Data Analytics

[Mod 2] 6 stages of the Data Life Cycle

(1.) Plan: Decide what kind of data is needed, how it will be managed, and who will be responsible for it. (2.) Capture: Collect or bring in data from a variety of different sources. (3.) Manage: Care for and maintain the data. This includes determining how and where it is stored and the tools used to do so. (4.) Analyze: Use the data to solve problems, make decisions, and support business goals. (5.) Archive: Keep relevant data stored for long-term and future reference. (6.) Destroy: Remove data from storage and delete any shared copies of the data.

[Mod 1] The analytical skill that involves breaking processes down into smaller steps and working with them in an orderly, logical way

A technical mindset

[Mod 1] An airline collects, observes, and analyzes its customers' online behaviors. Then, it uses the insights gained to choose what new products and services to offer. What business process does this describe? Analytical thinking Performance measurement Collaboration with stakeholders Data-driven decision-making

An airline collecting, observing, and analyzing its customers' online behaviors, then using the insights gained to choose what new products and services to offer, describes data-driven decision making. Data-driven decision-making is using facts to guide business strategy.

[Mod 1] The qualities and characteristics associated with solving problems using facts

Analytical skills

[Mod 1] What practice involves identifying, defining, and solving a problem by using data in an organized, step-by-step manner?

Analytical thinking

[Mod 2] After opening the ice cream shop on her farm, the same dairy farmer then surveys the local community about people's favorite flavors. She uses the data she collected to determine that the top five flavors are strawberry, vanilla, chocolate, mint chip, and peanut butter. She feels confident in her decision to sell these flavors. This is part of which phase of the data life cycle?

Analyze

[Mod 2] In the data life cycle, which phase involves gathering data from various sources and bringing it into the organization?

Capture

[Mod 2] In the processing phase, the aim is to refine the data. Data analysts find and eliminate any errors and inaccuracies that can get in the way of results. This usually means:

Cleaning data Transforming data into a more useful format Combining two or more datasets to make information more complete Removing outliers (data points that could skew the information) *Spreadsheets and SQL

[Mod 1] Fill in the blank: Gathering additional information about data to understand the broader picture is an example of understanding _____.

Context

[Mod 1] Which aspect of analytical thinking involves being able to identify a relationship between two or more pieces of data?

Correlation

[Mod 1] Analytical skills

Curiosity Understanding of context Technical mindset Data design Data strategy

[Mod 1] Which of the following terms refers to the collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making?

Data Analysis

[Mod 1] Fill in the blank: The analytical skill _____ encompasses how someone organizes information.

Data design

[Mod 1] The analytical skill that involves how you organize information

Data design

[Mod 1] The analytical skill that involves managing the processes and tools used in data analysis

Data strategy

[Mod 1] A company is seeing a decline in organizational efficiency. They decide to hire an outside organization to help increase overall performance. The data analyst, working for the newly contracted company, utilizes five analytical skills: curiosity, understanding context, having a technical mindset, data design, and data strategy to deliver the project goals. Once the project goals are met, the analyst informs the decision makers of their findings and the project is completed. What strategy did the data analyst use to complete this project?

Data-driven decision making

[Mod 1] Fill in the blank: Analytical skills are the qualities and characteristics associated with using _____ to solve problems.

Facts

[Mod 2] A data analyst finishes using a dataset, so they erase or shred the files in order to protect private information. This is called archiving.

False. Erasing or shredding files describes the destroy phase of the data life cycle. Archiving involves storing files in a place where it's still available.

[Mod 1] Fill in the blank: _______ is a method examining and evaluating how a process works currently in order to get where you want to be in the future.

Gap analysis

[Mod 1] Which of the following are examples of data visualizations? Select all that apply.

Graphs, maps, and charts

[Mod 2] A dairy farmer decides to open an ice cream shop on her farm. After surveying the local community about people's favorite flavors, she takes the data they provided and stores it in a secure hard drive so it can be maintained safely on her computer. This is part of which phase of the data life cycle?

Manage. This is the manage phase of the data life cycle. It deals with how data is cared for, how and where it's stored, the tools used to keep it safe and secure, and the actions taken to make sure it's maintained properly.

[Mod 1] Scenario: Use data to create better movies The movies Mega-Pik has released recently aren't having the impact they used to. Five of their last six releases barely broke even at the box office, and the sixth film lost a lot of money. The lead executives at Mega-Pik have noticed that their competitors went through a similar slump, but recovered when they started producing remakes of past successes and marketing them to a new audience. Mega-Pik is interested in following this trend. They want to do this based on data-driven strategies, so they hire your analytics company to help them make popular movies again. Specifically, they ask for exploratory data analysis (EDA) to help them understand what audiences have liked in the past and determine if the successes of those films can be replicated. Your company collects, cleans, and organizes the following relevant information into a dataset:

Movie name Release date Opening night revenue Opening weekend revenue Budget (cost to create) Marketing costs Ratings Genre

[Mod 1] Fill in the blank: In data analytics, the data ecosystem refers to the various elements that interact with one another to produce, manage, store, _____, analyze, and share data.

Organize

[Mod 2] Fill in the blank: During the _____ phase of the data life cycle, a business decides what kind of data it needs, how it will be managed, who will be responsible for it, and the optimal outcomes.

Planning

[Mod 1] Curiosity is an analytical skill that involves which of the following?

Seeking out new challenges and experiences

[Mod 2] At the start of any successful data analysis, the data analyst:

Takes the time to fully understand stakeholder expectations Defines the problem to be solved Decides which questions to answer in order to solve the problem

[Mod 1] Which analytical skill involves the ability to break things down into smaller steps and work with them in an orderly and logical way?

Technical mindset

[Mod 2] Understanding the importance of the data life cycle will set you up for success as a data analyst. Individual stages in the data life cycle will vary from company to company or by industry or sector. Historical data is important to both the U.S. Fish and Wildlife Service and the USGS, so their data life cycle focuses on archiving and backing up data. Harvard's interests are in research and teaching, so its data life cycle includes visualization and interpretation even though these are more often associated with a data analysis life cycle. The HBS data life cycle also doesn't call out a stage for purging or destroying data. In contrast, the data life cycle for finance clearly identifies archive and purge stages.

To sum it up, although data life cycles vary, one data management principle is universal: Govern how data is handled so that it is accurate, secure, and available to meet your organization's needs.

[Mod 1] Fill in the blank: In data analysis, data strategy involves managing the people, processes, and _____ .

Tools

[Mod 1] Data analysts ask, "Why?" five times in order to get to the root cause of a problem.

True

[Mod 1] Gap analysis is used to examine and evaluate how a process currently works with the goal of getting to where you want to be in the future.

True

[Mod 1] An acquaintance tells you that they spend many hours each day "playing." To learn more, you ask them whether they play sports, a musical instrument, or something else. Their answer helps you clarify the meaning of their statement. What does this scenario describe?

Understanding context

[Mod 1] The analytical skill that has to do with how you group things into categories

Understanding context

[Mod 2] With a solid foundation of well-defined questions and clean data, you'll delve into the analyze phase. This is when you turn the data you've gathered, prepared, and processed into _____________. In one upcoming course you'll continue using two of them: spreadsheets and SQL. In another upcoming course you'll explore using the programming language R to work with and analyze data.

actionable information.

[Mod 2] 6 stages of the data life cycle vs. 6 phases of the data analysis process

data life cycle = plan, capture, manage, analyze, archive, and destroy (PCMAAD) data analysis process = ask, prepare, process, analyze, share, and act (APPASA)

[Mod 2] In the prepare phase, the emphasis is _______?

on identifying and locating data you can use to answer your questions.

[Mod 2] In the share phase, __________ is a data analyst's best friend. So, an upcoming course will highlight why visualization is essential to getting others to understand what your data is telling you. In another upcoming course, you'll learn how to visualize data with R.

visualization

[Mod 1] The 5 aspects of analytical thinking

visualization, strategy, problem-orientation, correlation, and big-picture and detail-oriented thinking,

[Mod 1] Scenario: Use data to create better movies The movies Mega-Pik has released recently aren't having the impact they used to. Five of their last six releases barely broke even at the box office, and the sixth film lost a lot of money. The lead executives at Mega-Pik have noticed that their competitors went through a similar slump, but recovered when they started producing remakes of past successes and marketing them to a new audience. Mega-Pik is interested in following this trend. They want to do this based on data-driven strategies, so they hire your analytics company to help them make popular movies again. Specifically, they ask for exploratory data analysis (EDA) to help them understand what audiences have liked in the past and determine if the successes of those films can be replicated. You and your team develop the following objectives for Mega-Pik's EDA:

Identify key factors that contribute to a movie's opening weekend success. Understand the relationship between a movie's budget and its revenue. Determine which genres are most successful.