Data Essays

even your personal data that could be sold to third party companies. Major data breaches of popular website skyrocket to the news on what seems to be like on a daily basis, leaking thousands, if not millions of individuals person information. This data breaching can expose your bank account, credit card number, social security number, and many other confidential information that you would not share. The increase of cloud data, which is stored not on your device, but data from a company's server

I am writing in regard to your advertisement for a Data Analyst Intern posted on Indeed.com. Currently, I am a junior majoring in Economics and minoring in Statistics and Business. I believe my academic background coupled with my university involvements perfectly address the needs of the position. As a student at Penn State, I have taken classes that highly correlate with the Data Analyst Intern position. Some of the most relevant courses include… I learned to optimize and apply statistical models

Abstract- Outlier detection is an active area for research in data set mining community. Finding outliers from a collection of patterns is a very well-known problem in data mining. Outlier Detection as a branch of data mining has many applications in data stream analysis and requires more attention. An outlier is a pattern which is dissimilar with respect to the rest of the patterns in the data set. Detecting outliers and analyzing large data sets can lead to discovery of unexpected knowledge in area

spatial or geographical data. FOSS; Free or Open Source Software. FOSS programs have licenses that allow users to freely run the program for any purpose, modify the program as they want, and also to freely distribute copies of either the original version or their own modified version. ILWIS; Integrated Land and Water Information System is a GIS / Remote sensing software for both vector and raster processing. ILWIS features include digitizing, editing, analysis and display of data as well as production

Data mining can be viewed as a result of the normal development of information technology Since 1960, database and information technology has been growing methodically from primitive file processing systems to complicated and prevailing database systems [11] [13]. Figure 1.1: History of data base system and data mining Data mining drives its name for searching a important information from a large database to utilize this information in better way. It is, though, a misnomer, as mining for gold

The health care industry can and will benefit greatly from big data. As health care professionals look for ways to reduce disease, treat patients, and lower costs, big data will be heavily used to bridge the gaps. Doctors all around the world will be able to enter endless amounts of data and in return, big data can provide valuable statistical information on specific ailments and what factors contributed to development. Once you factor that in with a specific patient, a doctor will be able to make

Growing, cross-channel data volumes The rise of mobile, tablets and social media has accelerated the growth of available customer data. A typical retailer knows not only the basic demographic information about a customer, but purchase history, call center interaction, mobile/social interaction, supply chain data and more. The sheer volume of information available to retailers is unprecedented, even for brands that have years of experience analyzing customer data. 2. Increasing investment in technology

1.1. DATA MINING Data mining refers to extracting or mining knowledge from large amounts of data. Data mining has attracted a great deal of attention in the information industry and in society as a whole in recent years, due to the wide availability of huge amounts of data and the forthcoming need for turning such data into useful information and knowledge. The information and knowledge gained can be used for applications ranging from market analysis, fraud detection, and customer retention, to

Data mining is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data preprocessing, model and inference considerations, interestingness

discovery also known as data mining is the processes involve penetration into tremendous amount of data with the support from computer and web technology for examining the data. Data mining is a process of discovering interesting knowledge by extracting or mining the data fromlarge amount of data and the process of finding correlations or patterns among dozens of fields in large relational databases [3, 4]. Privacy Preserving in Data Publishing (PPDP) is very important in data mining when publishing

imagine you have 10 billion rows of retail SKU data that you are trying to compare. The user trying to view 10 billion plots on the screen will have a hard time seeing so many data points. One way to resolve this is to cluster data into a higher-level view where smaller groups of data become visible. By grouping the data together, or “binning,” you can more effectively visualize the data. 3.5 Dealing with outliers The graphical representations of data made possible by visualization can communicate

Group Assignment a. Discuss the two data mining methodologies The process of going through massive sets of data looking out for unsuspected patterns which can provide us with advantageous information is known as data mining. With data mining, it is more than possible or helping us predict future events or even group populations of people into similar characteristics. Cross Industry Standard Process for Data Mining (CRISP-DM) is a 6-phase model of the entire data mining process which is commonly used

2.2 Data Mining in Authorship Collaboration Nowadays, data mining in authorship collaboration gaining interest and demand among the researchers. Data mining techniques have been applied successfully in many areas from traditional areas such as business and science (Fu, 1997). A lot of organizations now employ data mining as a secret weapon to keep or gain competitive edge. The application of data mining techniques is becoming increasingly important in modern organizations that seek to utilize the

United Parcel Company (UPS) which is a logistics company takes many uses of big data. UPS have been tracking package movement and transaction information since 1980s. Currently the company tracks over 16.3 million packages of 8.8 million customers per day. Company takes up about 16 petabytes of data. Big data gets gathered from sources such as UPS transportation trucks that include truck speed, direction, braking, drive train performance, fuel levels etc. UPS consist of the world’s largest operations

Abstract Big data is everywhere. Big data revolution is creating paths to collect and analyze information of varying sizes, types and volume. It’s not only used in sectors like marketing, sales and product development. The potential use of big data is also spread to HR and Finance which help in finding new insights and strategic decision making. With big data, HR has exceptional opportunities to become more data driven analytical and strategic in the way it obtains talent. Utilizing the power of

Data Science vs Statistics Data science is one of the rapidly emerging trends in computing and is a vast multi-disciplinary area. Data science combines the application of subjects namely computer science, software engineering, mathematics and statistics, programming, economics, and business management. Data science is based on the collection, preparation, analysis, management, visualization and storage of large volumes of information. Data science in simple terms can be understood as having strong

a) The single most important and crucial reason for implementing data protection strategies can be described as the fear of financial losses. Data is always recognized as an important corporate asset that must be protected to greater extent. Loss of information can lead to direct financial losses which can be directly harmful to the company, such as loss of sales, fines or monetary judgments. It can also cause many indirect losses from the consequences of a drop in the confidence and trustworthiness

The data protection act 1998 can affect John Lewis company when they are using data and secondary information from the internet. So for instance if John Lewis uses any information from the internet, this could result in them breaching Data Protection Act meaning they could get into big trouble and face severe consequence. One of the staff in John Lewis has to follow the data protection act when doing questionnaires such as asking customers and receiving the answers, however if they spread customer’s

What is Big Data and how does it impacts social media? The advent of time and technology has brought greater significance to the use of data. The cut throat competition among businesses today requires them to harness a huge amount of information for their advantage. It has become important for businesses to extract and analyze crucial data in order to gain a larger understanding of market trends and patterns. And, this examination would eventually lead to birth of plans and polices for an organization’s

Data mining enables health systems to systemically use data and analytics to identify inefficiencies and best practices that improve care and reduce costs. There needs to be an analysis of large amounts of data to discover patterns and use them to predict future events. The most effective strategy in data mining has a three step approach: Analytics incudes the expertise to gather data, make sense and standardize measurements and aggregating the data into a data warehouse. Content system systematically