WEEK 1 - Effective questions
[Definition]
-Structured thinking: The process of recognizing the current problem or situation, organizing available information, revealing gaps and opportunities, and identifying the options
[Six problem types]
-Making predictions: Using data to make an informed decision about how things may be in the future
-Categorizing things: Assigning information to different groups or clusters based on common features
-Spotting something unusual: Identifying data that is different from the norm
-Identifying themes: Grouping categorized information into broader concepts
-Discovering connections: Finding similar challenges faced by different entities and combining data and insights to address them
-Finding patterns: Using historical data to understand what happened in the past and is therefore likely to happen again
[SMART questions]
Specific: Specific questions are simple, significant, and focused on a single topic or a few closely related ideas
ex) "Are kids getting enough exercise these days?" → "What percentage of kids achieve the recommended 60 minutes of physical activity at least five days a week?"
Measurable: Measurable questions can be quantified and assessed
ex) "Why did our recent video go viral?" → "How many times was our video shared on social channels the first week it was posted?"
Action-oriented: Action-oriented questions encourage change
ex) "How can we get customers to recycle our product packaging?" → "What design features will make our packaging easier to recycle?"
Relevant: Relevant questions matter, are important, and have significance to the problem you're trying to solve
ex) "Why does it matter that Pine Barrens tree frogs started disappearing?" → "What environmental factors changed in Durham, North Carolina, between 1983 and 2004 that could cause Pine Barrens tree frogs to disappear from the Sandhills Regions?"
Time-bound: Time-bound questions specify the time to be studied
If a question is worth asking, the the answer is worth recording.
[Helpful aspects of your conversation to note]
-Facts: Write down any concrete piece of information, such as dates, times, names, and other specifics
-Context: Facts without context are useless. Note any relevant details that are needed in order to understand the information you gather
-Unknowns: Sometimes you may miss an important question during a conversation. Make a note when this happen so you can figure out the answer later.
[Things to avoid when asking questions]
-Leading questions: questions that only have a particular response
ex) "This product is too expensive, isn't it?"
→ "What is your opinion of this product?"
"What price (or price range) would make you consider purchasing this product?"
(focused on pricing)
-Closed-ended questions: questions that ask for a one-word or brief response only
ex) "Were you satisfied with the customer trial?"
→ "What did you learn about customer experience from the trial?"
-Vague questions: questions that aren't specific or don't provide context
ex) "Does the tool work for you?"
→ "When it comes to data entry, is the new tool faster, slower, or about the same as the old tool?
If faster, how much time is saved? If slower, how much time is lost?"
WEEK 2 - Data-driven decisions
[Definition]
-Data-inspired decision-making: Explore different data sources to find out what they have in common
-Algorithm: A process or set of rules to be followed for a specific task
-Quantitative data: Specific and objective measures of numerical facts
-Qualitative data: Subjective or explanatory measures of qualities and characteristics
-Pivot table: A data summarization tool that is used in data processing. Pivot tables are used to summarize, sort,reorganize, group, count, total or average data stored in a database
-Metric: Single, qunatifiable type of data that can be used for measurement. Metrics can be used to help calculate customer retention rates, or a company's ability to keep its customers over time
-Metric goal: A measurable goal set by a company and evaluated using metrics
-ROI: Return on Investment = the net profit over a period of time / the cost of investment
[Reports vs. Dashboard]
Reports: Static collection of data given to stakeholders periodically
| Pros | Cons |
| -High-level historical data -Easy to design -Pre-cleaned and sorted data |
-Continumal maintenance -Less visually appealing -Static |
Dashboards: Monitors live, incoming data
| Pros | Cons |
| -Dynamic, automatic, and interactive -More stakeholder access -Low maintenance |
-Labor-intensive design -Can be confusing -Potentially uncleaned data |
[Benefits of using a dashboard]
| Benefits | For Data Analysts | For Stakeholders |
| Centralization | Sharing a single source of data with all stakeholders | Working with a comprehensive view of data, initiatives, objectives, projects, processes, and more |
| Visualization | Showing and updating live, incoming data in real time | Spotting changing trends and patterns more quickly |
| Insightfulness | Pulling relevant information from different datasets | Understanding the story behind the numbers to keep track of goals and make data-driven decisions |
| Customization | Creating custom views dedicated to a specific person, project, or presentation of the data | Drilling down to more specific areas of specialized interest or concern |
[Process of creating a dashboard]
1. Identify the stakeholders who need to see the data and how they will use it
2. Design the dashboard
- Use a clear header to label the information
- Add short text descriptions to each visualization
- Show the most important information at the top
3. Create mock-ups if desired
4. Select the visualizations you will use on the dashboard
5. Create filters as needed
https://www.tableau.com/data-insights/dashboard-showcase
Tableau Dashboard Showcase
Tableau Dashboard Showcase Tableau empowers people to find insights in their data, create beautiful and intuitive dashboards, and share them with their organizations and broader community. These are some of our favorite Tableau data visualizations.
www.tableau.com
https://public.tableau.com/app/discover/viz-of-the-day
Viz of the Day
Find a new featured visualization each day on Tableau Public.
public.tableau.com
https://help.tableau.com/current/pro/desktop/en-us/actions_filter.htm
Filter Actions
Filter actions send information between worksheets
help.tableau.com
[Benefits of big data]
-Companies identify more efficient ways of dooing business and save a lot of time and money
-Organizations spot the trends of customer buying patterns and satisfaction levels, which can help them create new products and solutions that will make customers happy
-Businesses get a much better understanding of current market conditions, which can help them stay ahead of the competition
-Companies keep track of their online presence-especially feedback, both good and bad, from customers. This gives them the information they need to improve and protect their brand
[V words for big data]
| Volume | Variety | Velocity | Veracity |
| The amount of data | The different kinds of data | How fast the data can be processed | The quality and reliability of the data |
[Crate and Barrel's data strategy]
How 1 retailer’s data strategy powers seamless customer experiences
Google's Official Digital Marketing Publication. Crate and Barrel improved customer experience and redefined digital retail strategy with data analytics.
www.thinkwithgoogle.com
[How PepsiCo is delivering a more personal and valuable experience to customers using data]
PepsiCo’s customer-first marketing - Think with Google
To stand out, PepsiCo has to deliver a personal and valuable customer experience. That means a digital transformation to customer-first marketing.
www.thinkwithgoogle.com
+) Advice
As a data analyst, your own skills and knowledge will be the most important part of any analysis project. It is important for you to keep data-driven mindset, ask lots of questions, experiment with many different possibilities, and use both logic and creativity along the way. You will then prepared to interpret your data with the highest levels of care and accuracy.
WEEK 3 - More spreadsheet basics
[Definition]
-Operator: A symbol that names the type of operation or calculation to be performed
-Cell reference: A cell or a range of cells in a worksheet that can be used in a formula
-Range: A collection of two or more cells
-Problem domain: The specific area of analysis that encompasses every activity affecting or affected by the problem
-Scope of work (SOW): An agreed-upon outline of the work you're going to perform on a project
ex) Deliverables, Timeline, Milestones, Reports
[Open data sources online]
- World Bank
- World Health Organization
- Google Public Data Explorer
- U.S. Census Bureau
[Spreadsheet Errors]
| Error | Description | Example |
| #DIV/0! | A formula is trying to divide a value in a cell by 0 (or an empty cell with no value) | =B2/B3, when the cell B3 contains the v alue 0 |
| #ERROR! | (Google Sheets only) Something can't be interpreted as it has been input. This is also known as a parsing error. | =COUNT(B1:D1 C1:C10) is invalid because the cell ranges aren't separated by a comma |
| #N/A | A formula can't find the data | The cell being referenced can't be found |
| #NAME? | The name of formula or function used isn't recognized | The name of a function is misspelled |
| #NUM! | The spreadsheet can't perform a formula calculation because a cell has an invalid numeric value | =DATEDIF(A4, B4, "M") is unable to calculate the number of months between two dates because the date in cell A4 falls after the date in cell B4 |
| #REF! | A formula is referencing a cell that isn't valid | A cell used in a formula was in a column that was deleted |
| #VALUE! | A general error indicating a problem with a formula or with referenced cells | There could be problems with spaces or text, or with referenced cells in a formula; you may have additional work to find the source of the problem |
https://haerin-study.tistory.com/12
Errors and fixes
It never feels good when you type in what you are sure is a perfect formula or function, only to get an error message. Understanding errors and how to fix them is a big part of keeping your data clean, so it's important to know how to deal with issues as t
haerin-study.tistory.com
WEEK 4 - Always remember the stakeholder
[Definition]
-Stakeholders: People that have invested time, interest, and resources into the projects you'll be working on as a data analyst
-Turnover rate: The rate at which employees leave a company
Before you communicate, think about
1. Who your audience is
2. What they already know
3. What they need to know
4. How you can communicate that effectively to them
[Scope of work: SOW]
A well-defined SOW keeps you, your tean, and everyone involved with a project on the same page. It ensures that all contributors, sponsors, and stakeholders share the same understanding of the relevant details.
※ Avoid vague statements. Be specific.
ex) "Fixing traffic problems" → "Identify top 10 issues with traffic patterns within the city limits, and identify the top 3 solutions that are most cost-effective for reducing traffic congestion."
- Deliverables: What work is being done, and what things are being created as a result of this project? When the project is complete, what are you expected to deliver to the stakeholders? Will you collect data for this project? How much, or for how long?
- Milestones: This is closely related to your timeline. What are the major milestones for progress in your project? How do you know when a given part of the project is considered complete?
- Timeline: It will be closely tied to the milestones created for your project. The timeline is a way of mapping expectations for how long each step of the process should take. The timeline should be specific enough to help all involved decide if a project is on schedule. When will the deliverables be completed? How long do you expect the project will take to complete? If all goes as planned, how long do you expect each component of the project will take? When can we expect to reach each milestone?
- Reports: Good SOW also set boundaries for how and when you'll give status updates to stakeholders. How will you communicate progress with stakeholders and sponsors, and how often? Will progress be reported weekly? Monthly? When milestones are completed? What information will status reports contain?
[5 Data Analytics Projects for Beginners]
https://www.coursera.org/articles/data-analytics-projects-for-beginners
5 Data Analytics Projects for Beginners
Build a job-ready portfolio with these five beginner-friendly data analysis projects.
www.coursera.org
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