power needed. What is Big Data you may ask and why is it such a big deal. NIST defines big data as anywhere “[…] data volume, acquisition velocity, or data representation limits the ability to perform effective analysis using traditional relational approaches […]” (Mell & Cooper, n.d.).

The amount of data in our world has been rapidly increasing and analyzing these large data sets, or big data, has become crucial for businesses in increasing their success. Many businesses use big data to model their business structures, control processes, and run the business. The availability of this data leads to a more accurate analysis of the target market. More accurate analyses lead to more confident decision making and better decisions means greater operational efficiencies, cost reductions and reduced risk. There are many ways in which big data can be successfully implemented in an organization. Big data allows businesses to segment their target market, creating more precisely tailored products and services. Big data is also used to conduct controlled experiments to make better management decisions. Finally, big data can unlock value by making the captured information transparent and usable at much higher frequency (Manyika, “Big data: The next frontier for innovation, competition, and productivity”).

“Why Big-Data Is a Big Deal”. Big-data is a logo used to describe a massive volume of both structured (is information already managed by the organization in relational databases ) and unstructured data (is information that is unorganized and does not fall into a pre-determined model) that is so large it is difficult to process using traditional database and software techniques. In most companies, the volume of data is too big or it moves too fast or it exceeds current processing capacity. Despite these problems, big-data has the potential to help companies improve operations and make faster, more intelligent decisions.

Big data is an extensive collection of structured and unstructured data. It is a modern day technology which is applied to store, manage and analyze data that are not possible to manage, store and analyze by using the commonly used software or tools. Since all of our daily tasks are overtaken by the modern technologies and all the businesses and organizations are using internet system to operate, the production of data has increased significantly in past

Many large companies like Google, Facebook, Amazon, Netflix are leveraging unstructured data to facilitate human decision making, automate simple tasks, and to make the world a smarter place. The term big data is used to describe these unstructured datasets that are so large and complex that traditional

Inventions in technology and excessive use of digital devices have presided over today’s Age of Big Data, in Three V’s of data. These data allows the users to enhance the social security, understand the existing systems and to track improvement progress. For example, transforming Big Data (banking transactions, call records, online user created data like Tweets and blogs, online searches, etc.) into useful data needs computational methods to reveal structure among and inside these very big socioeconomic data. The data driven management is now familiar and there is increasing interest for the concept of “Big Data”. Currently there is a gap between its insight and its potentials of Big Data.

The term Big Data is to a large extent vague and amorphous. Information technology professionals look at Big Data as large data sets that require supercomputers to collate, process and analyse to draw meaningful conclusions. A phenomenon defined by the rapid acceleration in the expanding volume of high velocity, complex, and diverse types of data. The new character added in this definition is

We define “big data” as a capability that allows companies to extract value from large volumes of data. Big data is unstructured data and for every kind, data is important so no policy as policy as it won’t filter any data.

Big data refers to large data sets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze. Big data is used to analysis the

Big data is a term used to define the amount of data, structures and unstructured, so huge that traditional data base managements techniques are rendered useless and the storage and analytics of this data pose a problem. There are various types of big data and big data can be defined in four Vs, which are: Volume, Velocity, Variety and Veracity. The problem is solved by Google Distributed File System, an application that google created for it’s own use to automatically store data.

“Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn’t fit the strictures of your database architectures. To gain value from this data, you must choose an alternative way to process it.” (Dumbill, "What is big data?", 2012).

Management of big data is useful with how it is used. Ways to use the stored information include, but not limited to, reduction of costs, time reductions, and making smart decisions based on data results. [1]

There are lots of opportunity associated to big data that help any organization to handle their large amount of data, like in financial sector it store data related to finance, healthcare sector it store health related patient records, doctors detail and medicine ,medical equipment related details . In retail sector it is also used [5]. Web/social media/mobile companies also use it for storing their user detail and data like their likes, search pattern, calling and messaging records. Manufacturing and government sectors also use it.