Data Analytics - Exam 1

raw figures and captured facts, such as categories, measures, and calculations

knowledge gained from data that is relevant for analysis purposes

the process of analyzing raw data to answer questions or provide insights

easy-to-use, accessible software that can prepare data, analyze data, and report results

two key features of SSBI software

an unknown or missing value in a data set

graphical representation of information and data to provide meaning and insights during the data analysis process

a graphical user interface that shows key performance indicators for an organization; useful tool to communication key information to everyone who needs it

three stages in the data analysis process

three steps in the planning stage of the data analysis process

the reason or stimulus for performing data analysis; the “why” behind a project

the project originates from a request or requirement by another party, such as external stakeholders (investors, creditors, etc.)

the project originates by a desire to better serve a client, better understand phenomena to gain business intelligence, or to perform job responsibilities; the incremental information gained is believed to outweigh potential costs involved with performing the data analyses

the goal of a data analytics project; a statement that details what the project will accomplish

two aspects involved in developing a strategy for the planning stage

two categories of data

data generated within an organization, such as sales and customer data; more easily controlled and verified by an organization

data that are acquired from outside an organization, such as weather or social media data; somewhat riskier to use since we often cannot know if the data are accurate or complete; can provide more insights that internal data alone cannot provide

four types of data analysis methods

data analysis method designed to understand and investigate what is currently happening or what has happened in the past; most common and easily understood analytics method; first analytics method performed to help understand data; examples include - sum, count, average, median, standard deviation

data analysis method designed to understand and reveal why something has happened; examples include - anomaly and outlier detection, trend analysis, pattern recognition

data analysis method that helps understand and predict what is likely to happen in the future; method uses data, statistical algorithms, and machine learning to identify the likelihood of future outcomes based on historical data; examples include - forecasting, regression analysis, time-series analysis

data analysis method that determines the best course of action to achieve a goal in a specific scenario; helps understand what should happen to meet goals and objectives; these analyses recommend one or more possible courses of action; examples include optimization and what-if analyses

three steps in the analysis stage of the data analysis process

the process of retrieving raw data from a source, cleaning, restructuring, and/or integrating them with other data, and then loading the data into software for analysis purposes

what does extracting in the ETL process refer to?

what does transforming in the ETL process refer to?

process of reviewing the data for possible issues

what does loading in the ETL process refer to?

the creation of information needed for analysis purposes, starting from the data collected; examples include - calculations for net income, profit margins, total assets, etc.

what does exploring data in the analysis stage refer to?

two steps in the reporting stage of the data analysis process

what does data analysis interpretation in the reporting stage refer to?

different ways in which the results of a data analysis project can be communicated

the professional habit of critically thinking through the planning, analysis, and reporting of data analysis results before making and communicating a professional choice or decision; minimizes the risk of biased or subjective thoughts; businesses can make decisions based on evidence rather than assumptions; individuals must focus on developing skills such as critical thinking, data literacy, technological agility, and communication skills

a data analytics mindset includes the abilities to …

four skills in developing a data analytics mindset

disciplined reasoning used to investigate, understand, and evaluate an event, opportunity, or issue; the foundation of a data analytics mindset

the human process of logically forming conclusions, judgements, or inferences from facts

the ability to read, write, and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied, and the ability to describe the use of case application and resulting value

an awareness of the latest technological developments and a willingness to work with new tools and try new things; the ability to quickly and smoothy adapt to or integrate current technologies with newer, different, disruptive, expansive, or convergent technologies

being able to concisely, coherently share results to multiple audiences; involves writing clear and effective memos and reports, preparing successful presentations, creating meaningful data visualizations for analysis, and telling compelling data stories

six elements of critical thinking when performing data analytics

individuals or groups who may be impacted by and/or have an interest in the outcome of a data analysis project

individuals or groups involved in a business’ operations who may be impact by and/or have an interest in the outcome of a data analysis project; includes an organization’s managers and employees

individuals or groups outside a company who may be impacted by and/or have an interest in the outcome of a data analysis project; includes investors, creditors, regulators, etc.

identifying the purpose in critical thinking refers to

three types of questions

type of question that employs evidence and reasoning within a specific domain; you can reach a correct answer

type of question that employs evidence and reasoning across several domains; you can reach an informed judgment, but there are better and worse answers

type of question that requires stating a subjective preference; cannot assess the answer

different options that are considered and ranked based on the objectives and goals of the data analysis

what does considering the alternatives in critical thinking involve?

obstacles and challenges to our thinking or analyses

four types of risk

risk that involves choosing inappropriate data, or data that are incomplete or incorrect

risk that involves choosing an inappropriate type of analysis, or apply a data analysis method incorrectly

risk that involves not understanding or evaluating assumptions about the data or results

risk that involves unconscious and mental shortcuts that can affect decisions; closed-minded

the concepts that add meaning to the data and analyses

identifying knowledge gaps in critical thinking includes

a review of what worked and what did not

performing self-reflection in critical thinking includes

critical thinking - decisions that are:

five v’s of data

the amount of data selected for an analysis project

a popular solution for storing high volume data; these services provide secure data storage on large servers using the organization’s own resources or third-party resources

benefits of cloud data services

three types of cloud data services

data clouds with restricted access that store the data for one organization or shared between an agreed-upon group of organizations; often include a single large company, a group of supply chain partners, or non-competing independent companies from different industries

benefits of data storage for a single organization

costs of data storage for a single organization

benefits of data storage that is shared by a set group of non-competing organizations

costs of data storage that is shared by a set group of non-competing organizations

data clouds that securely store data from multiple companies on shared servers using virtual server data separators; shared by many organizations who can easily come and go

benefits of public clouds

cost of public clouds

data clouds that offer both private and public cloud data storage, serving the needs of the security and use characteristics of the data involved; allow organizations to choose which data subset is best stored in a private cloud, while storing the rest in public clouds for cost efficiencies

the diversity of data structures and measurement scales in data that are useful for analysis

the speed at which new data points are generated

the reliability, or the integrity of the data used for analysis

three things data veracity depends upon

the benefits of certain data given the objective of a data analysis project

the systematic process/practice of looking for issues or patterns occurring within or between data fields; lets us better understand data behavior and test expectations about data values, patterns, or relationships; most common form of data analytics

new online technology that creates a single, shared record of transactions between parties

secure, online shared digital contracts; specific and popular application of blockchain technology; allow business contracts to be securely negotiated, settled, and signed online in a fraction of the traditional time

set of software technologies that record a specific order of human keystrokes and mouse activity steps within or across digital applications; used for stable processes where the steps of the process do not change over time; once saved or recorded, these routines can be repeated by simply rerunning the tool

tools that measure the timing and flow of data captured as business events occur; help businesses better evaluate process efficiency and effectiveness

programmed modules embedded in an organization’s AIS that evaluate transactions as they occur throughout the year; routine transactions are typically captured and tested in automated routines for consistent processing; results in more accurate assessment of risk and reduces audit workload at year end

the process of analyzing word choice in footnotes, investor communications, blogs, social media postings, and other documentation

the process of transforming text into a format that can be used for analysis; evaluates word choice and usage to reveal insights about honesty, transparency, intent, and sentiments in communications by management, elected officials, and customers

artificial intelligence technologies that use algorithms that mimic the human thought process; can range from simplistic decision models to dynamic, complex models

a collection of data columns and rows available for analysis

a collection of logically related data that can be retrieved, manipulated, and updated to meet users’ needs; structured tables composed of rows and columns

how data related to an object of interest are stored and linked in a relational database; can be linked together with relationships

a database is a collection of …

tables are comprised of…

what does each row in a table represent?

data in the rows of the data set representing instances of the phenomena being captured; represent the collection of columns that hold the descriptions of a single occurrence of the data set’s purpose

a specific, unique representation of the entity; rows of a data set