Essay On Big Data

Abstract- Big data is a hot research topic in today’s world. Data has become an indispensable part of every economy, industry, organization, business function and individual. With the fast growth now-a-days organizations has filled with the collection of millions of data with large number of combinations. This big data challenges over business problems. Big Data is a new term used to identify the datasets that due to their large size and complexity. Big Data mining is the capability of extracting useful information from these large datasets or streams of data, that due to its volume, variability, and velocity. We address broad issues related to big data and/or big data mining, and point out opportunities which help to reshape the subject area of today’s data mining technology toward solving tomorrow’s bigger challenges emerging in accordance with big data.

Sedgewick, R., & Wayne, K. (n.d.). Binary Search Trees. Retrieved April 26, 2016, from http://algs4.cs.princeton.edu/32bst/

Big data and its definition has changed over the years. In a 2011 research project by MGI and Mckinsey’s Business’ defined big data as

Marc Kosciejew states in his article titled “The Perils of Big Data,” that, “Big Data can cause catastrophic miscalculations if the underlying data is poor, mis-analyzed, or used misleadingly or unwisely.” (34) This means that data is dangerous, if it is not kept to strict privacy laws. In this day and age, someone’s career can be lost due to a simple phrase that spread across the internet like wildfire. (Doughty) The leaking of data can have disastrous effects if said data is used for harmful intent. The chances of “personally identifiable information” increasing privacy concerns are raised when certain factors work together. (Sherer 10) Data has a way to prevent us from recognizing that something is not right with the information produced, because we are unknowingly held to the product of our data. (Kosciejew 34) Data is given a form of truth which it has not earned. (Kosciejew 34) Today, data is used to rule over our lives in ways that cause serious damage. This vulnerability is known as the “dictatorship of data.” (Kosciejew 34) Many people have lost

Data is a forever growing thing and is not looking to slow down anytime soon. With that be said, companies must be able to manage data for their day to day operations as well as for predicting future trend. Now there are many tools for managing data and extremely high cost for managing it as well. One of the costs for managing data is data security, but this paper will touch on that topic in, but not as much as other topics. Also, this paper will demonstrate various business cases to serve as testimonial for just how useful big data management it in to day society.

After graphing our data it is clear that both masses are oscillating, however we notice that the period of oscillation for both masses does change after some time. It appears that the period of oscillation for mass 2 becomes shorter after some time. It is hard to make any conclusive conclusion of for the period of mass 1. However, it is clear that the two masses do appear to come closer to synchronization toward the end of the video. As seen in graph 1 and graph 2. Especially in graph 2 where the very last point at M1 and M2 appear to be close to synchronizing. Additionally, by closely watching

Another method is context search. The context search adds context to the search criteria. “Context search helps improve the keyword search solution by addressing the problems present in keyword searches related to synonymy and polysemy. Synonymy is a common linguistic issue where different words are used to express the same concept, and polysemy is where the same word can have different meanings” (Fordham, 2013). The context search method combines several advance techniques in a simple user interface, making searches

C] Onwuchekwa, Edeama O. and Jegede, Olumakinde Richard (2011) “Information Retrieval Methods in Libraries and Information

The dataset comprises of a single csv file data.csv that contains 3 types of entities namely users, businesses and reviews. Records for each entity are distinguished by the 'type ' column.

Relevance feedback refers to a system in which the user is involved in the retrieval process. From the initial query results a user selects a small set of documents that appear to be relevant to the query; the system then uses aspects derived from these selected relevant documents to recalibrate the original query. This revised query is then executed and a new set of results is returned. Documents from the original set can appear in the new results list, although they are likely to appear in a different rank order. Relevance feedback in its original form has been shown to be an effective mechanism for improving retrieval results in a variety of studies and settings. (Hearst, 1999)

Librarians have duties to design, query, and evaluate information retrieval systems. In order to do so, librarians must understand each basic element of an Information Retrieval System. The first step is to understand their purpose. Information Retrieval Systems are designed to deal with various sources of information, and to satisfy user’s requirements. When a user makes an inquiry, the system must analyze the available sources, match the search specifications, and retrieve the items which are the most relevant to the search terms. Chowdhury (2004) describes the three aspects of Information Retrieval System design: the document subsystem, the user subsystem, and the searching/retrieval subsystem. Together, these three subsystems work to store, maintain, and sort information items. These systems are in place in many areas of libraries. They can be found in privately held databases, Open Public Access Catalogs (OPAC), and paid subscription databases. OPACs may be confined to a single library or they may be jointly managed by a wider library district or by a collaboration of medical or academic libraries. They hold a great deal of information about the physical and the digital library collection. They allow users to retrieve information concerning the location of where information items are to be found. Without a well functioning OPAC, it would be very difficult for both librarians and patrons to access the information items held in library collections. OPACs hold

Due to the rapid growth in the use of Internet and its connected tools, an enormous amount of data are being produced on a daily basis. The concept of big data arrives when we were unable to manage this huge data with traditional methods. Big data is a mechanism of capturing, storing and analyzing the big datasets and also an idea of extracting some value from it. It is very handful while determining the root causes of failures, issues and defects in near-real time, creating coupons and other sales offers according to the customers shopping patterns, detecting any suspicious and fraudulent activities in real-time. As it is very advantageous, it also has some issues. Some of the common issues can be characterized into heterogeneity, complexity, timeless, scalability and privacy. The most important and significant challenge in the big data is to preserve privacy information of the customers, employees, and the organizations. It is very sensitive and includes conceptual, technical as well as legal significance.

Big data is needed in several situations during election process, but the main purpose of political data is to provide a citizens’ contact list. Campaigns need information about which citizens participate in specific campaign actions like rallies, petitions, candidate support, donating money, volunteering, or issues in tracking polls.

Big data lets many companies analyze data about their customers, if it is used efficiently. Spotify for example, uses its data to give the customer a better listening experience. By using their big data, they can pick up on preferences and tastes of the customers who are using the service. In order to create a better experience for the consumer “Spotify uses the big data it collects on user listening habits to design highly individualized products” (Laudon 244). By doing this, Spotify can create greater customer-supplier intimacy, because they create things specified for each customer. A multitude of playlists, or song recommendations can be created based off of personal information provided

Keyword search is the most effective information discovery method in documents. The large volume of data is stored in databases. Plain text coexists with structured data, unstructured data for this type of data efficient processing of top-k queries is a crucial requirement. This paper describes fundamental characteristics including relational database, top-k queries, steiner trees. Recently, Tuple units are used to improve the keyword search by joining the multiple related tuple units and indexes are used for structural relationships. In this paper various existing techniques for developing search system are compared. This survey also describes the Ranking. Ranking queries are dominant in many emerging applications for finding top-k answers. The research strategy used to resolve is top-k query processing.