Google Data Analytics

What are some key benefits of data visualizations? Select all that apply.

*Graphs and charts help people understand complex data *Visuals enable data professionals to more effectively share insights with others. Data visualizations are more engaging than tables and numbers.

Which of the following activities are part of the manage phase of the data life cycle? Select all that apply.

*Select tools to keep data secure *Decide where to store data *Reflect on how to care for data

To execute a plan using detail-oriented thinking, what does a data analyst consider?

, a data analyst considers the specifics.

Which of the following examples demonstrate data-driven decision-making? Select all that apply.

- A dentist's office uses specifics from patient records to track treatment outcomes and improve quality of care. - A school district uses report cards to track performance and identify areas where students need additional support. - A financial advisor interviews clients to assess their risk tolerance and investment goals in order to create personalized plans.

Which of the following statements correctly describe data and data analysis? Select all that apply.

- Collecting data is part of the data analysis process. - Data is a collection of facts. - One goal of data analysis is to make predictions

Which of the following activities are elements of data-driven decision-making? Select all that apply.

- Determine the problem to be solved - Analyze data - Uncover trends or patterns

Which of the following scenarios demonstrate analytical thinking? Select all that apply.

- You notice that two pieces of data trend in the same direction and investigate them further to check for correlation. - You identify and define a problem, then solve it by using data in an organized manner. - You select and design a graph to communicate your data in an appropriate and accessible way.

5 key aspects to analytical thinking

1. Visualization 2. Strategy 3. Problem-orientation 4. Correlation 5. Big-picture and detail-oriented thinking

database

A collection of data stored in a computer system

Query

A request for data or information from a database

Spreadsheets

Accessed through a software application Structured data in a row and column format Organizes information in cells Provides access to a limited amount of data Manual data entry Generally one user at a time Controlled by the user suitable for organizing, cleaning, and analyzing small to medium datasets

Which of the following statements accurately describe spreadsheet attributes and observations? Select all that apply.

An attribute is a characteristic or quality of data. An observation is a spreadsheet row. Attributes are often referred to as column names or headers.

Phase 3: Process

Clean and transform data to ensure integrity

Capture phase

Collect or bring in data from a variety of different sources.

problem-oriented

Data analysts use a problem- oriented approach in order to identify, describe, and solve problems. It's all about keeping the problem top of mind throughout the entire project.

act

For our final data analysis phase, we have act. This is the exciting moment when the business takes all of the insights you, the data analyst, have provided and puts them to work in order to solve the original business problem

manage

Here we're talking about how we care for our data, how and where it's stored, the tools used to keep it safe and secure, and the actions taken to make sure that it's maintained properly. This phase is very important to data cleansing, : Care for and maintain the data. This includes determining how and where it is stored and the tools used to do so.

Analytical thinking

Identifying and defining a problem and then solving it by using data in an organized, step-by-step manner

Phase 5: Share

Interpret and communicate results to others to make data-driven decisions

A data team at a timber company works on a project aimed at planting more trees and eliminating deforestation. They discuss what type of data they need and how it will be managed throughout its life cycle. What phase of the data life cycle does this scenario describe?

Plan

Company leaders at a business in Egypt want to ensure all supplies are sourced within the country. So, they ask the data team to investigate the performance of local suppliers. Team members consider how to manage the data for this project and who will be responsible for it. What phase of the data life cycle does this scenario describe?

Plan

Question 6 A data professional at a beauty products enterprise is assigned a task related to customer buying habits. They think about what type of data they need to be successful, as well as optimal project outcomes. What phase of the data life cycle does this scenario describe

Plan

A car rental company is interested in improving the customer experience. A data professional fixes typos and inaccuracies from a dataset containing feedback and ratings. They also verify and share their data-cleaning procedures with stakeholders. What step of the data analysis process does this scenario describe?

Process

Data analysts at a home appliance retailer have a dataset containing information about product repairs. They look for and resolve any errors within the dataset. Then, they transform the data into a format that will enable them to get useful insights about repair trends. What step of the data analysis process does this scenario describe?

Process

Phase 6: Act

Put your insights to work in order to solve the original problem

From issue to action: The six data analysis phases There are six data analysis phases that will help you make seamless decisions: ask, prepare, process, analyze, share, and act. Keep in mind, these are different from the data life cycle, which describes the changes data goes through over its lifetime. Going through the steps will help you solve all kinds of business problems that you might face on the job. Ask

Step 1: Ask It's impossible to solve a problem if you don't know what it is. These are some things to consider: Define the problem you're trying to solve Make sure you fully understand the stakeholder's expectations Focus on the actual problem and avoid any distractions Collaborate with stakeholders and keep an open line of communication Take a step back and see the whole situation in context Questions to ask yourself in this step: What are my stakeholders saying their problems are? Now that I've identified the issues, how can I help the stakeholders resolve their questions?

destroy phase.

To destroy it, the company would use a secure data erasure software. If there were any paper files, they would be shredded too. This is important for protecting a company's private information, as well as private data about its customers Remove data from storage and delete any shared copies of the data.

visualization tools

Turn complex numbers into a story that people can understand Help stakeholders come up with conclusions that lead to informed decisions and effective business strategies Have multiple features - Tableau's simple drag-and-drop feature lets users create interactive graphs in dashboards and worksheets - Looker communicates directly with a database, allowing you to connect your data right to the visual tool you choose

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

cloud

a place to keep data online, rather than a computer hard drive

Question 8 Fill in the blank: During the _____ step of the data analysis process, data analysts use tools such as spreadsheets to draw useful conclusions.

analyze

Question 8 Fill in the blank: During the _____ step of the data analysis process, data team members use tools such as SQL to make predictions.

analyze

Analytical Skills

are qualities and characteristics associated with solving problems using facts. The qualities and characteristics associated with solving problems using facts

A data professional is always interested in learning new skills and gaining knowledge. They often seek out challenging assignments at work and professional development experiences. Which analytical skill does this scenario describe?

curiosity

key data analyst skills

curiosity understanding context having a technical mindset data design data strategy

Phases Ask

define the problem and confirm stakeholder expectations

quartile

divides data points into four equal parts

Question 2 Which spreadsheet feature uses a set of instructions to perform calculations, such as addition or subtraction?

fORMULA

A software company wants to improve its customer experience scores by 3% over the next 30 days. A data professional works to achieve this objective by understanding current scores and how far away they are from desired scores. They then use data insights to help advance the company from where they are now to where they want to be next month. What does this scenario describe?

gap analysis

What is a method for examining and evaluating how a process works currently in order to get to an improved future state

gap analysis

Strategic

having a strategic mindset is key to staying focused and on track. Strategizing helps data analysts see what they want to achieve with the data and how they can get there. Strategy also helps improve the quality and usefulness of the data we collect

Life cycle of data

plan, capture, manage, analyze, archive, destroy

Data science involves using _____ data to create new ways of modeling and understanding the unknown.

raw

Data analyst

someone who collects, transforms, and organizes data in order to help make informed decisions.

spreadsheet

spreadsheet is a digital worksheet. It stores, organizes, and sorts data. Data analysts rely on spreadsheets to collect and organize data. Two popular spreadsheet applications you will probably use a lot in your future role as a data analyst are Microsoft Excel and Google Sheets. Spreadsheets structure data in a meaningful way by letting you Collect, store, organize, and sort information Identify patterns and piece the data together in a way that works for each specific data project Create excellent data visualizations, like graphs and charts.

Fill in the blank: During the prepare step of the data analysis process, data is collected and _____ for analysis

stored

anaLyZE

the data is used to solve problems, make great decisions, and support business goals

Visualization

the graphical representation of information

Prepare step

the prepare step of the data analysis process. This is where data analysts collect and store data they'll use for the upcoming analysis process. You'll learn more about the different types of data and how to identify which kinds of data are most useful for solving a particular problem. You'll also discover why it's so important that your data and results are objective and unbiased. In other words, any decisions made from your analysis should always be based on facts and be fair and impartial.

Root cause

the reason why a problem occurs Ask, why 5 times to reveal the root cause

Data analytics

the science of data

Data ecosystems

the various elements that interact with one another in order to produce, manage, store, organize, analyze, and share data.

What is the purpose of the five whys?

to reveal the root cause of the problem

Defining a problem

you look at the current state and identify how it's different from the ideal state The first step here is to determine who the stakeholders are

being able to identify a correlation between two or more pieces of data.

A correlation is like a relationship. You can find all kinds of correlations in data. Correlation does not equal causation. In other words, just because two pieces of data are both trending in the same direction, that doesn't necessarily mean they are all related.

Gap analysis

A method for examining and evaluating how a process works currently in order to get where you want to be in the future

query language

A query language is a computer programming language that allows you to retrieve and manipulate data from a database Query languages Allow analysts to isolate specific information from a database(s) Make it easier for you to learn and understand the requests made to databases Allow analysts to select, create, add, or download data from a database for analysis

observation

An observation includes all of the attributes for something contained in a row of a data table

During the _____ step of the data analysis process, data analysts use tools such as spreadsheets to draw useful conclusions.

Analyze

analyze

Analyzing the data you've collected involves using tools to transform and organize that information so that you can draw useful conclusions, make predictions, and drive informed decision-making

archive phase

Archiving means storing data in a place where it's still available, but may not be used again Keep relevant data stored for long-term and future reference.

Data analysis process phases

Ask, Prepare, Process, Analyze, Share, Act

A data team at a public university wants to communicate to stakeholders about which foreign language courses are most popular with students. They create a data visualization that identifies the 38 different courses, then shows the number of students enrolled in each one. What type of data visualization should they create?

Bar chart

Ask phase

Communicating with your stakeholders is key in making sure you stay engaged and on track throughout the project. So as a data analyst, developing strong communication strategies is very important. This part of the ask phase helps you keep focused on the problem itself, not just its symptoms. As you learned earlier, the five whys are extremely helpful here. 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 Qualifying stakeholder expectations means determining who the stakeholders are, what they want, when they want it, why they want it, and how best to communicate with them. Defining the problem means looking at the current state and identifying the ways in which it's different from the ideal state. With expectations qualified and the problem defined, you can derive questions that will help achieve these goals.

Which of the following statements correctly describe the archive and the destroy phases of the data life cycle? Select all that apply.

Data-erasure software can be used to destroy data on a hard drive. Even if data might be needed again in the future, it still may be archive **Data that is no longer relevant to business goals is often archived. A key reason for destroying data is to protect private company information. The archive phase involves storing data. Shredders may be used to destroy data on paper.

Databases

Database accessed using a query language Structured data using rules and relationships Organizes information in complex collections Provides access to huge amounts of data Strict and consistent data entry Multiple users Controlled by a database management system are ideal for storing, managing, and analyzing large and complex datasets. Data analysts often use a combination of spreadsheets, databases, and programming languages to effectively handle a wide range of data analysis tasks. A collection of data stored in a computer system

plan phase

Decide what kind of data is needed, how it will be managed, and who will be responsible for it.

What tasks may occur during the ask step of the data analysis process? Select all that apply

Define the problem to be solved Stay engaged by having a dialogue with stakeholders Consider the current state compared to the ideal state

process step

Here, data analysts find and eliminate any errors and inaccuracies that can get in the way of results. This usually means cleaning data, transforming it into a more useful format, combining two or more datasets to make information more complete and removing outliers, which are any data points that could skew the information. After that, you'll learn how to check the data you prepare to make sure it's complete and correct. This phase is all about getting the details right. So you'll also fix typos, inconsistencies, or missing and inaccurate data. To top it off, you'll gain strategies for verifying and sharing your data cleansing with stakeholders 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) After data analysts process data, they check the data they prepared to make sure it's complete and correct. This phase is all about getting the details right. Accordingly, the data analyst will refine strategies for verifying and sharing their data cleaning with stakeholders.

A data team at a national bank plans a project about its customer bill-paying tool. They apply analytical thinking to decide what they want to achieve with the data. This helps ensure the data is valuable and will help them accomplish their goals. Which aspect of analytical thinking does this scenario describe?

Strategic thinking

Question 9 Which of the following statements accurately describe data visualizations and visualization tools? Select all that apply

Tableau is a data visualization tool that enables simple and quick data-sharing. When working with the programming language R, data professionals can create dashboard-style data visualizations. Data professionals can create bar graphs, pie charts, and maps in a spreadsheet.

5 aspects of analytical thinking

The 5 key aspects are visualization, strategy, problem-orientation, correlation, and using big-picture and detail-oriented thinking.

technical mindset

The ability to break things down into smaller steps or pieces and work with them in an orderly and logical way

understanding context

The analytical skill that has to do with how you group things into categories

Data design

The analytical skill that involves how you organize information

Data strategy

The analytical skill that involves managing the processes and tools used in data analysis is the management of the people, processes, and tools used in data analysis

Data Analysis

The collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making

context

The condition in which something exists or happens

Machine Learning

These are separated by how many decisions you know you want to make before you begin with them. --

Stakeholders

They are people who have invested time and resources into a project and are interested in the outcome.

big-picture thinking

This means being able to see the big picture as well as the details

While planning a roadtrip, you figure out all of the specific stops you need to take along the way. You also consider how often you'll stop for gas, meals, and sleep. Having this information enables you to execute your plan. What does this scenario describe?

This scenario describes detail-oriented thinking, which is about figuring out all of the specifics that will help you execute a plan.

Key takeaways

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.

Phase 4: Analyze

Use data analysis tools to draw conclusions

Data-driven decision making

Using facts to guide business strategy

Attribute

attribute is a characteristic or quality of data used to label a column in a table. More commonly, attributes are referred to as column names, column labels, headers, or the header row.

Fill in the blank: A university system gathers historical academic data from an outside database and information from the internal records of student applications. This work occurs during the _____ phase of the data life cycle.

capture

Question 10 Fill in the blank: An agriculture company collects data from an outside commodity market database and internal files containing information about livestock. This work occurs during the _____ phase of the data life cycle.

capture

Question 8 Which text wrapping feature cuts off the contents of a spreadsheet cell so only the text that fits is visible?

clip

Phase 2: Prepare

collect and store data for analysis

Data

collection of facts

share phase

how data analysts interpret results and share them with others to help stakeholders make effective data-driven decisions. In the share phase, visualization is a data analyst's best friend. So this course will highlight why visualization is essential to getting others to understand what your data is telling you. With the right visuals, facts and figures become so much easier to see and complex concepts become easier to understand. it's time to share what you've learned with your stakeholders

Data analysts use a problem-oriented approach in order to _____, describe, and solve problems.

identify

Analytical thinking involves _____ a problem, then solving it by using data in an organized, step-by-step manner.

identifying and defining

SQL

is a language that lets data analysts communicate with a database.

R

is a popular tool for data manipulation, calculation, and visualization

function

is a preset command that automatically performs a specific process or task using the data in a spreadsheet.

formula

is a set of instructions that performs a specific calculation using the data in a spreadsheet

Data science

is defined as creating new ways of modeling and understanding the unknown by using raw data.

Data Visualization

is the graphical representation of information. Some examples include graphs, maps, and tables