Business Analytics Final Exam

Data overload

the access or exposure to too much data that prevents data from being properly synthesized and interpreted

SOAR Analytics model

it is the major framework for developing a business analytics mindset. It is composed of 4 steps:

1.       Specify the Question

2.       Obtain the Data

3.       Analyze the Data

4.       Report the Results

1

Specify the Question

2

Obtain the Data

3

Analyze the Data

4

Report the Results

Structured Data

data that is organized in a specific, predefined manner, making it easily readable and understandable by both humans and machines

2 types of structured data

Categorical data and Numerical data

categorical data

data that is categorized into groups that are represented either by words or by non-meaningful numerical data

categorical data

ex. grouping by age, categorizing transaction types, or specifying inventory costing method

numerical data

meaningful numbers that represent quantities

numerical data

ex. transaction amount, age, net income, or score on an exam

2 types of categorical data

nominal data and ordinal

nominal data

o   categorical data that cannot be ranked (summarized through counting and grouping or proportion)

nominal data

ex. country of origin and transaction type

ordinal data

categorical data with a natural order that allows them to be ranked and sorted (summarized through counting and grouping, proportion, or ranking/sorting)

ordinal data

ex. letter grade and Olympic medals

2 types of numerical data

interval data and ratio data

interval data

measured along a scale, with an equal and definitive interval or distance between each data point but no meaningful zero (counting and grouping, proportion, summing, and averaging)

interval data

ex. temperature and SAT Scores

ratio data

numerical data with an equal and definitive value between each data point, and with a meaningful zero (counting and grouping, proportion, summing, and averaging)

ratio data

ex. data measuring money, including all kinds of financials

big data concerns

Big data are data sets that are too large and complex for businesses’ existing systems to capture, store, manage, and analyze (1) cybersecurity and privacy, (2) data quality, and (3) integration and data silos

Volume, Velocity, Veracity, and Variety

4 Vs of Big Data

volume

the sheer amount of data

velocity

the speed that the data are being generated or the rate that data are being analyzed

veracity

the underlying truthfulness, accuracy (cleanliness), and trustworthiness of data

variety

different forms of data

population

group of phenomena that have something in common and is composed of every item of interest in that group (ex. every single retail store in the U.S.)

sample

a subset of members of a population (ex. 24% of retail stores in the U.S.)

statistic

a characteristic of a sample (ex. 24% of retail stores in the U.S. are open on Sunday)

parameter

characteristic of a population (ex. 28% of all retail stores in the U.S. are open on Sunday)

nonresponse bias

bias that results when respondents differ from non-respondents. This would be the bias that comes from people choosing not to do the survey for some reason.

selection bias

the bias that is introduced by the selection of individuals or data that are likely to sway the results of a study in favor of the analyst’s beliefs or hypothesis

confirmation bias

the bias that occurs when analysts analyze or present results in a manner that confirms their existing beliefs or theories while ignoring data and analysis that do not confirm their beliefs

outlier bias

the potential disproportionate influence of outliers in study results

mean

average of the measurements in a data set

median

the value that lies at the center of the data

mode

the most common observation in a data set (most)

symmetrical distribution

mean = median = mode

right-skewed

mean > median > mode

left-skewed

mean < median < mode

descriptive analytics

What happened? What is happening?

diagnostic analytics

Why did it happen? What are the causes of past results? Why are the results different than expectations?

predictive analytics

Will it happen in the future? What is the probability of something happening? Can we forecast what will happen?

prescriptive analytics

What should we do, based on what we expect will happen? How do we optimize our performance based on potential constraints?

adaptive analytics

How can we continuously learn using artificial intelligence? Can we learn from past and current events with adaptive learning?

predictive analytics (e)

What will product sales be? Or what is the chance the company will go bankrupt?

diagnostic analytics

why did revenue change? Or why did bond prices fall?

sorting

makes data for data visualization more meaningful and easier to identify. Can be done by category or numerically.

pie chart

a circular graph in which each slice represents the category’s proportion of the whole

stacked bar graph

a variation of a standard bar chart that allows you to visualize two categorical variables at once. Each bar represents a primary category and is divided into segments (sub-bars) that correspond to levels of a secondary category. The total length of the bar shows the overall value.

tree map

uses size and color to show the proportional size of values using physical space. It is made up of different sized rectangles with the color representing another category.

marketing mix

refers to the key choices that a company makes to bring a product/service to market. It consists of product, price, place, and promotion.

product, price, place, and promotion

4 Ps of the marketing mix

product

the good or service that a company offers to customers

price

the amount that a customer pays for a product

place

where the company sells a product and how the product is delivered to the market

promotion

all of the marketing communication strategies and techniques used to convince customers that they need the product at the specified price

product life cycle

the four phases (introduction, growth, maturity, and decline) that products go through, beginning with development and ending with decline/market removal

marketing dashboard

a visual management tool that helps track and monitor KPIs to improve marketing effectiveness

Financial, managerial, auditing, and tax accounting

4 branches of accounting

financial accounting

branch of accounting that focuses on collecting and analyzing business performance information for external decision makers. They provide information of the company’s performance, financial position, and financial statements under GAAP

managerial accounting

branch of accounting that focuses on collecting and analyzing business-performance information for internal decision makers (management). Does not have a set of accounting rules and solely exists to address management’s questions.

auditing

branch of accounting that investigates accounting and financial records to determine if they conform with GAAP or other relevant standards or laws. They work to fix errors, inaccuracies, and fraud.

tax accounting

branch of accounting that focuses on collecting and analyzing transactions to ensure they conform with tax law and minimizing future taxes through tax planning.

10-K, 10-Q, and 8-K

Forms required to be filed with the SEC

10-K

reports a company’s annual financial performance

10-Q

required quarterly submission reporting a company’s financial performance

8-K

notifies investors of important events or announcements

(new value - old value) / old value

percentage change formula

R-square

a measure to describe how well a simple regression (one independent variable) model predicts the dependent variable. The closer the value is to 1, the more prediction power it has (explains this percent of variation)

P-value

explains whether there is a significant relationship in the regression, the smaller the better (>0.05)

Significance F

evaluates whether a linear regression model provides a better fit of the data than a model that contains no independent variables. A very low significance power means it is a better model.

Regression coefficients

quantities by which variables in a regression equation are multiplied (slope of the line). Pay attention to whether it is positive or negative. This predicts what percent it will increase/decrease by 1 unit.

Human resources, IT operations, Supply Chain

3 branches of operations

human resources

focuses on managing and developing a company’s workforce

IT operations

how the company manages its hardware, software, and IT support

Supply Chain

responsible for the production of a good or service and its distribution to the final consumer

cash to cash cycle (DI + DAR - DAP)

measures the length of time between the company paying its vendors and the company receiving cash from its customers. The lower the ratio, the better

asset turnover (sales revenue/TA)

measures sales revenue generated by the company’s assets, the higher the better the efficiency

inventory to sales (inventory/sales)

measures amount of inventory being carried to fulfill sales, lower the better

inventory turnover (COGS/Inventory)

measures the number of times inventory is sold during the year, the higher the better

data mining

process of analyzing large amounts of data to identify patterns, anomalies, and relationships.

machine learning

statistical techniques that allow a computer to “learn” from data without being explicitly programmed

artificial neural network (ANNs)

a type of machine learning that uses connected processing nodes resembling the human brain

deep learning

when ANNs can be trained to recognize, classify, and describe unstructured data such as text, images, and voice. The more examples provided the more accurate the prediction.

customer segmentation

the process of grouping customers based on shared characteristics