Feminism in Sor Juana Essay - 1191 Words

Feminism in Sor Juana In Estela Portillo Trambley’s play Sor Juana the main character Sor Juana Ines de la Cruz was considered to be one of the earliest feminists. Sor Juana’s eternal struggles to study and unshakable craving for knowledge and wisdom, from whatever source it may be, support this attribute. In my opinion however, there are also significant elements of the play that suggest that Sor Juana would not be considered a true feminist. Of these reasons, there are three major ones that I will analyze. The first reason is that Sor Juana gave up her struggle for the acquirement of knowledge from books and settled for reading from religiously accepted writing, essentially giving up what she had been originally fighting for†¦show more content†¦This whole progression of events is evidence that Sor Juana was never a true feminist. Although she was an assertive and determined young woman earlier in life, Sor Juana learned to accept the way the world was, abandoned what feminist ide als she had had, and devoted her later life to pleasing God and being a good nun. Sor Juana Ines de la Cruz, as portrayed in Trambley’s play is only concerned with her own desires. She never shows interest in other women’s rights and she never speaks to other women about the idea of equal rights. She does not encourage her fellow females to fight to attend colleges and learn. It is like to Sor Juana, there is no such thing as another woman who desires the same things as she. To me this limits the extent to which Sor Juana could be called a feminist. She never, in any way, attempted to fight for the rights of anyone beside herself, and for no thing besides the freedom to study and become learned. It is much more applicable to refer to Sor Juana as one of the first in a sort of evolutionary linearity of what finally became feminism. At the low end of the evolutionary spectrum are characters like Sor Juana. She was forthright and assertive about what she desired, but she lacked the ability or means to organize or extend her struggle to any topic area that did not directly interest her. When Sor Juana says, â€Å"My journeyShow MoreRelatedThe Influences of Sor Juana and Julia de Burgos2050 Words   |  9 PagesInfluences of Sor Juana and Ju lia de Burgos Most every human being has encountered a time in their life when he or she has felt suppressed. However, not every person has stood up against the people and forces that have kept them oppressed. It takes a truly extraordinary person to stand up for their self and to take a stand for the greater good of others. According to Clare Booth Luce: â€Å"courage is the ladder on which all the other virtues mount.† The Mexican writer, Sor Juana Ines deRead More I, the Worst of All Essay2686 Words   |  11 Pagesxxiii) Lerners words hold true for two women involved in the film I, the Worst of All. Both of them had to reinvent the wheel and show their male contemporaries that women can and will find their way out from under the control of patriarchy. Juana Ines de la Cruz and Maria Luisa Bemberg are separated by three centuries of continuous strife for feminists to affirm feminine subjectivity and feminine values. The struggle was/is doubly difficult because of what they have to face. At the time of

Boeing Organizational Strategy Free Essays

Every company has a certain way that they organize their company. No two companies are run the same or organized the same way. Boeing also has a unique organization strategy. We will write a custom essay sample on Boeing Organizational Strategy or any similar topic only for you Order Now It is broken up into eight divisions. They are as follows: communications; engineering, operations and technology; finance; government operations; human resources and administration; internal governance; international; and law department. Below is a description of all of the different departments and their purposes. Communications The communications department is in charge of communications between the company and what it refers to as it’s â€Å"stakeholders.† Stakeholders are anyone who has anything to lose or gain from Boeing. Employees, customers, shareholders could all be considered stakeholders. The goal of the communications department is to make sure that the stakeholders hear news about Boeing from them directly, and not from a third party orginazation. Engineering, Operations and Technology The engineering, operations and technology department is responsible for the mechanical part of the Boeing company. They are responsible for ensuring that the products they produce are up to industry standard and represent the company in the way the Boeing wishes to be represented. They are also responsible for managing any technology investments that Boeing may have around the world. Finance The financial department of Boeing is mainly responsible for the monetary side of the company. They keep track of the company’s finances and are in charge of conducting the business that needs to be accomplished. Some of their responsibilities include paying the bills, and collecting on debts when necessary, auditing other departments to ensure accuracy in all financial records and setting budgets for all departments to ensure that the company will continue to prosper. Government Operations The government department is mainly responsible for ensuring that all of the products that Boeing produces and their emissions, the factory emissions, and all things about Boeing are abiding by the law. Human Resources and Administration Human resources and administration is in charge of ensuring that the employees of Boeing are taken care of and that laws are followed when it comes to labor laws and labor unions. Human resources is in charge of hiring people to operate factories and management for the companies. International The international department is in charge of the international aspect of Boeing. They are to ensure that imports and exports follow trade laws and are done correctly. The international department also oversees foreign sales and and laws and regulations that go with it. Law Department The law department is responsible for all aspects of Boeing that have to do with compliance to the laws of the land, whether that be nationally or internationally. It is comprised of lawyers and legal advisors ensuring that the letter of the law is being followed. How to cite Boeing Organizational Strategy, Essay examples

Big Data in Healthcare

Question: Discuss about the Big Data in Healthcare. Answer: Introduction Today, the concepts of big data are a vital aspect of business success; in fact, the services and solutions offered by big data are no longer optional company capabilities but necessities for the survival of big businesses and organisations. This notion is evidenced by the financial and operational edge provided by big data solutions (ATKearney 2017). Studies such as those done by the likes of Bain Company (2013), suggests that over 400 companies around the globe and with revenues of over $1 billion depend on this new technology to deliver their own services. However, what makes it suitable for businesses today as compared to other traditional methods? According to Taylor (CEO FICO) (2013), big data enables organisations to leverage on available data/information to make better decisions. Furthermore, the drive for smarter and better decisions is facilitated by customers information, which is now readily available. Now, this report assess the application of big data solutions and the services they offer to the healthcare sector while comparing them with other traditional data management systems. Through this assessment, processes used to identify big data solutions/technologies are provided as well as the impacts of the said technologies. In general, the term big data refers to data tasks or systems that manage large information assets that normal and conventional database systems are unable to handle. However, through a technical eye, big data will encompass technologies such as NoSQL, MapReduce and even Hadoop which offer solutions to the existing problems of data particularly those that have large volumes of unstructured information (Gaffney 2014). In application, two forms are used; online and offline big data systems. Online systems will have real-time support where data is created, ingested and transformed by the said system. On the other hand, offline systems will perform the same roles but in a batch mode that has an interactive output. Figure 1: Big data outline (Oracle 2013) The modern healthcare facilities and the expenditures involved have forced the industry to adopt systems that are big data driven. These technologies offer increased efficiencies in decision-making processes, which attract more economists and facilitates a rapid pace of innovation. Moreover, the healthcare sector is also guaranteed of other benefits offered by the advanced analytics seen in both online and offline big data systems. Consider the MapR Converged data platform, a platform that offers a wide range of solutions including; a united system that monitors fraud and manages resources, services that streamline system records, and integrates internet of things into the healthcare sector (McDonald 2017). Moreover, sub-components of the application such as UnitedHealthcare are already utilised by more than 51 million people and in over 6100 hospitals across America (McDonald 2017). Differences between online and offline BD system In online big data systems, the data is sourced online, therefore, creating new information. This outcome necessitates low-latency level in order to meet the user requirements more so the SLA stipulations. As an application, online big data will have a wide range of services including; product catalogues, websites, data sensors and analytics, e-commerce among many others. Examples of online big data include; MongoDB and NoSQL (Leone 2013). Offline big data, on the other hand, does not create any new data and instead will use the interactive platform to solve the problems raised by the users. Again, this outcome means they produce static (fixed) solutions that are presented as the end outputs. Therefore, they can go offline without impacting the overall goals of the systems. Examples of offline big data are Spark, Hadoop and other business intelligence tools (MongoDB 2016). Selecting a big data application System performance is always the ultimate goal of any big data application. The leadership in the healthcare sector will have little concerns over the different components of the system so long as it meets its overall objective (Regola, Cieslak Chawla 2013). Similarly, businesses and projects will emphasise on the desired outcome as compared to the elements of the applications. To meet this objective, some items are necessary and must be observed during the selection, they are: Big data platform Architecture components define the capabilities and the analysis aspects met by the big data application. In addition to this, the system architecture will determine the systems organization and functions. Therefore, the system design should come first to determine the overall outline of the big data system. As a good practice, the architecture should be able to consume myriad data sources in an efficient manner. Example: Figure 2: Big data architecture (George 2014) Storage methods Having identified the architecture, its also appropriate to select a storage system based on the size of the data and users. Online or offline system This is a critical assumption that will eventually determine the latency level, therefore, define the application delays. Furthermore, offline applications can also have in-memory solutions, which are faster, and process data at nearly real time pace (George 2014). User accessibility User integration will define the interface considered. For instance, NoSQL databases require certain interfaces to access them. Therefore, the access method should align with the tools used to develop the applications Data type Data serialisation should be considered when using an unstructured approach that includes streaming data such as that found in social media. Data serialisation will facilitate capture and representation of such data, which occurs in high velocity (Millman 2017). System integration If the big data application is set to use an already existing data warehouse, then data integration tools must be considered. As an added advantage, vendors who deal with big data platform will also provide these solutions thus provide a support for the integration process. (Modified from Nick Millman work 2017). Big Data technologies Big data analytics has expanded over the past few years to include mainstream consumers unlike before when it was used by large organisations but with minimal customer impact. Today, big data technologies are categorised based on their demand and the potential for growth. In healthcare, for instance, technologies such as those seen below are used to store and process records. Furthermore, they streamline information captured by sensors or medical machines attached to patients. These features improve examination methods such as the mapping of human genome among other many applications (Singh, Singh, Garg Mishra 2015). Technologies: Column oriented databases (COD) Due to modern volumes of data that are ever growing traditional row-oriented database systems fall short in query performance. This necessitates the importance of COD that use column modules allowing faster query time and improved data compression rates (Rodrigues 2012). NoSQL database A key big data technology that enables data documentation/storage through graph database systems. This technology is appropriate for assessment and analysis, a key practice of business management (Rodrigues 2012). Hadoop An open source platform that is used to handle big data. Moreover, its the most popular method of implementing MapReduce which among its benefits has a high flexibility to function with multiple data sources (Gill Press 2016, Rodrigues 2012). MapReduce Having highlighted it above, its a programming technique that enables users to execute scalable and massive jobs using many different servers. It will function into two steps; one mapping where inputs are converted into datasets of specific values and two, reduce where outputs are combined to form reduced sets of data (Modified from Gill Press 2016). Hive A bridge technology that allows normal BI programs to run queries using Hadoop clusters. Therefore, through its operations it enhances the reach of Hadoop platform improving its application among BI users (Rodrigues 2012). Business Impact of Big Data Information technology has revolutionised business more so by creating an extensive global market. This global marketplace has many supplier and consumers, which have produced the vast amount of information available today. In fact, the volume of data available today doubles every 18 months (IDC 2010). This flood of information is the root concept of big data, which can challenge businesses or provide considerable opportunities. Challenges of big data One of the predominate challenges with big data is poor data quality where businesses are unable to obtain accurate information based on their requirements. In fact, the price of obtaining accurate information is the actual admission fee of entering into the business market (ATKearney 2017). Moreover, when one considers the aggregate challenges that are experienced due to the quality of data, the price of business intelligence becomes significantly high which is a common problem of starting a business. Furthermore, consider other challenges that are produced by this problem; inaccurate prospects, excessive data sources that require extended time for analysis and long development time (IDG Connect 2014). Opportunities Through big data, enterprises can identify and filter customers based on their requirements. This makes the customer the heart of business thus improving the level of customer intimacy, which generally increases the customer base, and in return an organization can increase its revenue. A hospital, for instance, can increase its throughput through efficient management of customer information (ATKearney 2012). Furthermore, with big data services, an enterprise is able to utilise the vast wealth of information collected throughout the years. Unlike before, this unused data is used to produce better products and services that are focused on the customers needs. Therefore, big data increases product innovation a critical element for business survival. Finally, big data can manage business operations through assessment technologies such as those that use sensors and radio frequency identifiers (ATKearney 2017) Organisational Impact of Big Data. Big data is generally thought to improve an organisations performance, however, this impact is dependent on the organisations resources visa vie those of the application used. In some cases, the big data application may lower the productivity of an organisation if its set as the sole managerial product and not as a support mechanism (Ghasemaghaei, Hassanein Turel 2015). According to a study by McKinsey Global Institute (MGI) (2015), most organisations have zero to negative big data impact, as their analytics are limited to tests and shallow analysis in some slices of their businesses. However, in other organisations such as those in the healthcare sector big data increases operational margins by over 60 percent. In addition to this, the US healthcare sector has experienced reduced operational costs of over 8 percent through the services offered by big data especially those of data analytics and quality advancements (Court 2015). Nevertheless, an organisational impact is dictated by the strategy used to capture information that is later used for analysis. As a start, organisation transformation will start with a plan based on the demand at hand. In addition to this, cultural challenges (organisation culture) must be addressed prior to the incorporation of the new data system. This outlook will provide a positive impact on an organisation leading to success. Conclusion Big data services, solutions and technologies offer many benefits as compared to other traditional data management systems. Data analytics a defining characteristic of big data enables organisations to make better decisions that enhance business intelligence. Consider the sector highlighted, the healthcare sector, this industry has been able to forecast patient activities, which have helped them, meet the current medical demand. Today, hospitals and other clinical facilities that use big data technologies such as MapR can increase their services through efficient mechanisms, which in return have increased their throughput. Therefore, when properly selected and implemented, big data increases the overall efficiency of an organisation particularly those in the business sector. References ATKearney, 2012. Big Data and the Creative Destruction of Todays Business Models. Online. Available at: https://www.atkearney.com/documents/10192/698536/Big+Data+and+the+Creative+Destruction+of+Todays+Business+Models.pdf/f05aed38-6c26-431d-8500-d75a2c384919 ATKearney, 2017. Big Data: The Next Leading Edge in the Financial Industry. Financial institutions. Online. Available at: https://www.atkearney.com/financial-institutions/ideas-insights/featured-article/-/asset_publisher/4rTTGHNzeaaK/content/big-data-the-next-leading-edge-in-the-financial-industry/10192?_101_INSTANCE_4rTTGHNzeaaK_redirect=%2Ffinancial-institutions%2Fideas-insights Avanade, 2010. Global Survey: The Business Impact of Big Data. Online. Available at: https://www.avanade.com/~/media/asset/point-of-view/big-data-executive-summary-final-seov.pdf Court. D, 2015. Getting big impact from big data. Mckinsey Quarterly. Online. Available at: https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/getting-big-impact-from-big-data Gaffney. B, 2014. What is Big Data? Himss Clinical and business intelligence. Available at: www.himss.org/file/1242441/download?token=sQoZJ5uB Ghasemaghaei. M, Hassanein. K Turel. O, 2015. Impacts of Big Data Analytics on Organizations: A Resource Fit Perspective. Impact of Data Analytics on Organizational Performance. Available at: https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1030context=amcis2015 George. L, 2014. Getting Started with Big Data Architecture. Cloudera. Online. Available at: https://blog.cloudera.com/blog/2014/09/getting-started-with-big-data-architecture/ IDG Connect, 2014. Big Data for Marketing Sales: Data Accuracy to Business Impact. Online. Available at: https://info.avention.com/rs/onesource/images/Whitepaper_IDGBigDataForMarketingandSales.pdf McDonald. C, 2017. 5 Big Data Production Examples in Healthcare. Online. Available at: https://www.mapr.com/blog/5-big-data-production-examples-healthcare Millman. N, 2014. 8 considerations when selecting big data technology. Online. Available at: https://www.computerworld.com/article/2475840/big-data/8-considerations-when-selecting-big-data-technology.html MongoDB, 2016. Big Data: Examples and Guidelines for the Enterprise Decision Maker. Available at: https://s3.amazonaws.com/infomongodbcom/10gen_Big_Data_White_Paper.pdf Oracle, 2013. Oracle: Big Data for the Enterprise. Oracle white paper. Online. Available at: https://www.oracle.com/us/products/database/big-data-for-enterprise-519135.pdf Press. G, 2016. Top 10 Hot Big Data Technologies. Online. Available at: https://www.forbes.com/sites/gilpress/2016/03/14/top-10-hot-big-data-technologies/#4fbab1f065d7 Regola. N, Cieslak. D Chawla. N, 2013. The Need to Consider Hardware Selection when Designing Big Data Applications Supported by Metadata. Online. Available at: https://www3.nd.edu/~nchawla/papers/bigdata13.pdf Rodrigues. T, 2012. 10 emerging technologies for Big Data. Tech republic. Online. Available at: https://www.techrepublic.com/blog/big-data-analytics/10-emerging-technologies-for-big-data/ Signh. S, Singh. P, Garg. R Mishra P, 2015. Big Data: Technologies, Trends and Applications. International Journal of Computer Science and Information Technologies. 6(5). Available at: https://ijcsit.com/docs/Volume%206/vol6issue05/ijcsit20150605101.pdf Taylor. J, 2013. Delivering Customer Value Faster With Big Data Analytics. Decision management solutions. Online. Available at: https://www.fico.com/en/wp-content/secure_upload/DeliveringCustomerValueFasterWithBigDataAnalytics.pdf Wegener. R Sinha. V, 2013. The value of Big Data: How analytics differentiates winners. Bain and Company. Online. Available at: https://www.bain.com/Images/BAIN%20_BRIEF_The_value_of_Big_Data.pdf

Smart Growth Defined Essay Example

Smart Growth Defined Essay It aims to: 1) uphold economic growth; 2) hamper or reduce climate change; 3) protect the environment; 4) and 5) support and promote public health (Sustainable.., 2007). It also intends to attain the following: â€Å"an exceptional sense of community and place; enlarge the variety of transportation, employment and housing alternatives; evenhandedly dole out the expenditures and benefits of development; conserve and improve natural and cultural resources; and promote public health† (Sustainable.., 2007).Furthermore, Smart Growth’s principles include the following: 1) â€Å"take advantage of compact building design†; 2) â€Å"strengthen and direct development towards existing communities†; 3) â€Å"provide a variety of transportation choices†; 4) â€Å"preserve open space, farmland, natural beauty and critical environmental areas†; 5) â€Å"mix land uses†; 6) â€Å"make development decisions predictable, fair and cost effective†; 7) â€Å"foster distinctive, attractive communities with a strong sense of place†; 8) â€Å"encourage community and stakeholder collaboration†; 9) â€Å"create walkable neighborhoods†; 10) â€Å"create range of housing opportunities and choices† (Sustainable.., 2007).The tools that cities can utilize to uphold smart growth include the following: 1) â€Å"local government functions like land-use planning, urban design, development regulations, as well as, the major policy development processes that support the objectives of smart growth; 2) â€Å"strategic plans†; 3) â€Å"district plans†; 4) â€Å"land use plans†; and 5) â€Å"citizen involvement tools† (Sustainable.., 2007).Tools which Could Possibly Be (or Already are) Effective in KuwaitKuwait should â€Å"provide a variety of transportation choices† since traffic is terrible in Kuwait due to the fact that rules are not obeyed (Sustainable.., 2007). Smarth growth is badly needed there.