Build me a PowerPoint presentation about data analytics and create two small case study tutorials
Budget: $200 – $250 USD
I would like you to build me a PowerPoint presentation about data analytics. The PowerPoint presentation must be about 360 slides.
Each slide must have an accompanying script for the presentation written in professional English.
I have uploaded an outline of the major topics of the presentation. I also list them below, but please refer to the attached outline because it is formatted more clearly.
Part 1
Data and Information
Data in the real world - benefits, challenges in reality
Data vs. information
The many "Vs" of data
Structured data and unstructured data
Types of data - qualitative and quantitative
Data analysis defined
Why do we analyze data?
Data analysis defined
Data analysis mindset
Data analysis steps
Descriptive statistics versus inferential statistics
Types of variables and data acquisition
Types of variables
Sources of data
Ways to acquire data
Sampling techniques
Tabular and Graphical Presentations of Data (examples of each)
Tabular and graphical methods for describing qualitative data (summary tables, contingency tables, bar charts, pie charts, and side-by-side bar charts)
Tabular and graphical methods for describing quantitative data (ordered array, frequency distribution, histogram, ogive, and maps)
Potential errors in charting - wrong charts for the type of data, misleading axis ranges, incorrect use of colors or symbols, etc.
Part 2
Organizing data for a better analysis
Analyzing raw data using sorting, filtering, and cross-tabulation (pivot tables excel tools)
Case study MS Excel example: analyzing sales data in different regions of the US
Simple and multiple linear regression
Correlation (vs. causation)
Simple linear regression models
Measures of variation and coefficient of determination
Tests of significance
Clustering
The central tendency of data
correlation
(arithmetic) mean
median
mode
Part 3
Basic probability
Probability uses in business
Ways we can calculate the probability
Probability terms
Calculating probability
Calculating probability from a contingency table
Conditional probability
Frequency distribution
Distributions, variance, and standard deviation
Discrete distributions
Continuous distributions
Range
Quartiles
Variance
Standard deviation
Fitting data
Bivariate data (two variables)
Covariance and correlation
Simple linear regression
Linear regression
Fitting functions
Predictive analytics
Monte Carlo simulation
Emerging Topics in Data Analytics
Artificial Intelligence, Machine Learning, Deep Learning – Advantages and challenges
Big Data storage and analytics – Advantages and challenges
Challenges and strategies for visualization
Case study: Streamlining logistics
I also require two simple data analysis case study tutorials using Excel, and you provide me with the accompanying data. The case studies should use Excel and show a simple, realistic business data analysis on the two case study topics highlighted in the outline.
Requirements:
Slides should have minimal text.
Slides should have lots of meaningful images and figures that illustrate the concepts.
Images cannot be from copyrighted sources (I will check this).
Text cannot be plagiarized (I will check this).
Slides must be visually appealing and professional.
Slide text and script must be written in professional English without grammatical and spelling errors.
Slide style cannot be from a copyrighted source.
The presentation must include current best commercial practices.
Each slide must have an accompanying script for the presentation written in professional English.
I have uploaded an outline of the major topics of the presentation. I also list them below, but please refer to the attached outline because it is formatted more clearly.
Part 1
Data and Information
Data in the real world - benefits, challenges in reality
Data vs. information
The many "Vs" of data
Structured data and unstructured data
Types of data - qualitative and quantitative
Data analysis defined
Why do we analyze data?
Data analysis defined
Data analysis mindset
Data analysis steps
Descriptive statistics versus inferential statistics
Types of variables and data acquisition
Types of variables
Sources of data
Ways to acquire data
Sampling techniques
Tabular and Graphical Presentations of Data (examples of each)
Tabular and graphical methods for describing qualitative data (summary tables, contingency tables, bar charts, pie charts, and side-by-side bar charts)
Tabular and graphical methods for describing quantitative data (ordered array, frequency distribution, histogram, ogive, and maps)
Potential errors in charting - wrong charts for the type of data, misleading axis ranges, incorrect use of colors or symbols, etc.
Part 2
Organizing data for a better analysis
Analyzing raw data using sorting, filtering, and cross-tabulation (pivot tables excel tools)
Case study MS Excel example: analyzing sales data in different regions of the US
Simple and multiple linear regression
Correlation (vs. causation)
Simple linear regression models
Measures of variation and coefficient of determination
Tests of significance
Clustering
The central tendency of data
correlation
(arithmetic) mean
median
mode
Part 3
Basic probability
Probability uses in business
Ways we can calculate the probability
Probability terms
Calculating probability
Calculating probability from a contingency table
Conditional probability
Frequency distribution
Distributions, variance, and standard deviation
Discrete distributions
Continuous distributions
Range
Quartiles
Variance
Standard deviation
Fitting data
Bivariate data (two variables)
Covariance and correlation
Simple linear regression
Linear regression
Fitting functions
Predictive analytics
Monte Carlo simulation
Emerging Topics in Data Analytics
Artificial Intelligence, Machine Learning, Deep Learning – Advantages and challenges
Big Data storage and analytics – Advantages and challenges
Challenges and strategies for visualization
Case study: Streamlining logistics
I also require two simple data analysis case study tutorials using Excel, and you provide me with the accompanying data. The case studies should use Excel and show a simple, realistic business data analysis on the two case study topics highlighted in the outline.
Requirements:
Slides should have minimal text.
Slides should have lots of meaningful images and figures that illustrate the concepts.
Images cannot be from copyrighted sources (I will check this).
Text cannot be plagiarized (I will check this).
Slides must be visually appealing and professional.
Slide text and script must be written in professional English without grammatical and spelling errors.
Slide style cannot be from a copyrighted source.
The presentation must include current best commercial practices.