Xav-BI-D1-tejaswi-150words Data processing can be defined as the process of collecting raw data and converting it into some form of useable information. Data processing helps enhance the competitive edge of the business and is performed by data scientists. It helps businesses to draw feasible conclusions for business insights and thus it becomes mandatory and important to understand the necessity and importance of processing it. The main steps in the process of data processing are as follows. Collection of data: This is the first step in the processing of data, where data is retrieved from warehouses and trusted sources with the highest level of quality and authenticity (Fenner, 2020).
Preparing data: After the data is collected, it enters the preparatory state, where it is refined and strategized for processing. In this stage, data is also assessed for errors and any incredible data is eliminated at this stage. Processing: The prepared data is then processed with the help of algorithms, with each machine learning technique assigned for different types and sources of data. Data Interpretation: At this stage, the data gets refined in such a way that even non-scientists can understand and comprehend it (Sharda et al., 2021). Data gets translated and it becomes readable now and gets filled with graphs, videos, and images. At this stage, the organization begins to self-serve data for its analytics projects. Storage of data: This is the final stage of data processing, as all the refined and processed data gets stored for use in the future. Xav-BI-D1-sneha-150 Why are the original/raw data not readily usable by analytics tasks? Often, raw data can be semi-structured or unstructured, which means that the data is not organized correctly. Even though data may be collected in bulk through modern-day data collection mechanisms like RFID-based networks, it still needs to comply with specific usability and quality metrics (Sharda et al., 2020).
For different data analytics processes, data needs to pass certain quality and quantity requirements and a particular structure in place. The data needs to have the key fields or variables as normalized values. Also, there should be organization-wise standards set for the variables and subject matters (Sharda et al., 2020). Thus original/ raw data is not readily usable by analytics tasks. The data needs to be processed to match the analytical requirements. What are the main data preprocessing steps? List and explain their importance in analytics. In the first step, the relevant data is collected from the sources, and necessary records and variables are identified while filtering non-relevant data. Records from multiple data sources are merged. This step is called data consolidation. The next step is Data Cleaning/Scrubbing, and the missing data values might be imputed or ignored, reduction of noise takes place, and duplicated, if any, are eliminated.
Noisy values are outliers, and missing values can either be anomalies or natural parts of the dataset. It is vital to tend to these values in this step. The third step is Data Transformation, where data is normalized, discretized, and attributes are created. In this step data is normalized between minimum and maximum for all variables to reduce the potential bias of variables dominating other variables due to large numeric values. In discretization, numeric values are converted to categoric values. The next and final step is Data Reduction/variable selection; data volume is reduced by eliminating the dimensions. Too much data can be an issue for analytics; hence the dimensions are reduced to keep the data size smaller and relevant. The sampling is done carefully so that the subset of data would contain all the relevant patterns of the entire data set(Sharda et al., 2020). These data preprocessing steps are crucial to perform to make the original data suitable for analytics. Because of preprocessing steps, the analytic data procedures can read the data correctly and produce the desired results with improved accuracy. Xav-D2-aditya-150 What are the privacy issues with data mining?
Do you think they are substantiated? Data mining is the process by which businesses convert raw data into usable facts. The data mining process is typically carried out using traditional techniques rather than automated software devices. Despite the fact that there are several benefits of using this technology, such as: B. Forethought. Market dynamics and the business sales raise a slew of privacy concerns. The philosophy of exchanging sensitive information creates loopholes for data fraud, which is the root cause of the issues. Data mining assists businesses in obtaining valuable knowledge to aid in corporate activities. They often get a large amount of personal information (Sumathi & Sivanandam, 2016). Personal information gathered by data mining applications can be easily transferred to third parties without the owners’ permission. This will include things such as fitness statistics and shopping patterns. as well as official information Outsourced data could be used for artificial learning, intelligence, data management applications, and databases.
In most cases, we provide our personal information to banks and other government departments. The government will use data to combat terrorism. and is very likely to be targeted by cyber attacks (Mendes & Vilela, 2017). Although this approach is advantageous to the government, leaked information may be traded on the black market, compromising both protection and privacy because the government must seek approval from users before transferring their sensitive information to their database. Xav-feroz-150 The key issue in the data mining are individual privacy data mining makes it possible to analysis the business transactions and a significant amount of information about individuals buying habits and preferences (Clifton, 2019). • The major issue in the data mining are data integrity because of data integrity many individuals are companies groups data has been duplicated from different sources • There is another issue is cost where system software costs drops dramatically then data mining and data warehousing becomes easier and available in everywhere. • Data mining can confirm or qualify such observations in addition to finding new patterns that may not be immediately discernible through simple observation.
There are a certain issues, contingent upon your information, the applications, and on your legitimate circumstance. All are legitimate. To start with, your information ought not to have any actually recognizable data (PII) except if you truly should have it, even at that point, your protection understanding may confine what you do (Fayyad, 2019). Indeed, even without PII, you may have security issues. Postal code in addition to age and sexual orientation is sufficient to distinguish a critical division of most populaces. On the off chance that you have six information components, you can ID about everybody. Thus, PII expulsion isn’t sufficient. Second, applications matter. In the event that you are seeing wide patterns, similar to the connection of pay to mark inclinations, you are more secure than focusing on. Deciding how to target young person young ladies for a particular sort of cosmetics is a case of something that may stray into a security issue. Finding a workable pace stuff like pregnancy testing packs is a perilous application for information mining (Rolf Stadler, 2018).
Third, laws matter and they are diverse around the globe. In China you can do about anything as long as the legislature can get to your work for their own motivations. In Europe, GDPR seriously confines what you can do, in spite of fact you would be alright somewhere else. This is just a study of a couple of issues, and some may contend different points are similarly as significant (Peter Cabena, 2018). Raj-aneesh-150 words The most significant change was the introduction of the “Safe Spaces” policy (which would create “safe spaces” for people who choose to not share personal information and make them “safe spaces” on a site like tumblr, etc), while several countries have “no hate speech” policies which have become increasingly common.
Raj-priyal-150 The development of social media application has proved very productive and comprehensive in the society as the merits and the demerits are associated with these sites and application. There is a need to regularize the content of social media sites because of the increasing negative impacts rather than the positive impact. The rules and regulations should be devised that can be followed by the users otherwise the strict actions should be taken on violation (Kayandepatil, 2019). The self-regularization of the social media sites should be preferred before the regularization of the government because the authoritative power can develop the more comprehensive approaches than government. But the power of the government can help the management for the implementation of these rules (Boccia Artieri et al., 2021). The transparency report should be issued to the government from the different social media sites as Facebook and Tik Tok. The report should shows that the management of the sites has removed the unnecessary and inappropriate content from the sites.
The European Union has issued the rules as if the inappropriate content from the sites is not removed by the users who have posted the content has to bear the fine. There is a need to devise the similar rules to manage the content. The government should fine the social the social media sites when the criminal rate is increased because of the inappropriate content. If the sites are not clear about the rules and regulations of content, then these should be banned in a territory. The management is necessary for the improvement of content (Boccia Artieri et al., 2021). Kon-HC-rasika-150 The pattern of services provided in healthcare is changing. Volume based service (fee for service) has been a norm, but now value based reimbursement structure is in more demand. Value based system provides more incentives for healthcare providers to offer the best care at the lowest cost and patients are receiving more value for their money.
Due to increasing demand for value-based system, there will be higher patient demand due to increased access to care, that can lead to less out-of-network services. Care of patient with chronic diseased will increased and prioritized. Patients will have options to choose their healthcare providers. Some of the change’s healthcare organization will have to consider: Identifying and maintaining an effective balance of value-based payment contracts. Providers to identify standard quality indicators that align with payers’ expectations. Understanding patient populations needs to appropriately develop payment model. Creating a plan of migrating to value based payment model without putting excessive strain on an organization’s resources or capabilities. Establishing an organizational structure that will implement effective processes, training, and incentives. Cutting costs, reducing waste, and improving quality to drive value.
Organizations and pharma companies must target a specific drug for a specific population to test outcome and quality of the value-based payment model. Organizations can start the transition by offering shared saving payment plan and then move towards a fully value- based model. Biopharma companies may agree to pay a portion of a hospital’s readmissions penalty if, for example, and implanted cardiac devices fails, and a patient is readmitted to the hospital. Many health care insurance companies are allocating much of their revenue toward value-based care. This means that switching to this type of care can give some health care providers a head start. organizations may begin to offer joint savings plans to smaller health care providers should they focus on value-based care. This is important, especially now since patients have more and more care options than ever before. Kon-raheel-150 The number of payments for services in the volume category that benefits from a volumespecific payment rate increases as people are paying higher and higher rates for certain services with the additional volume that those services pay. There are many different services with different volume levels, and therefore they need to decide which services are more valuable.
They can make the case that at a certain cost rate for those most valuable services, they can put up with the increased cost and then move the cost rate to the lowest for those services that are not valued at that cost rate. When the cost is higher than the service is valued, they then move the price to the next lowest cost rate and finally remove the service from the volume category. They have this system where they choose between more valuable services or choose between less valuable services (Waddimba et al., 2020). Furthermore, that way, they make money. If their company is going through a transition, there is much stress in getting the business set up and getting all the support they need up and running. If it is a family-owned business that’s transitioning, they are already on edge and need the support they need.
So, they need to get it all set up and ready to go at the same time (Waddimba et al., 2020). For many healthcare organizations, the first step towards becoming financially viable is to develop an investment approach to investment-side investing. Moreover, while many organizations are adopting this approach, the underlying concept remains. The underlying principle of this approach is still quite powerful – that, as in most investment strategies, they should be looking at how to capture costs they do not generate but that they should maximize if possible. Nevertheless, since the underlying principle is still incredibly compelling, they will dive into the particulars of using this investment strategy in practical ways to enable healthcare organizations to be successful financially viable in the long-term perspective (Kokshagina & Keränen, 2021). Nag-harish-150 History of Caesar Cypher Caesar Cypher, also known as shift cipher, is an encryption technique. It is named after Julius Caesar, who was the Roman ruler who used this technique with a shift of three to provide encryption to messages. Suppose he required anything to write in a confidential way he used to write in a cipher, by changing the order of alphabets, which keep protection from forming any meaningful word.
If anyone wishes to convert these to plain text and find out the meaning, he must substitute the shift of three, namely D, for A, E for B, and so on. No one was there who has recorded this substitution. Augustus, Julius Caesar’s nephew, used the cipher for decryption but only with one shift. Whenever he encrypts, he wrote B for A, F for E and moving the same with this pattern. One can assume about the ciphertext during that time. Later several types of ciphers were introduced, but all the substitutions didn’t replace the Caesar Cipher because it is simplest to solve. For example, the cipher is implemented on many devices; one of them is the wheel device. Where two wheels (one outer and the other inner) contain the alphabet printed on them, when the inner wheel gets rotate, it aligns with any letter on the other wheel. If the letter M is placed under the letter A and the inner wheel gets rotated, it will have a displacement of 12. It has an incredibly long and fascinating history to cipher development which helps us in sending advance and sophisticated messages today (Christensen, 2010). Cypher Impact on Cryptography Cryptography came from two words, crypt and graph, which have their own meaning. Crypt means hidden, whereas graph refers to writing.
So it protects our information from suspicious and malicious third parties. Cryptography is the science of writing codes and ciphers and has been used since cipher technique development. . It allows people to transmit information in a secure manner. It is an essential security tool that provides the opportunity to sender sending their messages in an encrypted form to receiver. The technique of encryption prevents the message from unauthorized access. It helps the user to protect information against spoofing and forgeries. Hash function of cryptography plays vital role about data integrity assurance. cryptography is considered the most secure communication which is used to encrypt and decrypt with ensuring secure between two users. It helps in storing sensitive data by dispatching towards insecure channel like internet. A key is used to decode the encrypted message to a plain text (Purnama, Rohayani, 2015).
Caesar Cypher is one of the oldest algorithms for cryptography. This is the simplest algorithm therefore it is easy to crack. Cryptography is an art of converting the readable text into non readable form. Now a days it is required to send most of the data in online that is electronic way, so it’s becoming necessary to provide security while data transmission. Cryptography has come up with many extra features to protect from data thieves and malicious attacks. Nag-sandeep-150 Caesar’s early history of ciphering was very much dominated by classical cryptography. The first cryptographic paper dates back to 1665, but this is the only time a cipher is specified. In 1672 William Thorington proposed the Aesculapian Symmetric Cipher for computing the secret of one’s public key. He thought that the secret would efficiently compute, for the Aesculapian Cipher has based on the multiplication operation. He also thought that the secret would efficiently compute, and this will do by a simple series of permutations or multiplication of bits techniques.
The problem with this approach is that we cannot multiply many bits simultaneously with a relatively small number of bits (Gunawan, 2018). The Caesar cipher was developed around 1770 using a secret alphabet, the Caesar alphabet, to create a mathematical formula that could make mathematical computations faster and more efficient. The…
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