This document provides an overview of data analysis, including definitions, processes, techniques, tools, advantages, and disadvantages. It discusses the importance of data analysis in research, defining key terms like structured vs. unstructured data. The document outlines the data analysis process from data collection and cleaning to interpretation and visualization. It also covers quantitative and qualitative analysis techniques such as regression analysis, hypothesis testing, content analysis, and discourse analysis.
📊 Dive into the world of #DataAnalytics to unlock the secrets of information! 🚀 Understanding the basics is your gateway to data-driven success. 🌐 Explore foundational concepts, from data collection to interpretation, demystifying the data landscape. 📈 Master key techniques, empowering you to extract valuable insights and make informed decisions. 💡 Enhance your analytical skills and stay ahead in the fast-paced digital era. 🧠 Whether you're a beginner or looking for a refresher, this journey into data understanding is your stepping stone to a data-savvy future!
MaxEd, an initiative from i-miRa Knowledge Solutions offers data analytics and curated market intelligence solutions for MSMEs and fast growing brands in Kerala.
Data analytics is the process of examining large and varied datasets to uncover hidden patterns, correlations, trends, and insights. It involves applying statistical and mathematical techniques, as well as computational tools and algorithms, to analyze data and derive meaningful conclusions.
Data Analysis Methods 101 - Turning Raw Data Into Actionable InsightsDataSpace Academy
Data analytics is powerful for organisations. It can help companies improve their overall efficiency and effectiveness. The blog offers a step-by-step narration of the data analysis methods that will help you to comprehend the fundamentals of an analytics project.
📊 Dive into the world of #DataAnalytics to unlock the secrets of information! 🚀 Understanding the basics is your gateway to data-driven success. 🌐 Explore foundational concepts, from data collection to interpretation, demystifying the data landscape. 📈 Master key techniques, empowering you to extract valuable insights and make informed decisions. 💡 Enhance your analytical skills and stay ahead in the fast-paced digital era. 🧠 Whether you're a beginner or looking for a refresher, this journey into data understanding is your stepping stone to a data-savvy future!
MaxEd, an initiative from i-miRa Knowledge Solutions offers data analytics and curated market intelligence solutions for MSMEs and fast growing brands in Kerala.
Data analytics is the process of examining large and varied datasets to uncover hidden patterns, correlations, trends, and insights. It involves applying statistical and mathematical techniques, as well as computational tools and algorithms, to analyze data and derive meaningful conclusions.
Data Analysis Methods 101 - Turning Raw Data Into Actionable InsightsDataSpace Academy
Data analytics is powerful for organisations. It can help companies improve their overall efficiency and effectiveness. The blog offers a step-by-step narration of the data analysis methods that will help you to comprehend the fundamentals of an analytics project.
what is ..how to process types and methods involved in data analysisData analysis ireland
Data analysis is the process of cleaning, transforming, and processing raw data in order to extract useful and actionable information that can assist businesses in making better decisions.
Uncover Trends and Patterns with Data Science.pdfUncodemy
In today's data-driven world, the vast amount of information generated every second presents both challenges and opportunities for businesses and researchers alike. Harnessing this data effectively can provide valuable insights, unlock hidden trends, and identify patterns that drive innovation and strategic decision-making.
Take the first step towards a rewarding career in data analytics with APTRON Solutions' Data Analytics Course in Noida. Whether you are a beginner or an experienced professional, our comprehensive training program will empower you to harness the power of data and drive business success. Enroll now and unlock a world of opportunities in the dynamic field of data analytics!
Data Analytics Certification in Pune-JanuaryDataMites
A data analytics course is an educational program designed to teach individuals the skills and techniques necessary for analyzing and interpreting data to extract meaningful insights.
For more details visit: https://datamites.com/data-analytics-certification-course-training-pune/
leewayhertz.com-Data analysis workflow using Scikit-learn.pdfKristiLBurns
Data analysis is the process of analyzing, cleaning, transforming, and modeling data to uncover useful information and draw conclusions from it to support decision-making. It involves applying various statistical and analytical techniques to uncover patterns, relationships, and insights from raw data.
Data analytics courses are educational programs designed to teach individuals the skills and techniques needed to work with data, analyze it, and extract meaningful insights.
For More Details: https://datamites.com/data-analytics-certification-course-training-pune/
A data analytics course is an educational program designed to teach individuals the skills and techniques necessary for analyzing and interpreting data to extract meaningful insights.
For more details visit: https://datamites.com/data-analytics-certification-course-training-chennai/
Top 30 Data Analyst Interview Questions.pdfShaikSikindar1
Data Analytics has emerged has one of the central aspects of business operations. Consequently, the quest to grab professional positions within the Data Analytics domain has assumed unimaginable proportions. So if you too happen to be someone who is desirous of making through a Data Analyst .
Data analytics courses are educational programs designed to teach individuals the skills and techniques needed to work with data, analyze it, and extract meaningful insights.
For More Details: https://datamites.com/data-analytics-certification-course-training-delhi/
What are Entry Level Data Analyst Jobs?: A Guide Skills optnation1
Paid internships and employment training programmes that are directly related to their field of study are permitted for international students holding F-1 student visas, provided that the courses fall under the category of Optional Practical Training to their major subjects of study. You can search for remote data analyst jobs and other OPT positions in the USA with similar specialisations.
Data Analytics Course In Hyderabad-OctoberDataMites
Data analytics courses are educational programs designed to teach individuals the skills and techniques needed to work with data, analyze it, and extract meaningful insights.
For More Details: https://datamites.com/data-analytics-certification-course-training-hyderabad/
Data Analytics Course In Chennai-NovemberDataMites
Data analytics courses are educational programs designed to teach individuals the skills and techniques needed to work with data, analyze it, and extract meaningful insights.
For More Details: https://datamites.com/data-analytics-certification-course-training-chennai/
what is ..how to process types and methods involved in data analysisData analysis ireland
Data analysis is the process of cleaning, transforming, and processing raw data in order to extract useful and actionable information that can assist businesses in making better decisions.
Uncover Trends and Patterns with Data Science.pdfUncodemy
In today's data-driven world, the vast amount of information generated every second presents both challenges and opportunities for businesses and researchers alike. Harnessing this data effectively can provide valuable insights, unlock hidden trends, and identify patterns that drive innovation and strategic decision-making.
Take the first step towards a rewarding career in data analytics with APTRON Solutions' Data Analytics Course in Noida. Whether you are a beginner or an experienced professional, our comprehensive training program will empower you to harness the power of data and drive business success. Enroll now and unlock a world of opportunities in the dynamic field of data analytics!
Data Analytics Certification in Pune-JanuaryDataMites
A data analytics course is an educational program designed to teach individuals the skills and techniques necessary for analyzing and interpreting data to extract meaningful insights.
For more details visit: https://datamites.com/data-analytics-certification-course-training-pune/
leewayhertz.com-Data analysis workflow using Scikit-learn.pdfKristiLBurns
Data analysis is the process of analyzing, cleaning, transforming, and modeling data to uncover useful information and draw conclusions from it to support decision-making. It involves applying various statistical and analytical techniques to uncover patterns, relationships, and insights from raw data.
Data analytics courses are educational programs designed to teach individuals the skills and techniques needed to work with data, analyze it, and extract meaningful insights.
For More Details: https://datamites.com/data-analytics-certification-course-training-pune/
A data analytics course is an educational program designed to teach individuals the skills and techniques necessary for analyzing and interpreting data to extract meaningful insights.
For more details visit: https://datamites.com/data-analytics-certification-course-training-chennai/
Top 30 Data Analyst Interview Questions.pdfShaikSikindar1
Data Analytics has emerged has one of the central aspects of business operations. Consequently, the quest to grab professional positions within the Data Analytics domain has assumed unimaginable proportions. So if you too happen to be someone who is desirous of making through a Data Analyst .
Data analytics courses are educational programs designed to teach individuals the skills and techniques needed to work with data, analyze it, and extract meaningful insights.
For More Details: https://datamites.com/data-analytics-certification-course-training-delhi/
What are Entry Level Data Analyst Jobs?: A Guide Skills optnation1
Paid internships and employment training programmes that are directly related to their field of study are permitted for international students holding F-1 student visas, provided that the courses fall under the category of Optional Practical Training to their major subjects of study. You can search for remote data analyst jobs and other OPT positions in the USA with similar specialisations.
Data Analytics Course In Hyderabad-OctoberDataMites
Data analytics courses are educational programs designed to teach individuals the skills and techniques needed to work with data, analyze it, and extract meaningful insights.
For More Details: https://datamites.com/data-analytics-certification-course-training-hyderabad/
Data Analytics Course In Chennai-NovemberDataMites
Data analytics courses are educational programs designed to teach individuals the skills and techniques needed to work with data, analyze it, and extract meaningful insights.
For More Details: https://datamites.com/data-analytics-certification-course-training-chennai/
Similar to Data analysis (Seminar for MR) (1).pptx (20)
nformationprocessingmodelfile1-110306221437-phpapp02 (1).pdf
This ppt will be helpful for studying about teaching models, information processing models
Income from House property explained in detail. One of these heads is “Income from House property”. The income earned by the ownership of a property is said to be Income from House property. If a taxpayer owns a house property and rents it, the rent received from that property is taxable. Your house, building, office, or shop can be termed as house property All types of properties are taxed under the head 'income from house property' in the income tax return.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
2. GLOSSARY
S.NO TOPICS
1 Introduction
2 Types of data based on structures and formats
3 Techniques of data analysis
4 Why data analysis is important ?
5 Data analysis process
6 Importance of data analysis in research
7 Types of data analysis
8 Tools used for data analysis
9 Advantages of data analysis
10 Disadvantages of data analysis
11 Conclusion
3. INTRODUCTION
◦ A process used by researchers for reducing data to a story and interpreting it to derive insights. The data
analysis process helps in reducing a large chunk of data into smaller fragments, which makes sense.
◦ Data interpretation is a process representing the application of deductive and inductive logic to the research
and data analysis.
◦ We analyze the data during research work because data analysis tells the most unforeseen yet exciting
stories that were not expected at the time of initiating data analysis. Therefore, rely on the data you have at
hand and enjoy the journey of exploratory research.
◦ Sometimes, data analysis can be a messy , ambiguous, and time-consuming but it is a fascinating and clear
piece of data through which various and number of data is being brought to a structure, order and
meaningful.
4. TYPES OF DATA BASED ON STRUCTURES AND
FORMATS
◦ Big data: A huge data set that continues to grow at an exponential rate over time. The four fundamental
characteristics of big data are volume, variety, velocity, and variability.
◦ Structured/unstructured data: Structured data is a predefined data model such as a traditional row-column
database. Unstructured data comes in a format that does not fit in rows and columns and can include
videos, photos, audio, text, and more.
◦ Metadata: A form of data that describes and provides information about other data. For example, metadata
for an image can include the author, image type, and date created. Metadata enables users to organize
unstructured data into categories, making it easier to work with.
◦ Real-time data: Data that is presented as soon as it is acquired. This type of data is useful when decisions
require up-to-the-minute information. For example, a stockbroker can use a stock market ticker to track the
most active stocks in real time.
◦ Machine data: This data is produced wholly by machines without human instruction.
5. TECHNIQUES OF DATA ANALYSIS
◦ Quantitative data analysis : Refers to working with numerical variables including statistics, percentages, calculations, measurements, and
other data as the nature of quantitative data is numerical. Quantitative data analysis techniques typically include working with
algorithms, mathematical analysis tools, and software to manipulate data and uncover insights that reveal the business value.
◦ Typical steps involved in quantitative data analysis: Regression analysis & hypothesis analysis.
◦ Regression analysis: A type of statistical analysis method that determines the relationships between independent and dependent
variables.
◦ For example, an independent variable can be the amount an individual invests in the stock market with the dependent variable thetotal
amount of money an individual will have when they retire.
◦ Two primary types of regression analysis : Simple linear and Multiple linear
◦ Simple linear regression analysis: It consists of a dependent variable and an independent variable. The mathematical representation of
the dependent variable is typically Y, while X represents the independent variable. Example:-A market researcher analyzing the
relationship between their company’s products and customer satisfaction.
◦ Multiple linear regression analysis :Contains various independent variables, resulting in a potentially complex formula for performing a
regression analysis
6. ◦ Hypothesis analysis : A data analysis technique that uses sample data to test a hypothesis and a statistical test method to validate an
assumption and determine if it’s plausible or factual.
◦ Two foundational components of hypothesis analysis : Null hypothesis and alternative hypothesis
◦ Qualitative data analysis: Describes information that is typically non numerical and approach involves working with unique
identifiers, such as labels and properties, and categorical variables, such as statistics, percentages, and measurements. A data
analyst may use firsthand or participant observation approaches, conduct interviews, run focus groups, or review documents and
artifacts in qualitative data analysis.
◦ Two main qualitative data approaches: Deductive and Inductive.
◦ Deductive approach: This analysis method is used by researchers and analysts who already have a theory or a predetermined idea of
the likely input from a sample population. The deductive approach aims to collect data that can methodically and accurately support
a theory or hypothesis.
◦ Inductive approach : In this approach, a researcher or analyst with little insight into the outcome of a sample population collects the
appropriate and proper amount of data about a topic of interest. Then, they investigate the data to look for patterns. The aim is to
develop a theory to explain patterns found in the data.
7. ◦ Two main qualitative data analysis techniques : Content analysis and Discourse analysis.
◦ Content analysis: Content analysis can reveal patterns in recorded communication that
indicate the purpose, messages, and effect of the content. An analyst could identify instances
where the word “employment” appears in social media, news stories, and other media and
correlates with other relevant terms, such as “economy,” “business,” and “Main Street.”
◦ Components of content analysis: Identify data sources, Determine data criteria, Develop
coding for the data and Analyze the results.
◦ Discourse analysis : Helps provide an understanding of the social and cultural context of
verbal and written communication throughout conversations. Discourse analysis aims to
investigate the social context of communication and how people use language to achieve
their aims, such as evoking an emotion, sowing doubt, or building trust . Discourse analysis
helps interpret the true meaning and intent of communication and clarifies misunderstanding
◦ Steps in discourse analysis :Define the research question, Select the content types, Collect the
data and Analyze the content.
8. WHY DATA ANALYSIS IS IMPORTANT ?
◦ Better Customer Targeting: You don’t want to waste your business’s precious time, resources, and money putting together advertising
campaigns targeted at demographic groups that have little to no interest in the goods and services you offer. Data analysis helps you
see where you should be focusing your advertising efforts.
◦ You Will Know Your Target Customers Better: Data analysis tracks how well your products and campaigns are performing within your
target demographic. Through data analysis, your business can get a better idea of your target audience’s spending habits, disposable
income, and most likely areas of interest. This data helps businesses set prices, determine the length of ad campaigns, and even help
project the quantity of goods needed.
◦ Reduce Operational Costs: Data analysis shows you which areas in your business need more resources and money, and which areas
are not producing and thus should be scaled back or eliminated outright.
◦ Better Problem-Solving Methods: Informed decisions are more likely to be successful decisions. Data provides businesses with
information. You can see where this progression is leading. Data analysis helps businesses make the right choices and avoid costly
pitfalls.
◦ You Get More Accurate Data: If you want to make informed decisions, you need data, but there’s more to it. The data in question
must be accurate. Data analysis helps businesses acquire relevant, accurate information, suitable for developing future marketing
strategies, business plans, and realigning the company’s vision or mission.
9. DATA ANALYSIS PROCESS
◦ It involves gathering all the information, processing it, exploring the data, and using it to find patterns and other insights.
◦ This process contains number of steps which organizes and makes the data in a typical manner. They are:
◦ Data Requirement Gathering: Be sure why you are analyzing the data which you have collected for the research report
and what type of data analysis you are planning to exhibit it out.
◦ Data Collection : This step involves collecting of data from various number of sources like case studies, surveys,
interviews, questionnaires, direct observation, and focus groups. Organizing the data is important.
◦ Data Cleaning : This step is a mandatory one because all the data's which we collect is not useful for representing it out or
for a research report so some duplicate reports, white blank spaces , etc. will be cleaned off. This step is done before the
information is sent for analyzing process.
10. ◦ Data Analysis: Here is where you use data analysis software and other tools to help you interpret and understand the
data and arrive at conclusions. Data analysis tools include Excel, Python, R, Looker, Rapid Miner, Chartio, Metabase,
Redash, and Microsoft Power BI.
◦ Data Interpretation: Now that you have your results, you need to interpret them and come up with the best courses of
action, based on your findings.
◦ Data Visualization: A fancy way of saying, “graphically show your information in a way that people can read and
understand it.” You can use charts, graphs, maps, bullet points, or a host of other methods. Visualization helps you
derive valuable insights by helping you compare datasets and observe relationships.
0
1
2
3
4
5
6
Category 1 Category 2 Category 3 Category 4
Series 1 Series 2 Series 3
11. IMPORTANCE OF DATA ANALYSIS IN RESEARCH
A huge part of a researcher’s job is to sift through data. That is literally the definition of
“research.” However, today’s Information Age routinely produces a tidal wave of data,
enough to overwhelm even the most dedicated researcher. Data analysis, therefore,
plays a key role in distilling this information into a more accurate and relevant form,
making it easier for researchers to do to their job. Data analysis also provides
researchers with a vast selection of different tools, such as descriptive statistics,
inferential analysis, and quantitative analysis. So, to sum it up, data analysis offers
researchers better data and better ways to analyze and study said data.
12. TYPES OF DATA ANALYSIS
◦ Diagnostic Analysis: The process of using data to determine the causes of trends and correlations between variables. It can be viewed
as a logical next step after using descriptive analytics to identify trends.
◦ Predictive Analysis: The use of data, statistical algorithms and machine learning techniques to identify the likelihood of future
outcomes based on historical data.
◦ Prescriptive Analysis: A form of data analytics that tries to answer "What do we need to do to achieve this?“ It uses machine learning
to help businesses decide a course of action based on a computer program’s predictions.
◦ Statistical Analysis: The collection and interpretation of data in order to uncover patterns and trends. It is a component of data
analytics. Statistical analysis can be used in situations like gathering research interpretations, statistical modeling or designing surveys
and studies.
◦ Descriptive analysis : The type of analysis of data that helps describe, show or summarize data points in a constructive way such that
patterns might emerge that fulfill every condition of the data.
◦ Inferential: Inferential analysis is used to generalize the results obtained from a random (probability) sample back to the population
from which the sample was drawn.
◦ Text Analysis: A methodology that involves understanding language, symbols, and/or pictures present in texts to gain information regarding
how people make sense of and communicate life and life experiences.
14. ADVANTAGES OF DATA ANALYSIS
◦ It detects and correct the errors from data sets with the help of data cleansing.
◦ It removes duplicate information's from data sets and hence saves large amount of memory space. This decreases cost to
the company.
◦ It helps in displaying relevant advertisements on the online shopping websites based on historic data and purchase
behavior of the users.
◦ It reduces banking risks by identifying probable fraudulent customers based on historic data analysis. This helps institutes
in deciding whether to issue loan or credit cards to the applicants or not.
15. DISADVANTAGES OF DATA ANALYSIS
◦ Lack of alignment within teams
◦ Lack of commitment and patience
◦ Low quality of data
◦ Privacy concerns
◦ Complexity and bias
16. CONCLUSION
◦ The conclusion is the essential step in completing the data analysis process. The conclusion gives important
inferences derived from the study and bind them together as a final summary of findings.
◦ Cause and effect: The conclusion should be derived based on cause and effect relations. The cause and effect
among the data variables, classes, samples, and groups provide a final conclusion.
◦ Generalizations: Though generalization should be avoided; certain large samples can be generalized to derive
conclusions. The populations with simple structures, small populations that can find certain general
characteristics among themselves can be generalized.
◦ Data Reporting: All the organized data, along with findings, and results in the visualized form, should be
reported on the paper in the form of a document and following a certain format that is called data report or
research paper/thesis. Final reporting of data in the prescribed format, along with research question,
methodology, and literature review, must be put together as a report in the final step of data analysis and
conclusion.