Finding Manan A Memoir Of A Cuban Exodus Essay - 1850 Words

From April 15 to October 31 in 1980, over 125,000 Cuban migrants arrived in the United States. Family members from America ferried relatives and institutionalized Cubans from the Cuban port of Mariel, in what was soon coined the Mariel Boatlift. Mirta Ojito, one of these ‘Marielitos’, as they soon were termed, grew up to write â€Å"Finding Maà ±ana: A Memoir of a Cuban Exodus†. In this text, the author provides a historic account of events leading up to the Mariel Boatlift, narratives from important figures surrounding the event, and a personal narrative describing the struggle of her family to gain freedom from the socialist dictatorship of Fidel Castro. Throughout the story of the years preceding the boatlift and the influence that living in Cuba held on her life, Ojito describes the positive and negative elements of the both the political climate and personal life on the communist island which led to her eventual emigration to the United States. The choice made by the author and her family to leave Cuba stems from the many negative aspects of life due to the communist revolution. Many of the reasons for Mirta’s family to seek emigration arose from the harmful political impact that the rise of Fidel Castro created, which propagated to adversely affect their personal lives. Ojito mentions the opinion about island politics which her parents held as early as the prologue. Her parents never believed, even before Fidel’s rise, that â€Å"A thirty-three-year-old in dirty fatigues and a

Two Viewpoints Dealing with the Interpretation of...

There generally are two viewpoints that exist when dealing with the interpretation of mythology in present day. The first, that mythology is a good thing, that it spreads culture and that the belief that they were created to comfort the ignorant is completely false. The other, which myths, while having their uses, have no place in a modern society such as the one we live in. I personally believe in the latter. I will explain my beliefs by first explaining why myths came about in the first place, and why we do not need myths anymore to accomplish those goals. A well-accepted hypothesis is that myths came up as a source of explanation for when there is no explanation available and, as people fear the unknown, myths came up to explain these uncertainties away. However, in the age of modern science, most everything in the universe can now be explained. Spiders don’t weave webs because a temperamental goddess was angry at a weaver, they do so to capture prey and eat them. Many counter this argument by saying the actual, scientific explanations are often cold and uninteresting in comparison to the stories that could have been drummed up in their stead, but I steadfastly disagree. Once one starts to understand that the unknown world is greater than what the human mind could possibly understand and comprehend, once one starts truly hearing the rhythm of the world, it is then when the truth becomes more interesting than fiction. To cover up these unknowns with tales of fantasy isShow MoreRelated Why Creationism Should Not Be Taught in Public Schools Essays1921 Words   |  8 Pagescurriculum in schools. Despite an overwhelming number of individuals in favor of teaching creationism in public education, science classes should refrain from becoming a discussion of religious belief. 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Data Warehouses, Decision Support and Data Mining free essay sample

This paper provides an overview of data warehousing and OLAP technologies by using back end tools for extracting, cleaning and loading data into a data warehouse; multidimensional data models typical of OLAP; front end client tools for querying and data analysis; server extensions for efficient query processing, with an emphasis on Applications for Data Warehouses such as Decision Support Systems (DSS), On-Line Analytical Processing (OLAP) and Data Mining to deliver advanced capabilities. Contents 1. Introduction 2. Data Warehousing Architecture and End-to-End Process 3. Decision support Back End Tools and Utilities 4. Conceptual Model and Front End Tools 5. OLTP Database Design Methodology 6. Data Mining a. Goals of Data Mining b. Data Mining Applications c. Standard data mining process d. CRISP-Data Mining process 7. Phases in the DM Process: CRISP-DM 8. Conclusion 9. References Chapter 1 Introduction Data warehousing is a collection of decision support technologies, aimed at enabling the knowledge workers such as executive, manager, analysts to make better and faster decisions. Data warehousing technologies have been successfully deployed in many industries such as manufacturing for order shipment and customer support, retail for user profiling and inventory management, financial services for claims analysis, risk analysis, credit card analysis, and fraud detection, transportation (for fleet management), telecommunications (for call analysis and fraud detection), utilities (for power usage analysis), and healthcare (for outcomes analysis). This paper presents a roadmap of data warehousing technologies, focusing on the special requirements that data warehouses place on database management systems (DBMSs). A data warehouse is a â€Å"subject-oriented, integrated, time- varying, non-volatile collection of data that is used primarily in organizational decision making. † Typically, the data warehouse is maintained separately from the organization’s operational databases. There are many reasons for doing this. The data warehouse supports on-line analytical processing (OLAP), the functional and performance requirements of which are quite different from those of the on-line transaction processing (OLTP) applications traditionally supported by the operational databases . OLTP applications typically automate clerical data processing tasks such as order entry and banking transactions that are essential day-to-day operations of an organization. These tasks are structured and repetitive, and consist of short, atomic, isolated transactions. The transactions require detailed, up-to-date data, and read or update a few (tens of) records accessed typically on their primary keys. The size of Operational databases ranges from hundreds of megabytes to gigabytes in size. Consistency and recoverability of the database are critical, and maximizing transaction throughput is the key performance metric. Consequently, the database is designed to reflect the operational semantics of known applications, and, in particular, to minimize concurrency conflicts. Data warehouses, in contrast, are targeted for decision support. Historical, summarized and consolidated data is more important than detailed, individual records. Since data warehouses contain consolidated data, perhaps from several operational databases, over potentially long periods of time, they tend to be orders of magnitude larger than operational databases; enterprise data warehouses are projected to be hundreds of gigabytes to terabytes in size. The workloads are query intensive with mostly ad hoc, complex queries that can access millions of records and perform a lot of scans, joins, and aggregates. Query throughput and response times are more important than transaction throughput. To facilitate complex analyses and visualization, the data in a warehouse is typically modeled multidimensionally. For example, in a sales data warehouse, time of sale, sales district, salesperson, and product might be some of the dimensions of interest. Often, these dimensions are hierarchical; time of sale may be organized as a day-month-quarter-year hierarchy, product as a product-category-industry hierarchy. Many organizations want to implement an integrated enterprise warehouse that collects information about all subjects (e. g. , customers, products, sales, assets, personnel) spanning the whole organization. However, building an enterprise warehouse is a long and complex process, requiring extensive business modeling, and may take many years to succeed. Some organizations re settling for data marts instead, which are departmental subsets focused on selected subjects (e. g. , a marketing data mart may include customer, product, and sales information). These data marts enable faster roll out, since they do not require enterprise-wide consensus, but they may lead to complex integration problems in the long run, if a complete business model is not developed. Data Mining may be viewed as automated search procedures for discovering c redible and actionable insights from large volumes of high dimensional data. Often, there is emphasis upon symbolic learning and modeling methods (i. . techniques that produce interpretable results), and data management methods (for providing scalable techniques for large data volumes). Data Mining employs techniques from statistics, pattern recognition, and machine learning. Many of these methods are also frequently used in vision, speech recognition, image processing, handwriting recognition, and natural language understanding. However, the issues of scalability and automated business intelligence solutions drive much of and differentiate data mining from the other applications of machine learning and statistical modeling. Chapter2 Data Warehousing Architecture and End-to-End Process Figure 1. Data Warehousing Architecture It includes tools for extracting data from multiple operational databases and external sources; for cleaning, transforming and integrating this data; for loading data into the data warehouse; and for periodically refreshing the warehouse to reflect updates at the sources and to purge data from the warehouse, perhaps onto slower archival storage. In addition to the main warehouse, there may be several departmental data marts. Data in the warehouse and data marts is stored and managed by one or more warehouse servers, which present multidimensional views of data to a variety of front end tools: query tools, report writers, analysis tools, and data mining tools. Finally, there is a repository for storing and managing metadata,and tools formonitoring and administering the warehousing system. The warehouse may be distributed for load balancing, scalability, and higher availability. In such a distributed architecture, the metadata repository is usually replicated with each fragment of the warehouse, and the entire warehouse is administeredcentrally. Analternative architecture, implemented for expediency when it may be too expensive to construct a single logically integrated enterprise warehouse, is a federation of warehouses or data marts, each with its own repository and decentralized administration. Chapter 3 Decision support Back End Tools and Utilities Data warehousing systems use a variety of data extraction and cleaning tools, and load and refresh utilities for populating warehouses. Data extraction from â€Å"foreign† sources is usually implemented via gateways and standard interfaces (such as Information Builders EDA/SQL, ODBC, Oracle Open Connect, Sybase Enterprise Connect, Informix Enterprise Gateway). Data Cleaning Since a data warehouse is used for decision making, it is important that the data in the warehouse be correct. However, since large volumes of data from multiple sources are involved, there is a high probability of errors and anomalies in the data.. Therefore, tools that help to detect data anomalies and correct them can have a high payoff. Some examples where data cleaning becomes necessary are: inconsistentfield lengths, inconsistentdescriptions, inconsistent value assignments, missing entries and violation of integrity constraints. Not surprisingly, optional fields in data entry forms are significant sources of inconsistent data. Load After extracting, cleaning and transforming, data must be loaded into the warehouse. Additional preprocessing may still erequired:checkingintegrityconstraints;sorting; summarization, aggregation and other computation to build the derived tables stored in the warehouse; building indices and other access paths; and partitioning to multiple target storage areas. Typically, batch load utilities are used for this purpose. In addition to populating the warehouse, a load utility must allow the system administrator to monitor status, to cancel, suspend and resume a load, and to restart after failure wit h no loss of data integrity. The load utilities for data warehouses have to deal with much larger data volumes than for operational databases. There is only a small time window (usually at night) when the warehouse can be taken offline to refresh it. Sequential loads can take a very long time, e. g. , loading a terabyte of data can take weeks and months! Hence, pipelined and partitioned parallelism are typically exploited . Doing a full load has the advantage that it can be treated as a long batch transaction that builds up a new database. While it is in progress, the current database can still support queries; when the load transaction commits, the current database is replaced with the new one. Using periodic checkpoints ensures that if a failure occurs during the load, the process can restart from the last checkpoint. Refresh Refreshing a warehouse consists in propagating updates on source data to correspondingly update the base data and derived data stored in the warehouse. There are two sets of issues to consider: when to refresh, and how to refresh. Usually, the warehouse is refreshed periodically (e. g. , daily or weekly). Only if some OLAP queries need current data (e. g. , up to the minute stock quotes), is it necessary to propagate every update. The refresh policy is set by the warehouse administrator, depending on user needs and traffic, and may be different for different sources. Refresh techniques may also depend on the characteristics of the source and the capabilities of the database servers. Extracting an entire source file or database is usually too expensive, but may be the only choice for legacy data sources. Most contemporary database systems provide replication servers that support incremental techniques for propagating updates from a primary database to one or more replicas. Such replicationservers can be usedto incrementally refresh a warehouse when the sources change. There are two basic replication techniques: data shipping and transaction shipping. In data shipping (e. g. , used in the Oracle Replication Server, Praxis OmniReplicator), a table in the warehouse is treated as a remote snapshot of a table in the source database. After_row triggers are used to update a snapshot log table whenever the source table changes; and an automatic refresh schedule (or a manual refresh procedure) is then set up to propagate the updated data to the remote snapshot. In transaction shipping (e. g. , used in the Sybase Replication Server and Microsoft SQL Server), the regular transaction log is used, instead of triggers and a special snapshot log table. At the source site, the transaction log is sniffed to detect updates on replicated tables, and those log records are transferred to a replication server, which packages up the corresponding transactions to update the replicas. Transaction shipping has the advantage that it does not require triggers, which can increase the workload on the operational source databases. However, it cannot always be used easily across DBMSs from different vendors, because there are no standard APIs for accessing the transaction log. Such replication servers have been used for refreshing data warehouses. However, the refresh cycles have to be properly chosen so that the volume of data does not overwhelm the incremental load utility. In addition to propagating changes to the base data in the warehouse, the derived data also has to be updated correspondingly. The problem of constructing logically correct updates for incrementally updating derived data (materialized views) has been the subject of much research . For data warehousing, the most significant classes of derived data are summary tables, single-table indices and join indices. Chapter 4 Conceptual Model and Front End Tools A popular conceptual model that influences the front-end tools, database design, and the query engines for OLAP is the multidimensional view of data in the warehouse. In a multidimensional data model, there is a set of numeric measures that are the objects of analysis. Examples of such measures are sales, budget, revenue, inventory, ROI (return on investment). Each of the numeric measures depends on a set of dimensions, which provide the context for the measure. For example, the dimensions associated with a sale amount can be the city, product name, and the date when the sale was made. The dimensions together are assumed to uniquely determine the measure. Thus, the multi-dimensional data views a measure as a value in the multidimensional space of dimensions. Each dimension is described by a set of attributes. For example, the Product dimension may consist of four attributes: the category and the industry of the product, year of its introduction, and the average profit margin. Figure2 Another distinctive feature of the conceptual model for OLAP is its stress on aggregation of measures by one or more dimensions as one of the key operations; e. g. , computing and ranking the total sales by each county (or by each year). Other popular operations include comparing two measures (e. g. , sales and budget) aggregated by the same dimensions. Time is a dimension that is of particular significance to decision support (e. g. , trend analysis). Often, it is desirable to have built-in knowledge of calendars and other aspects of the time dimension. Front End Tools The multidimensional data model grew out of the view of business data popularized by PC spreadsheet programs that were extensively used by business analysts. The spreadsheet is still the most compelling front-end application for OLAP. The challenge in supporting a query environment for OLAP can be crudely summarized as that of supporting spreadsheet operations efficiently over large multi-gigabyte databases. One of the popular operations that aresupportedbythemultidimensional spreadsheet application is pivoting. Consider the multidimensional schema of Figure 2 represented in a spreadsheet where each row corresponds to a sale . Let there be one column for each dimension and an extra column that represents the amount of sale. The simplest view of pivoting is that it selects two dimensions that are used to aggregate a measure, e. g. , sales in the above example. The aggregated values are often displayed in a grid where each value in the (x,y) coordinate corresponds to the aggregated value of the measure when the first dimension has the value x and the second dimension has the value y. Thus, in our example, if the selected dimensions are city and year, then the x-axis may represent all values of city and the y-axis may represent the years. The point (x,y) will represent the aggregated sales for city x in the year y. Thus, what were values in the original spreadsheets have now become row and column headers in the pivoted spreadsheet. Other operators related to pivoting are rollup or drill-down. Rollup corresponds to taking the current data object and doing a further group-by on one of the dimensions. Thus, it is possible to roll-up the sales data, perhaps already aggregated on city, additionally by product.

Smoking Culture in Society

Smoking culture refers to the practice of smoking tobacco by people in the society for the sheer satisfaction and delight it offers (Matsumoto Juang 31). Smoking is an activity that is practiced by both men and women within different societies. The smoking activity is aimed at achieving the â€Å"good feeling† that results from stimulation by nicotine.Advertising We will write a custom essay sample on Smoking Culture in Society specifically for you for only $16.05 $11/page Learn More The smokers do not have a bad agenda behind the smoking. Smoking culture is distinct from the common â€Å"bad boy† smoking habit in that in the latter, people smoke so as to feel confident whenever they want to go against the accepted behavioral codes of the society, by creating a false feeling of being tough and able (White 45). In smoking culture, people simply smoke for the elegance of the act. Smoking culture is a preferred and generally accepted cultural pattern within the population, which is widely spread among the members of that society (Danesi 166). The smoking culture is widely accepted and embraced in the society because of the various benefits it offers to that society. This paper is therefore an in-depth analysis of the smoking culture as an example of pop-culture by looking at the way it has found its way in the society. Further, in the paper the benefits as well as the impacts of smoking culture will also be discussed among other issues related to the smoking culture. The smoked tobacco comes in two similar, yet broadly different forms, which are cigars and cigarettes. A pipe is used by so-called â€Å"gentlemen† as a tool to facilitate the smoking. Cigars are different from cigarettes. A cigar refers to a roll of dried and well-fermented whole tobacco leaves while a cigarette is made by wrapping finely cut tobacco leaves, generally referred to as the tobacco powder. The cigarettes are further classified into thre e main categories, including filtered, non-filtered, and electronic cigarettes. A cigar holds more appeal to those seeking bigger esteem and a ‘classy’ feeling about themselves. The smoking culture finds its ways to the roots of the society through various ways. The main channel through which smoking culture spreads throughout the society is by direct observation and imitation (Hilton, 121). Since this culture has been an accepted pattern in the lifestyle of the society, the current generation copies the habit from the preceding one.Advertising Looking for essay on cultural studies? Let's see if we can help you! Get your first paper with 15% OFF Learn More The copying and imitating is repeated by every generation and thus the act becomes fully integrated in that society’s set up. The onset of the internet has also increased the means of spreading this culture from one generation to another. The younger generation is exposed to materials that contain images and videos of people who smoke (Shechter 102). Therefore, it becomes easier for them to learn these habits from other people all over the world. Smoking culture is healthy among those who do it responsibly (Rafferty Mann 141). The nicotine found in the cigarette smoke gives the smokers a feeling of stimulation. The stimulation causes blood to circulate at a faster rate and pressure, which leads to a feeling of being awake and active. This feeling can be helpful in making appropriate decisions when faced with a dilemma. In addition, smoking causes a feeling of relaxation and comfort hence reducing depression. In other societies such AS among the Indians, pipe smoking is a way of showing ‘class’ and ability in terms of wealth. It is therefore a unique act used by the rich people to distinguish themselves from the crowd (Matsumoto Juang164). Smoking culture provides a complementary item that is used to create a feeling of satisfaction when taken with other foods and beverages. The cigar, for instance, goes very well with wines and spirits for those who drink. It also matches very well with the non-alcoholic coffee such as Nescafe, when the two are taken together. Smoking therefore makes meals more enjoyable and improves the taste of food. According to Fedorak, a cigar like Cohiba Esplendido is usually a â€Å"great smoke† after a meal of roast meat (Hilton 212). Smoking has its health benefits. Although it has been scientifically proven that cigarette smoke causes cancer when poorly taken, the cigarette smoke can also be used to prevent or cure some fatal diseases. It is a proven fact that cigarette smoke repels insects, and thus when used, it lowers the risk of contracting common fatal diseases caused by the insects.Advertising We will write a custom essay sample on Smoking Culture in Society specifically for you for only $16.05 $11/page Learn More For instance, the cigarette smoke repels the Nile West worm, which causes the Stichis Encephatiasis disease (Rafferty Mann 118). Furthermore, the nicotine found in tobacco causes a feeling of relaxation and consequently helps to lower high blood pressure. Cigarette smoking therefore reduces the risk of developing health problems such as heart attack and stroke. Smoking is used as a way of recreation during leisure time. This can be done at individual or group levels. The act of smoking helps the smokers to utilize their free time. Therefore, the engagement in smoking prevents the smokers from doing other destructive activities. Statistics show that the act of smoking helps to reduce excessive energy. The engagement and physical activity consumes some energy while the cigarette smoke burns excessive fats in the body (Hilton 89). Smoking culture is also a source of income for the government. According to statistics, the New York state has the highest cigarette taxes in the US, and thus the populous state provides a good avenue for collec ting a measurable amount of taxes. In most countries, the tax rates on tobacco products are ever reviewed upwards, and this does not affect the demand. The funds collected as tax are then used by the government to finance important public projects such as improvement of infrastructure. According to economists, the smoking industry is very important in soaking up the excessive wealth from individuals. The smokers spend their income in a â€Å"Pyramid† pattern (Rafferty Mann 305). The excessive wealth spend on purchasing the cigars and cigarettes forms part of the taxes levied by the government on tobacco products. The smoking industry is therefore a necessary medium through which the government distributes wealth amongst the citizens. Similarly, the smoking industry provides employment and income for its workers. Wages and profits are essential elements in any economic set up in boosting the GDP.Advertising Looking for essay on cultural studies? Let's see if we can help you! Get your first paper with 15% OFF Learn More According to a research done by Philip Morris about the lighter side of smoking in the Czech Republic, early deaths of smokers helps the government reduce the burden of providing them with care and essential services in their later years of life (Deflem 114). The smoking culture is also important in building the culture of a society. It is tied to other forms of art such as in music, movies, and literature as a cultural attribute. As early as the 9th century, paintings of early arts of smoking were depicted in the Mayan pottery (Rabin Sugarman 198). Rulers or deities were depicted while smoking. The pipe smoking which was common in the 19th century was a symbol of power, wealth, and authority. The pipe was a sign for calmness and thoughtfulness while the cigarette symbolized youthfulness and modernity. In the movie industry, frequent smoking was used to depict the characters mystique sensation. The super heroes are portrayed to attain what seems impossible with cigarettes in their hands. The smoking culture therefore is essential in building up the overall culture of a society. In the modern society, smoking has penetrated and become prevalent among the younger generation of most countries. There is a feeling among the young generation that smoking bestows their life’s certain importance, and it is a rich source of recreation in times of dilemma (Danesi, 52). The younger generation has developed a belief that smoking builds confidence in them, and thus enables them to do â€Å"mighty† things, which could have otherwise been impossible. This high level of confidence increases productivity among the younger generation. Smoking is also important in creating and strengthening the social bonds between members of a society and between other societies (Deflem 224). The smoking groups generally make up well-bound units of the society. There is increased interactions amongst the members of the society through group smoking activities, and as the members borrow and exchange cigars and cigarettes among themselves. This has an effect of creating and maintaining friendly relationships among the individual members. In addition, the smoking activities can be taken as recreation events, which provide good grounds for social interactions. As a result, the unity in the society is boosted. The smokers have a common unifying object, which they claim to collectively own: the cigarette. As mentioned earlier, smoking can lead to fatal health diseases such as cancer. There are several types of cancers can develop from the inhaled cigarette smoke such as lung cancer, mouth cancer as well as cancer of the throat (Rafferty Mann 256). However, responsible smoking can help the smokers to evade these fatal illnesses. According to the cancer organization, a social smoker who does not more than five cigarettes a week, or not more than one cigar a day, and he or she does not inhale the smoke, has very little exposure to the health risk. Since the smoke i s not inhaled, it does not reach the delicate lung tissues, and therefore the individual becomes less susceptible to the mostly common lung cancer. As noted above, careless smoking can lead to serious health hazards. It can lead to illnesses such as coronary heart disease, lung cancer, mouth cancer, and severe problems regarding throat, bladder, kidney, and pancreas, which can become very severe until there is no cure. However, controlled smoking can greatly reduce the risk of developing these health problems to nearly zero. First, the smokers should not inhale the cigarette smoke. They should also try to avoid the unfiltered cigarettes, which directly allow passage of harmful chemical substances from the cigarette. The government should also formulate and enforce laws that govern the smoking industry (Rabin Sugarman 154). The smoking culture is therefore a very important element in every society (Hilton 321). It has several advantages as discussed above. It is a source of satisfac tion and gives the smokers a â€Å"classy† feeling. It is also of paramount importance in making improving the tastes of some foods such as roast meat and beverages such wines and spirits. The smoking culture is essential in forming some basic society units of smokers, and therefore serves to create new bonds and strengthen existing ones among the members of the society. However, careless smoking can lead to fatal health problems, which can eventually lead to deaths as pointed out. It is therefore upon the smokers to control their smoking habits so as to enjoy the â€Å"good† feeling achieved while smoking (Rabin Sugarman 97). The youth should also be provided with adequate information to monitor their smoking habits, rather than letting them smoke secretly and blindly. This way, the society will be composed with people who smoke responsibly without bringing about any harm to the society. Works Cited Danesi, Marcel. Popular Culture: Introductory Perspectives. Lanham, Md: Rowman Littlefield, 2008. Print. Deflem, Mathieu. Popular Culture, Crime and Social Control. Bingley: Emerald, 2010. Print. Hilton, Mathew. Smoking in British popular culture, 1800-2000: Perfect pleasures. New York: Manchester University Press, 2000. Print. Matsumoto, David, Juang, Patrick. Culture and psychology. Belmont, CA: Wadsworth, 2013. Print. Rabin, Rose, Sugarman, Stephen. Smoking policy: Law, politics, and culture. Oxford: Oxford university press, 1993. Print. Rafferty, Smith, Mann, Raphael. Smoking and culture: The archaeology of tobacco pipes in eastern north America. Knoxville: The University of Tennessee press, 2004. Print. Shechter, Richard. Smoking, culture and economy in the Middle East: The Egyptian tobacco market 1850-2000. London: Tauris, 2006. Print. White, Davis, Billings, John. The well-crafted argument: A guide and reader. Boston, MA: Wadsworth Cengage Learning, 2011. Print. This essay on Smoking Culture in Society was written and submitted by user Braelynn Rose to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly. You can donate your paper here.