contoh essay data analysis

Importance of Data Analysis Essay

To find inspiration for your paper and overcome writer’s block
As a source of information (ensure proper referencing)
As a template for you assignment

The data analysis process will take place after all the necessary information is obtained and structured appropriately. This will be a basis for the initial stage of the mentioned process – primary data processing. It is important to analyze the results of each study as soon as possible after its completion. So far, the researcher’s memory can suggest those details that, for some reason, are not fixed but are of interest for understanding the essence of the matter. When processing the collected data, it may turn out that they are either insufficient or contradictory and therefore do not give grounds for final conclusions.

In this case, the study must be continued with the required additions. After collecting information from various sources, it is necessary to understand what exactly is needed for the initial analysis of needs in accordance with the task at hand. In most cases, it is advisable to start processing with the compilation of tables (pivot tables) of the data obtained (Simplilearn, 2021). For both manual and computer processing, the initial data is most often entered into the original pivot table. Recently, computer processing has become the predominant form of mathematical and statistical processing.

The second stage is mathematical data processing, which implies a complex preparation. In order to determine the methods of mathematical and statistical processing, first of all, it is important to assess the nature of the distribution for all the parameters used. For parameters that are normally distributed or close to normal, parametric statistics methods can be used, which in many cases are more powerful than nonparametric statistical methods (Ali & Bhaskar, 2016). The advantage of the latter is that they allow testing statistical hypotheses regardless of the shape of the distribution.

One of the most common tasks in data processing is assessing the reliability of differences between two or more series of values. There are a number of ways in mathematical statistics to solve it. The computer version of data processing has become the most widespread today. Many statistical applications have procedures for evaluating the differences between the parameters of the same sample or different samples (Tyagi, 2020). With fully computerized processing of the material, it is not difficult to use the appropriate procedure at the right time and assess the differences of interest.

The following stage may be called the formulation of conclusions. The latter are statements expressing in a concise form the meaningful results of the study. They, in a thesis form, reflect the new findings that were obtained by the author. A common mistake is that the author includes in the conclusions generally accepted in science provisions – no longer needing proof. The responses to each of the objectives listed in the introduction should be reflected in the conclusions in a certain way.

The format for presenting the results after completing the task of analyzing information is of no small importance (Tyagi, 2020). The main content needs to be translated into an easy-to-read format based on their requirements. At the same time, you should provide easy access to additional background data for those who are interested and want to understand the topic more thoroughly. These basic rules apply regardless of the format of the presentation of the information.

In order to successfully solve this problem, special methods of analysis and information processing are required. Classical information technologies make it possible to efficiently store, structure and quickly retrieve information in a user-friendly form. The main strength of SPSS Statistics is the provision of a vast range of instruments that can be utilized in the framework of statistics (Allen et al., 2014). For all the complexity of modern methods of statistical analysis, which use the latest achievements of mathematical science, the SPSS program allows one to focus on the peculiarities of their application in each specific case. This program has capabilities that significantly exceed the scope of functions provided by standard business programs such as Excel.

The SPSS program provides the user with ample opportunities for statistical processing of experimental data, for the formation of databases (SPSS data files), for their modification. SPSS may be considered a complex and flexible statistical analysis tool (Allen et al., 2014). SPSS can take data from virtually any file type and use it to create tabular reports, graphs and distribution maps, descriptive statistics, and sophisticated statistical analysis.

At this point, it seems reasonable to define the sequence of the analysis using the SPSS tools. First, it is essential to draw up a questionnaire with the questions necessary for the researcher. Next, a survey is carried out. To process the received data, you need to draw up a coding table. The coding table establishes the correspondence between individual questions of the questionnaire and the variables used in the computer data processing (Allen et al., 2014). This solves the following tasks; first, a correspondence is established between the individual questions of the questionnaire and the variables. Second, a correspondence is established between the possible values of variables and code numbers.

Next, one needs to enter the data into the data editor according to the defined variables. After that, depending on the task, it is necessary to select the desired function and schedule. Then, you should analyze the subsequent tabular output of the result. All the necessary statistical functions that will be directly used in exploring and analyzing data are located in the Analysis menu. A very important analysis can be done with multiple responses; it is called the dichotomous method. This approach is used in cases when in the questionnaire for answering a question, it is proposed to mark several answer options (Allen et al., 2014).

Comparison of the means of different samples is one of the most commonly used methods of statistical analysis. In this case, the question must always be clarified whether the existing difference in mean values can be explained by statistical fluctuations or not. This method seems appropriate as the study will involve participants from all over the state, and their responses will need to be compared.

It should be stressed that SPSS is the most widely used statistical software. The main advantage of the SPSS software package, as one of the most advanced attainments in the area of automatized data analysis, is the broad coverage of modern statistical approaches. It is successfully combined with a large number of convenient visualization tools for processing results (Allen et al., 2014). The latest version gives notable possibilities not only within the scope of psychology, sociology, and biology but also in the field of medicine, which is crucial for the aims of future research. This greatly expands the applicability of the complex, which will serve as a significant basis for ensuring the validity of the study.

Ali, Z., & Bhaskar, S. B. (2016). Basic statistical tools in research and data analysis. Indian Journal of Anesthesia, 60 (9), 662–669.

Allen, P., Bennet, K., & Heritage, B. (2014). SPSS Statistics version 22: A practical guide . Cengage.

Simplilearn. (2021). What is data analysis: Methods, process and types explained . Web.

Tyagi, N. (2020). Introduction to statistical data analysis . Analytic Steps. Web.

The Issue of Source Credibility
Data Normalization and Its Main Advantages
Using IBM Spss-Statistics: Gradpack 20 System
Application of T-Tests: Data Files and SPSS
Preparation of Correspondences by Typewriters and Computers
Data Collection Methodology and Analysis
Information Systems and Typical Cycle Explanation
Aspects of Databases in Hospitals
Data Analytics in TED Talks
The Document Warehousing Concepts
Chicago (A-D)
Chicago (N-B)

IvyPanda. (2022, November 30). Importance of Data Analysis. https://ivypanda.com/essays/importance-of-data-analysis/

"Importance of Data Analysis." IvyPanda , 30 Nov. 2022, ivypanda.com/essays/importance-of-data-analysis/.

IvyPanda . (2022) 'Importance of Data Analysis'. 30 November.

IvyPanda . 2022. "Importance of Data Analysis." November 30, 2022. https://ivypanda.com/essays/importance-of-data-analysis/.

1. IvyPanda . "Importance of Data Analysis." November 30, 2022. https://ivypanda.com/essays/importance-of-data-analysis/.

Bibliography

IvyPanda . "Importance of Data Analysis." November 30, 2022. https://ivypanda.com/essays/importance-of-data-analysis/.

Home — Essay Samples — Information Science and Technology — Data Analysis — Research of Data Analysis and Different Types of Analysis

Research of Data Analysis and Different Types of Analysis

Categories: Data Analysis Data Mining

About this sample

Words: 1171 |

Published: Sep 20, 2018

Words: 1171 | Pages: 2 | 6 min read

Introduction, types of anaysis.

To think in terms of significant tables that the data permit.
To examine carefully the statement of problem and earlier analysis and to study the original records of data.
To get away from the data to think about the problem in layman’s terms or to actually discuss the problems with others.
To attack the data by making various statistical calculations. Any of these approaches can be used to start analysis of data. The data analysis strategy is influenced by factors like the type of data, the research design researcher’s qualifications and assumptions underlying a statistical technique.

Data requirements

Data processing, data cleaning.

Should follow an “upside down” triangle format, meaning, the writer should start off broad and introduce the text and author or topic being discussed, and then get more specific to the thesis statement.

Provides a foundational overview, outlining the historical context and introducing key information that will be further explored in the essay, setting the stage for the argument to follow.

The topic sentence serves as the main point or focus of a paragraph in an essay, summarizing the key idea that will be discussed in that paragraph.

The body of each paragraph builds an argument in support of the topic sentence, citing information from sources as evidence.

After each piece of evidence is provided, the author should explain HOW and WHY the evidence supports the claim.

Should follow a right side up triangle format, meaning, specifics should be mentioned first such as restating the thesis, and then get more broad about the topic at hand. Lastly, leave the reader with something to think about and ponder once they are done reading.

Cite this Essay

Let us write you an essay from scratch

450+ experts on 30 subjects ready to help
Custom essay delivered in as few as 3 hours

Get high-quality help

Dr. Heisenberg

Verified writer

Expert in: Information Science and Technology

+ 120 experts online

By clicking “Check Writers’ Offers”, you agree to our terms of service and privacy policy . We’ll occasionally send you promo and account related email

No need to pay just yet!

Related Essays

3 pages / 1258 words

1 pages / 679 words

1 pages / 318 words

1 pages / 487 words

Remember! This is just a sample.

You can get your custom paper by one of our expert writers.

121 writers online

Research of Data Analysis and Different Types of Analysis Essay

Still can’t find what you need?

Browse our vast selection of original essay samples, each expertly formatted and styled

Related Essays on Data Analysis

In the field of arts management, audience engagement is an increasingly important and influential area of study. As the arts sector strives to create a more accessible, participatory and democratic experience for audience [...]

In the modern retail sector the consumers are the primary drivers of change in this industry, all the decision making process has become more sophisticated and complex than ever before. The objectives of this research analysis [...]

New communication methods have brought a change to how people are working, this includes the ways in which they work in and how they work together for instance, the facilities used by the employees and the technology being used [...]

The information system controls effectiveness is evaluated through an information system audit. An audit aims to establish whether information systems are safeguarding corporate assets, maintaining the integrity of stored and [...]

Research is the scientific method of investigation. The purpose of research is to learn something and gather evidence. Research typically begins with an observation and then curiosity as to why or how an entity or system [...]

"Updating of security procedures and scheduling of IT security audits: All security procedures within a company are required to be regularly updated in order to allow for a company to be able to have procedures in place that [...]

Get Your Personalized Essay in 3 Hours or Less!

We use cookies to personalyze your web-site experience. By continuing we’ll assume you board with our cookie policy .

Instructions Followed To The Letter
Deadlines Met At Every Stage
Unique And Plagiarism Free

The Process of Data Analysis

Introduction, the content analysis, rules of content analysis, uses of content analysis, types of content analysis, the advantages of content analysis, limitations of content analysis.

The process of data analysis starts immediately after the data is collected. It intends to examine, clean-up, transform and model the collected data to bring out the useful inference in order to make correct decisions. Caution is that the process of data analysis does not correct any bias in the data if it was collected in a biased way. Thus the quality of the data should be stressed before data analysis. Data analysis must take into account of the need, type, and purpose of the analysis. Different data analysis methods will only suit certain agendas (Bryman & Bell, 2007).

Data analysis entails noticing, thinking, and collecting the unique ideas in the data collected. Analysis will depend on the purpose and the need for the report. The best analysis will need one to either focus on the question, time, period, event, or the topic that the data was collected; in this case the question is the focus since the topic is not available. First one has to read and re-read the data so as to understand the data (Krueger, 1998).

During the reading one should jot down any impression that comes from the data; this will make one identify consistencies and differences in the data. Noticing will engage what will and should be noticed, and the process to noticing them. This is followed by coding of the information noticed. The best method of data analysis that will be used to analyze the given data will be content analysis (Krippendorff, 2004).

Content analysis is a comprehensive method of data analysis that determines what statements of respondents mean. The content analysis gives the better option of analyzing the narrative data provided since it analysis what the respondents have raised in their answers. It also helps to know how the statements relate and establish the emphasis which the respondents put forward. The Open-ended question from a survey of negative workplace relationships: “Please briefly outline how your work environment has made worse a negative relationship you have had at work” gives the basis of the data analysis (Bryman & Bell, 2007). The respondents were taken from a random sample from the administered question.

As cited by Stemler (2001) in the article “An overview of content analysis” there are six questions that should be addressed in any content analysis, these are; “Understand data being analyzed, how it should be defined, Know the population which its being drawn form, context relation on the data being are analyzed, boundaries of analysis and inferences target.”

The question may be from an interview or a question where the respondents gave their feeling on the environment at work could have worsened a negative relation they had at the workplace (Renner, 2003). According to the data given the respondents come from a wide range of professions, workplace, ranks, gender, and experiences. A total of 115 answers are issued in the data from the huge sample of respondents. This may have made up a representative sample of the respondents.

Analysis of the qualitative data would first involve reading the answers given. Noticing the given answer will be an easy task since it will involve checking the same answers or closely related answers given by the respondents. The noticed pattern of data will be recorded on spreadsheet with each narrative answer analyzed to give a short precise answer or phrase that will allow easier inference (Weber, 1990).

The phrase will explain the idea, concept, behavior, interactions, feelings, or problem stated by the respondents of the question. The phrase will be stated in such a way that it summarizes the meaning of each statement from the respondent and what he/she intended to express.

The set rules and regulations for content analysis are theory driven and are; firstly the amount of data analyzed at a particular time should be state and adhered to. This means that when you state a phrase, line, paragraph, or sentence to code data it should be consistent to the end. Secondly, is what is mean by each category used? The categories should be either inclusive or exclusive. Thirdly, is that the categories must be defined precisely on each property (Renner, 2003).

The few narrative answers from the respondents were as follows; “It encourages competition, especially since one is measured by “who has most projects” that also creates a lonely environment and reduces real team work.” “Poor performance from other person who I have a negative relationship with made me angry and affected my judgment”, “The negative relationship dominated the work place to such an extent that work colleagues became divided into two clear distinct groups. It made the work environment very stressful for all involved and in the end the bastard had to leave!”, “Time pressures can mean that there is not enough opportunity to discuss problems adequately”, “I’m a designer – the company is roughly divided into ‘account teams’ who deal with the clients and admin, and the ‘studio’ where all production and creative staff work. Where I currently work, the workplace is divided into upstairs for studio, and downstairs for account teams. The physical separation exaggerates any (and many!) differences the two parts of the company have and definitely contributes to an ‘us’ and ‘them’ attitude for both sides”, “When one became a supervisor and we were under him. He thought he was better then us and stopped hanging out with us” “Usually in a negative relationship I avoid the person in question. In the work environment I am required to maintain a level of professionalism, which requires me to put aside differences and work with that person, which seems to add more strain to the situation because you both know that neither of you wants to be involved”, “Too much work puts me under stress and so makes me grumpier before speaking with the person I don’t like” and “Boss again – sometimes there can be weeks we don’t speak to each other – he just comes and dumps the work on my desk and leaves the room” among others.

For the above statements different inferences are made, the phrases given for the above answers may be; reduce team work, resignation, time wastage, crisis, disagreements, tension, stress, low concentration, and boredom, pressure, under performance, firing of employees, excommunication, and enmity. Each of these inferences will have a code or category that will be given to simplify the initial statement given (Silverman & Marvasti, 2001). Due to the bulk of data the phrases may be numerous so that to incorporate everyone’s views. The statements must also be sampled randomly and inferred in the correct way possible to avoid bias; they should also be very clear and precise to avoid ambiguity or double statements.

There are three categories of content analysis. They are; being able to make an inference of the statements given, describing the characteristics of communication, and giving the effects of communication. Content analysis is used in terms of purpose, question, and communication constituent. On the part of communication constituent issues such as; source, encoding and decoding procedure, channel, message, and recipient (Creswell, 2009).

The specific uses include; answering queries of disputes, analyzing; individual traits, techniques, styles, and evaluating evidence. It is also important to describe communication patterns, contents, standards, sources, and response. It also assesses the information flow, communication response, inference of personal life conditions (Denzin & Lincoln, 2008). In the data provided the analysis will seek to reveal the effect of a negative workplace relationship on the work, detect the existing problems, give the attitude and behavior of the respondents, and the effects that finally occur.

There are two types; the conceptual and relational analysis. In conceptual a specific model is identified for analysis and the frequency of occurrence is recorded. This method was the traditional content analysis. The rules may either be explicit or implicit hence they should be clearly defined before analysis (Creswell, 2009).

One must first identify the research question and samples to be used. This is followed by coding or categorizing in to manageable sizes. The meaning is the inferred from the units of information and communication that are analyzed and inferred. Relational analysis is based on conceptual analysis which also examines texts for any relationship (Patton, 1990). This method is more flexible and one can decide which concepts will be analyzed.

Content analysis offers various pros when used in analysis. Firstly, it works on the communication of text and sentences directly; this is important since the key issues of the statements are addressed. Secondly, it is flexible to allow both qualitative and quantitative data analysis (Denzin & Lincoln, 2008).In addition it gives significant insight for a given period of time for the text analysed.

It also gives allowance text analysis which relate categories and relationships and statistical analysis of coded texts and sentences (Janesick, 2003). It is used to infer information for specific purposes in the society, while it is an unmistakable means of investigating interactions. It is also very important in establishing complex models of social structure thus it can be an exact data analysis research method.

Content analysis offers various cons when used in analysis. Firstly, it is time consuming given the nature of data to be analyzed. Secondly, when relational analysis is applied then there can be increased errors. It also has no theoretical base and hence any inference is based on understanding the relationships. It is also not easy to computerize or automate the system of data analysis since it is mostly based on words (Denzin & Lincoln, 2008).

Data analysis can be a long process but can be simplified when the correct analysis method is applied. The process of data analysis should be thorough and intensive to give the correct inference. With narrative qualitative data content analysis would be useful and most appropriate to induce the information. The content analysis gives us the better option of analyzing the narrative data provided since it analysis what the respondents have raised in their answers. It also helps to know how the statements relate and establish the emphasis which the respondents put forward.

For the Open-ended question from a survey of negative workplace relationships: “Please briefly outline how your work environment has made worse a negative relationship you have had at work” analysis will be easy when content analysis is used. If data is used to make any inference in a report then it must be analyzed perfectly so as to make correct decision in management.

Bryman, A. & Bell, E. (2007). Business Research Methods . Oxford: Oxford University Press.
Creswell, J. (2009). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . Thousand Oaks: Sage Publications.
Denzin, N. & Lincoln, S. (2008). Collecting and Interpreting Qualitative Materials . Thousand Oaks: Sage Publications.
Janesick, V. (2003). Stretching Exercises for Qualitative Researchers . London: Sage.
Krippendorff, K. (2004). Content Analysis: An Introduction to Its Methodology. Newbury Park: SAGE Publications.
Krueger, A. (1998). Analysing and Reporting Focus Group Results . Thousand Oaks: Sage Publications.
Patton, Q. (1990). Qualitative Evaluation and Research Methods . Newbury Park: Sage Publications.
Renner, M. (2003). Analyzing Qualitative Data . Madison, Wisconsin: University of Wisconsin.
Silverman, D & Marvasti, B. (2001). Doing Qualitative Research: A Comprehensive Guide . Los Angeles: Sage Publications.
Stemler, S. (2001). An Overview of Content Analysis. Practical Assessment, Research & Evaluation. 7(17), 78-92
Weber, P. (1990). Basic Content Analysis. Newbury Park: Sage Publications.

Cite this paper

Chicago (N-B)
Chicago (A-D)

StudyCorgi. (2021, November 23). The Process of Data Analysis. https://studycorgi.com/the-process-of-data-analysis/

"The Process of Data Analysis." StudyCorgi , 23 Nov. 2021, studycorgi.com/the-process-of-data-analysis/.

StudyCorgi . (2021) 'The Process of Data Analysis'. 23 November.

1. StudyCorgi . "The Process of Data Analysis." November 23, 2021. https://studycorgi.com/the-process-of-data-analysis/.

Bibliography

StudyCorgi . "The Process of Data Analysis." November 23, 2021. https://studycorgi.com/the-process-of-data-analysis/.

StudyCorgi . 2021. "The Process of Data Analysis." November 23, 2021. https://studycorgi.com/the-process-of-data-analysis/.

This paper, “The Process of Data Analysis”, was written and voluntary submitted to our free essay database by a straight-A student. Please ensure you properly reference the paper if you're using it to write your assignment.

Before publication, the StudyCorgi editorial team proofread and checked the paper to make sure it meets the highest standards in terms of grammar, punctuation, style, fact accuracy, copyright issues, and inclusive language. Last updated: November 23, 2021 .

If you are the author of this paper and no longer wish to have it published on StudyCorgi, request the removal . Please use the “ Donate your paper ” form to submit an essay.

Data analysis - List of Essay Samples And Topic Ideas

Data analysis is the process of inspecting, cleaning, transforming, and modeling data to discover useful information and support decision-making. Essays on data analysis could delve into various techniques and tools used in data analysis, its application in different fields like business or science, or the ethical considerations in handling data. Discussions might also explore the role of big data and analytics in modern society, the challenges posed by data privacy concerns, or the future of data analysis with the advent of technologies like artificial intelligence and machine learning. We have collected a large number of free essay examples about Data Analysis you can find in Papersowl database. You can use our samples for inspiration to write your own essay, research paper, or just to explore a new topic for yourself.

Impact of Technology on Privacy

The 21st Century is characterized by the heavy impact technology has on us as a society while it continues to develop new devices and modernize technology. Millions of individuals around the world are now connected digitally, in other words, people globally rely heavily on smartphones tablets, and/ or computers that store or save a majority of their personal information. Critical and extremely personal data is available and collected in these smart technology such as credit card details, fingerprint layout, and […]

What the Future Life Might Look Like with Blockchain

Just ten short years ago, blockchain was just an idea in a handful of forward-thinking developer’s heads. Even today, it’s widely misunderstood and only a small portion of the population knows exactly what it is. Most technology experts agree, however, that blockchain will transform many of the ways we do business. In just a short time, it is already having an impact on many business segments and is starting to touch our lives in many meaningful ways that we may […]

Sexual Orientation on Helping Behaviors Among African American College Students

Introduction Seeking help from friends and family members are much easier as opposed to strangers. Many considerations run in the mind of an individual when seeking help from persons they are not aware of. Factors such as the sexual orientation of the person expected to provide help and the time of the day are some of the considerations made before determining the chances of the help being granted. Sexual orientation and time of the day are therefore important factors that […]

We will write an essay sample crafted to your needs.

Alcohol Abuse Among Women in Salford

Introduction Nowadays, our society found it difficult to understand or restrain their use of alcohol to women because this alcoholic beverage has been a part of social life for ages. Alcohol abuse has destroyed many lives and considerably damaged many families, patients and women. Also it can bring a massive consequence in the entire society. The shocking effects of too much alcohol drinking are generally well-known. The alcohol use in women in Salford have been brought sharply into focus over […]

Beyond Numbers: the Significance of Qualitative Data Analysis

In the ever-evolving landscape of research and analysis, the spotlight has historically shone brightly on quantitative data, offering a seemingly unassailable foundation for drawing conclusions. However, a paradigm shift is underway, acknowledging the irreplaceable role played by qualitative data analysis. Beyond the stark numerical arrays inhabiting spreadsheets and statistical models, a treasure trove of nuanced insights awaits discovery through a more interpretive and thorough exploration. Qualitative data analysis, fundamentally, is a meticulous and rigorous expedition into non-numeric information. It entails […]

Quantifying Impact: Data Analysis in Assessing Social Phenomena

In the contemporary tapestry of knowledge, the quest to fathom the reverberations of social phenomena has evolved into a fascinating expedition at the crossroads of data analysis and human interaction. This symbiotic relationship has birthed a vibrant discipline, where the intricate dance of numbers meets the enigma of social dynamics. Unraveling the complexities and quantifying the profound consequences of various phenomena on individuals and communities now unfolds in the realm of data-driven exploration. In an age where data reigns supreme, […]

Insights from Data Analysis: Methodologies, Applications, and Implications

Multifaceted domain of data analysis, examining its methodologies, applications, and implications within diverse fields of inquiry. Drawing from statistical techniques, machine learning algorithms, and computational methods, it explores the process of deriving meaningful insights from data and making informed decisions based on empirical evidence. Through an examination of case studies and theoretical frameworks, this essay elucidates the role of data analysis in informing decision-making, driving innovation, and advancing knowledge across disciplines. Data analysis serves as a cornerstone of empirical inquiry, […]

Quantum Data Analysis: Bridging Gaps in Incomplete Datasets

In the ever-evolving landscape of data analytics, the challenge of handling incomplete datasets remains a persistent stumbling block. As we delve into the intricacies of quantum data interpolation, a groundbreaking approach emerges—one that transcends conventional methods and introduces a paradigm shift in the way we address data gaps. Traditional data interpolation methods often fall short when confronted with the complexity of incomplete datasets. The inadequacies of linear and polynomial interpolations become evident, especially in scenarios where quantum data is involved. […]

1. Tell Us Your Requirements

2. Pick your perfect writer

3. Get Your Paper and Pay

Hi! I'm Amy, your personal assistant!

Don't know where to start? Give me your paper requirements and I connect you to an academic expert.

short deadlines

100% Plagiarism-Free

Certified writers

Home / Essay Samples / Health / Medicine / Data Analysis

Data Analysis Essay Examples

General overview of data analytics.

As there is massive growth in technology, the usage of data is also increasing day by day due to social networks and cloud computing. Lots of data was getting used and there was no back up for the data, so analytics of data was introduced....

The Crusial Aspects of Lead Generation

Many sales executives talk of budget, needed timeframe and authority (i. e. BANT) to get leads. Some claim they need appointment with the right person and some businesses are using webinars, blog subscriptions, sign ups, emails etc. to reach buyers. The B2B sector is growing...

Gdpr, Trust and Personal Data Sharing: Literature Review

Following the revelations of the Facebook-Cambridge Analytical scandal, Google unlawfully collecting iPhone users’ data and the numerous other reports of data misuse cases, GDPR (General Data Protection Regulation) has been implemented. GDPR law gives the individuals the choice on how an organisation may use, store...

Analysis of Data Management Strategies at Tesco

Tesco are a large multinational organisation. Initially Tesco was founded in 1919 by Jack Cohen as a grocery stall in East London, with the first store opened in Edgware in 1929. The first self-service store was opened in 1948 in Hertfordshire, with “a mixed reaction...

Target's Marketing Strategy: Pregnancy Prediction Algorithm

This report aims to highlight how the retail stores are using big data and predictive analytics to know their customer’s need and do personalized advertising. The report focuses on the enhanced marketing operation of US retail giant Target through the use of big data. Target...

Leadership and Data Fighting Activities

Our expanding reliance on data advances and self-ruling frameworks has heightened global worry for data and digital security even with politically, socially and religiously roused digital assaults. Data fighting strategies that meddle with the stream of data can challenge the survival of people and gatherings....

Pregnancy Loss: Cognitive Behavioral Therapy

This report aims to highlight how the retail stores are using big data and predictive analytics to know their customer’s need and do personalized advertising. Report focuses on the enhanced marketing operation of US retail giant Target through the use of big data. Target was...

Analysis of the Article on Panther Conservation Project

According to the paper, the panther species of North America is listed as endangered and is one of the last from that area. A panther population of Florida was rediscovered and efforts immediately went underway to conserve, support, and protect them. The authors gathered data...

Analysis of the Study "Auto-join: Joining Tables by Leveraging Transformations"

The authors attempt to address the problem of joining tables when the datasets are collected from different sources and their key columns are formatted differently. Joins are very useful when it comes to combining records for data analysis and the present-day tools available allow to...

How Economic Development Has Made Womens Lifes Difficult

As indicated by Database (2002) underdeveloped nations allude to nations of Africa, Asia and Latin America, which were portrayed as nations with low wage, high neediness rate, joblessness, high populace and war. This exposition fundamentally show how monetary improvement tended to make the lives of...

Trying to find an excellent essay sample but no results?

Don’t waste your time and get a professional writer to help!