responsible leaders” (Florida Catholic University). Using data effectively and efficiently is the moral responsibility of Saint Leo Alumni for our students and community. In order to be effective and efficient one must be able to recognize different types of data and be able to determine the need and meaning behind the numbers. Before interpreting different types of data, remember that data refers to a group of information that one can analyze. Data can range from a gender ratio to scores of an individualized
The topics featured in Gandy’s article focuses on the notion of “racially coded data” (1) and how the data is translated into information that may or may not be put to the greatest use. Meaning that targeting certain races with a number of issues with the intention of aiding them, May actually cause more harm than help. He tries to argues that “racial statistics have not only come to represent the distribution of life chances in ways that continue to place African Americans down the bottom of the
Introduction Big Data is a term used to refer to extremely large and complex data sets that have grown beyond the ability to manage and analyse them with traditional data processing tools. However, Big Data contains a lot of valuable information which if extracted successfully, it will help a lot for business, scientific research, to predict the upcoming epidemic and even determining traffic conditions in real time. Therefore, these data must be collected, organized, storage, search, sharing in
responsible leaders” (Florida Catholic University). Using and creating opinions on data leaves one vulnerable to data fraud and other unethical qualms. In order to uphold the integrity and core value of “Excellence” we must be sure to provide accurate and honest representations of data that are provided. When looking at the data from the following chart, one can appreciate how many different analyses can be made. Data Set Nominal, Ordinal, Interval Discrete, Continuous Audience Teacher Gender Male-
Comparing Data As a piece of Statistics coursework, I have decided to compare two items of data, in order to prove, or disprove my theory: "A country's position in the Commonwealth games varies accordingly to that country's population size." My theory is that a country's position in something such as the Olympics or Commonwealth Games is proportional to that country's population size. I say this because I believe that if a country has a large population, there will be more potential
Data Normalization Data normalization is an important step in any database development process. Through this tedious process a developer can eliminate duplication and develop standards by which all data can be measured. This paper addresses the history and function of data normalization as it applies to the course at hand. In 1970, Dr. E.F. Codd's seminal paper "A Relational Model for Large Shared Databanks" was published in Communications of the ACM. This paper introduced the topic of data
by the customer is called: digital data or digital information, which is simply any kind of information in digital format. Digital data can be public or private, it can be kept by the government, banks, medical providers, and other institutions; as well as a freely available in the internet in websites like myspace.com, facebook, LinkedIn, etc. The use of digital data has increased over the years rapidly. Few years ago, the most significant piece of digital data, and sometimes the only one, a person
1. The difference between Information and Data are as follows: Data can be considered as raw and unorganized particulars. Data has little to no meaning when observed and can be something simple and seemingly random and useless, but can achieve meaning if sorted and organized. Data can be in the form of numbers, characters, symbols, or even pictures. Information can be considered as organized data. This means that data has to be processed, arranged, systematized or presented in a given perspective
Data privacy refers to the sensitive information that individuals, organizations or other entities would not like to expose to the external world. For example, medical records can be one kind of privacy data. Privacy data usually contain sensitive information that is very important to its owner and should be processed carefully. Data privacy is not equal to data security. Data security ensures that data or information systems are protected from invalid operations, including unauthorized access,
But social-media data are fundamentally unstructured—that’s what makes it so fascinating and so hard to evaluate. There is no tagging structure that allows us to make sense of social-media data through systematic tools. We already know that any effort at scrutinizing this data on a social scale is not even plausible. Gone are the days when we could hire a college student to watch a Twitter feed and retort to consumers in real time. What are the Advantages of Big Data? Big data technology deals noteworthy
Mark Benioff of Salesforce.com once said, "The world is being re-shaped by the convergence of social, mobile, cloud, big data, community and other powerful forces. The combination of these technologies unlocks an incredible opportunity to connect everything together in a new way and is dramatically transforming the way we live and work." These are powerful words and so true of the world that we currently live in. Still, I also understand how hard it is to let go of the world we once lived in and
a greater outcome and new organizational capabilities. Big data and data analytics are one of those important factors that contribute to a successful company and their updated software and information systems. What are Big Data and Data Analytics? You may ask what big data analytics is. Well according to SAS, the leading company in business analytics software and services describes big data analytics as “the process of examining big data to uncover hidden patterns, unknown correlations and other
be generating large amount of complex data ranging from different entities including patients , hospitals resources, disease records etc. Recently, there has been tremendous increase in the application of informatics to health care which is defined as science of information, the practice of information processing, and the engineering of information systems The growing adoption of information technologies in healthcare and the availability of more patient data and related healthcare variables provide
Introduction As data remains one of the most important aspects of every business, companies are gradually placing lots of importance on the quality of data used. Databases use different formats or styles. This can make the data collected to be extremely clumsy and sometimes unintelligible. Inaccurate or incomplete data records are not of use to anyone, and we cannot control the way data is stored in the databases. Therefore, the best solution to having an organized data is to apply a process called data cleansing
quantitative data and relevant business intelligence, is available to businesses and business partners. This new form of information is known as “big data,” which according to Viktor Mayer-Schonberger and Kenneth Cukier is not merely the ownership of large amounts of data, but also the “ability of society [including businesses] to harness information in novel ways to produce useful insights or goods and services of significant value.” A key example given by Cukier and Mayer in their book Big Data, is the
Statistics is the universal language behind data-enabled decision making and is widely used in our daily lives. Statistical analyses’ applications range from Google’s development choices to political parties’ campaign strategies. With the emergence of Data Science, Sports Analytics has also become an important industry. Today, almost all professional sports organizations are using data analytics to guide decision making on everything from player selection to marketing technique. As a result, there
The accuracy of data input is important within means of a business. Printed questionnaires are great for ideas of improvement and the quality of performance received from the company. Restaurants use printed questionnaires for complaints and suggestions from the customers. This is a wonderful way of accomplishing better service and reliable customers. It is also used by sensors to determine how many people are living in your home; this in turns allows them to determine how many people live in ones
Data Encryption I. What is Data Encryption? Data encryption describes the transformation of plain text into a different format that is meaningless read by human eye without being decrypted, so called cipher text, in order to prevent any unauthorized party to obtain information from the document. According to the Webster dictionary, “cryptography is the practice and study of data encryption and decryption - encoding data so that it can only be decoded by specific individuals.” Crypto is
Granular data is the lowest level that a data can be or how defined and detail-oriented the data is.1 In this scenario, the PI of the research study wants only a tally of the number of sessions each patient participated to confirm that they received the correct “dose” of the intervention. However, according to the study protocol, each patient in the intervention group is supposed to receive a total of 24 sessions over 3 months, occurring twice a week. Based on this protocol, collecting the “granular”
Abstract:- This paper presents a brief idea about data mining, data mining technology, and big data. The applications regarding data mining will also be discussed briefly. The main cause of data mining is to get different ideas, how to access big data by different tools. Keywords- data mining, data mining technology, big data. I.INTRODUCTION Data mining refers to the use of data from big data source by using different tools in order to solve real time problems that include logistics management