Data Analysis and Forecasting Introduction Expansion is an essential process that an organization has to adequately consider in maintaining a more influential platform for successful engagement. As a salesperson, it is vital to assess different measures which can help in maintaining a unique system for an improved level of development. Various factors need to be evaluated in determining the underlying independent factors that influence vehicle ownership. Thus, ensuring that the expansion criteria are adequately assessed, it would be possible to ensure that the company emphasizes better concepts that promote the needs of individuals. Therefore, this research will determine the data collected in Turkey. The data focused on the most recent data in 2018. Thus, the research will involve the assessment of different factors that will help in improving the company commitment for Automobile Inc. so that it would help in making a better decision regarding its focus on expansion. Scatterplots Scatterplots are essential in assessing the underlying relationship between two variables that are investigated. The relationship can be either linear or inverse based on the relationship of the variables that…

Big data Systems in Healthcare Potential Benefit of using Big Data as part of a Clinical System Bid data in healthcare relates to the abundance of health data that are derived from numerous sources such as electronic records, genomic sequencing, research, medical insurance records that help improve in the delivery of healthcare services (HealthLeaders, 2019). The adoption of the use of big data systems in any healthcare organization can help improve the services such a driving healthcare from a fee-for-service model into one that is value based and more concerned with patient outcome. In such an event it is possible to realize reduce healthcare cost while maximizing patient services in terms of diagnosis and treatment. A good example is the new approach in technology where mobile applications have been used to monitor the health of patients. These applications rely of big data systems which are backed up in cloud serves (Catalyst, 2018). Such applications can them offer advice to their patients about their health condition and inform them when to seek medical attention based on the information they input on…

Beneficiaries of Improved Healthcare Data Security Healthcare organizations need to understand the benefits of secure healthcare data sharing and way they could participate in securing such classified information. There is a wide range of benefits involved in this professional process in ethical healthcare practice that the entire system should implement to improve high quality healthcare. For instance, chronic disease registries, information on substance abuse, large-scale analytics, epidemiology, or disease tracking are all vital potential uses for data sharing. Data sharing is also important in the interoperation routine in the emergency department and genetic studies.  Other than clinical and patient-facing uses, ethical exchange of data in medical practices is important because it ensure sharing of best healthcare practices. The sharing of this data could be between organizations, or between entities in other industries like government agencies and financial institutions. For example, healthcare organizations can share data on cyber threats or the insider threats such as those emanating from cyber attacks. Ethical information sharing is useful in all types of threats and incidences whether there is incident of something that occurred in…

Risks to Patients Data   Beneficiaries of Improved Healthcare Data Security Healthcare organizations need to understand the benefits of secure healthcare data sharing and way they could participate in securing such classified information. There is a wide range of benefits involved in this professional process in ethical healthcare practice that the entire system should implement to improve high quality healthcare. For instance, chronic disease registries, information on substance abuse, large-scale analytics, epidemiology, or disease tracking are all vital potential uses for data sharing. Data sharing is also important in the interoperation routine in the emergency department and genetic studies.  Other than clinical and patient-facing uses, ethical exchange of data in medical practices is important because it ensure sharing of best healthcare practices. The sharing of this data could be between organizations, or between entities in other industries like government agencies and financial institutions. For example, healthcare organizations can share data on cyber threats or the insider threats such as those emanating from cyber attacks. Ethical information sharing is useful in all types of threats and incidences whether there is incident…

Data Analysis Describe the purpose of data analysis. Data refers to assets of the variables in terms of quality and quantity (Lavrakas, 2008). Data analysis refers to a process that involves the application of the various statistical data in the organization, evaluation, and interpretation of the data. The organization of data for easy manipulation,  access to the information, is referred to as the data analysis. Data analysis has several requirements. Data establishment The specific entity from which the data is being collected. Before the analysis of the data, there should be a source for the information that needs to be analyzed. The data variables need to get received in the manner that the analysis methodologies efficiently analyze the data. Data collection After the establishment of the data, the data needs to be collected. The selection that is to be employed varies with the type of information that is to be collected.  The various data collection methods that need to be used include; traffic cameras in the case of the road statistics, satellite light and, recording devices. Others include interviews, downloads…

Qualitative Data Analysis Qualitative data is the non- numeric information that is gathered from interviews transcripts, audio and video recordings, texts and image textbooks. Organizing data Data collected during the research is organized in a manner that will facilitate the process analysis to be easy. Sources of data can be from interviews either written or recorded, observation notes, questionnaires, surveys or official documents. In research, some several respondents and participants are involved in research which gives information on the topic of research under study. To code and extricate data from several sources can be very challenging, but if the data is organized correctly, it becomes easy. Various steps are involved in organizing data, and these are, Step 1; review the entire data that is collected. Collected data needs to be reread again so that patterns and themes can start to develop. The patterns or the topics are assigned symbols, numbers or letters to differentiate the different categories. There are three types of coding which are open, axial and selective coding. Open coding usually comprises trying to make logic of the…

Prepare Your Data Center with New Security Measures to Protect Sensitive Information Cloud migration allows you to have a centralized location for your IT infrastructure, which includes network computers and storage and processors for extensive data. Having a cloud data center minimizes the overall maintenance cost by providing services such as data storage, backup and restore, and data management. It holds sensitive information such as customer data and proprietary information, making data center security, both physical and digital, a paramount measure. How to Implement Data Center Security Datacenter design and implementation depend on the demand of your business, DevOp methodologies, and popular software. They are also built using new technology to enable them to offer various benefits, including: Cutting operational costs Scale and elasticity of IT infrastructure An improved match between distributed microservices (software structure of the applications) and deployment (containers and virtual machines) Quick turn-around between development and release cycles With these benefits rises the need to enhance data center security measures. Over the last few years, there has been an increase in data breaches and cyber-attacks. As a…

Using Correlating data in detection of worms and botnet attacks Correlating data is very important when it comes to the detection of worms and botnet attacks (Malik & Alankar, 2019). Correlating data, in this case, refers to the data that is related to the worm or the botnet attacks. The process of detecting worms and botnet attacks may be easy or difficult, depending on the approaches that one uses. It is the desire of every person to detect the worms and botnet attacks easily without any significant challenges. There is a need to make use of correlating data to ensure that this happens. The data will help the person in charge to gain some knowledge, which will assist him or her in detecting the worms and the botnet attacks (Yin, Yang & Wang, 2013). If the cybersecurity specialist in charge of dealing with worms and other attacks doesn’t understand the data concerning worms, then it will be challenging to deal with them. The data may be from a previous worm or botnet attack, which happened to a particular organization. By…

BIG DATA ANALYSIS Big data analysis is defined as the various processes of collecting and analyzing data in a bid to find useful information. Big data analysis is key to the different trends in society. With the constant growth in technology, it is inevitable for big data analysis to be adopted by the various set of companies. Big data is key to increasing and the different set sectors in the economy. Big data analysis, to a greater extent, passes through the various sets of economy irrespective of the field. The given article on the impact of big data and business analytics on supply chain management is a practical example of how big data has various implications, especially in supply chain management. The article is much relevant to the topic and chapters of big data analysis as it tries to show on the various aspects that have been affected by big data analysis and its importance in the different areas of supply chain management. With big data analysis, it is evidently clear that supply chains have more to gain. The optimization…

Outline of Why the United States Should Adapt To European Data Protection Policy Security UE- the handling and access to databases that concern the welfare of the citizens have always been guarded with a lot of secrecy (Danezis 234). USA- political parties and campaigns almost face no regulations in respect to access, collection, and dissemination of citizen’s data Personal data used by the major candidates and political parties without consent in the last election. 2) Political exploitation in regard to data access and use. USA– political systems and have no any legal implications under US privacy law for invasion of private data. EU- advanced method of data collection and analysis EU- more comprehensive data protection systems and legislation compared to the US. USA: a high number of individuals involved in big data security and access creates a data security problem. 50,000 people in Arkansas University affected dues to the high number of people accessing sensitive data in the university. eBay data breach, 145 million people affected and birthday, home address and emails address stolen. EU- controls the physical space and…