Data Analytics - Course 8

interview tip 4

-> Come ready with questions --> such as "What are some upcoming projects I'd be working on? What current goals is the company focused on? Can you tell me about the team I'll be working with?" This not only shows you care about understanding the company and the position you're applying for, but it's also a testament to the research you've done by looking into the company. Besides, this is your opportunity to interview them as well.

interview tip 1

-> Find connections between the job listing and your resume

about the tableau platform (sharing your work)

Finally, you might choose Tableau to host your work. You've already got some experience with Tableau from our work here. It's a great option if you're focused on the data viz side of things. Plus, you can create interactive dashboards using Tableau's tools that are easily shareable. Choosing where to host your portfolio is an important decision, but hopefully now you have some ideas about how each platform could be useful. And you might end up using multiple platforms over time to fit your specific needs. The important thing is to remember the two questions we talked about earlier. What platforms align with your interests and passions? And where do you want to spend more time after this program?

how can github be a great host for your portfolio?

GitHub is a hosted platform primarily used by developers as a repository for code, but it can also be used as a repository for documentation. One of the tips you have been given in this program is to keep an electronic journal of things to remember, especially for SQL or R syntax. If something in your electronic journal is particularly useful, you can create a document for your portfolio in GitHub

about the github platform (sharing your portfolio)

GitHub's primarily used for programming languages like R or Python. It has a more technical setup than other platforms. But it's a great place to share your code and the how behind your analysis with other users. And if you want to learn from other data analysts' work, GitHub's a great place to be.

Stage 3: The compatibility interview (optional)

In some cases, not all, there will be an additional interview to determine mutual compatibility between you and the company. To give you a comprehensive idea of what the work culture is like, the interviewer might include other members of the team during this round.

Salary negotiation advice

Once the interviews are over, if the company offers you the position, you and the company both need to agree on your starting salary. Although it is often an uncomfortable part of the process for many job applicants, negotiating a salary that you feel is fair is very important. This video highlights how Sally has done her research and didn't feel pressured to accept the company's first offer on the spot. When it comes to job interviews, there is no such thing as being too prepared. Be sure to do your research on the company, the role you are applying to, and salary expectations for the position. Practice marketing yourself and your skills and use active listening whenever you are asking and answering questions.

keep your portfolio:

Personal: Show who you are, what you are interested in, and what is important to you. Simple: Display your work with easy navigation and without cluttered pages. Relevant: Match your work to the skills included in job descriptions. Presentable: Emphasize quality in the samples you show. Unique: Showcase your own work; cite sources of content to avoid plagiarism.

what is an elevator pitch used for?

When you're discussing the case studies in your portfolio, you'll want to develop an elevator pitch to give interviewers a quick, high-level understanding of your work. Basically, an elevator pitch is just a short statement describing an idea or a concept. It should be just a couple of sentences, short enough that you could explain it to someone in an elevator. It's always a good idea to prep your elevator pitch beforehand. Then once the interviewers have that high-level understanding of your case study, you can give concrete examples of your process and how you solved problems in your data analysis before.

What are the key purposes of discussing a case study during an interview? Select all that apply.

You may discuss a case study during an interview to outline your thinking about a data analytics scenario or recommend real-world solutions based on your own work.

how to create an effective resume

https://applieddigitalskills.withgoogle.com/c/college-and-continuing-education/en/start-a-resume/overview.html

where to browse the coursera job platform

https://googlecerts.courserajobplatform.org/

how to create a profile on the coursera job platform

https://googlecerts.courserajobplatform.org/profiles/sign_up -> where you can find and apply to relevant data analytics jobs, including those available through our participating employers like Walmart, Accenture, Snap Inc., Deloitte, and more.

what is a resource to prepare for interviews?

https://grow.google/certificates/interview-warmup/ -> interview warmup is a tool that helps you practice answering questions to get more confident and comfortable with interviewing.

how to publish on medium

https://help.medium.com/hc/en-us/articles/115004681607-Getting-started-with-a-Medium-publication

publishing your portfolio in github

https://medium.com/@brianmwevi/8-steps-to-publish-your-portfolio-on-github-9d6e6e3d2e84

instructions on how to publish your site and share it publicly (google sites)

https://support.google.com/sites/answer/6372880

some personal experience questions

"Was there a time when you took initiative during a project and what was the outcome?" This question can come in many forms with slightly different wording, but the goal is to understand your leadership abilities and how you have used them in the past. "What was the most challenging project you have ever been faced with?" This question is usually meant to assess your problem-solving and interpersonal skills. Come to the interview prepared with several different examples of how you successfully navigated a difficult project or situation in the past. "How would you explain a complex topic to a stakeholder who was unfamiliar with it?" This question helps your interviewer get a sense of how skilled you are at communicating effectively in high-pressure or sensitive circumstances. "How do you cope when things don't go according to plan?" It is important to be adaptable, especially when things don't go the way you expected. This question provides a great opportunity for you to explain how you coped with unexpected changes and adapted quickly to a different course of action.

some technical interview questions

"What are your preferred tools for analysis?" This is a chance to demonstrate that you are well-versed in data analysis, with proficiency in SQL, Excel, and R programming. "How do you maintain integrity in your data?" Reliability and accuracy are essential parts of good data analysis, and any issues with your data can have a major impact on data-driven business decisions. Be prepared to discuss the methods you use for error checking and validation. "Do you understand different SQL functions and the roles they play?" SQL is arguably one of the most important skills for you to have as a data analyst. This is an opportunity to demonstrate your understanding of different types of SQL functions and their value or result. Personal experience questions

interview tip 2

-> Focus on data --> This helps your interviewer understand not just your overall achievements, but how big of an impact you made. What data can you provide that tells the story of your experience in terms of the needs of this position? The "equation" we suggest including goes something like this: I accomplished X as measured by Y doing Z. Here's an example: "I increased customer satisfaction by 22% in three months by designing a new digital onboarding process."

interview tip 3

-> Look back at past work experiences --> Think of examples of times you achieved something so you are prepared to answer questions like "Tell me about a time when . . ." or "How would you approach this situation . . .?"

is there a time limit for a case study?

-> Usually, there's a time limit for the case study you've been asked to do. For example, a potential employer might give you some sample data and project questions and ask you to create a presentation or memo with your recommendations in 24 to 48 hours. -> That time limit can be a little challenging. But the good news is, your answer to the case study doesn't have to be perfect. What's important is that you show off your thought process so that the interviewers can understand how you approach the problem.

what is a case study?

-> a common way for employers to assess job skills and gain insight into how you approach common data-related challenges. -> Different employers might send you different kinds of case studies. For example, you might be asked to clean and analyze a data set, offer a proposal around how to measure the success of a project, or figure out and define metrics of success for a specific product.

Follow these steps to start a 5-question practice interview related to data analytics:

1. Go to grow.google/interview-warmup. 2. Click Start practicing. 3. Select the "Data Analytics" practice set. 4. Click Start. -> It takes about 10 minutes, and the questions will be different every time. Each question set will have two background questions, one behavioral question, and two technical questions, simulating what you would encounter in a real interview. You can try as many practice interviews as you want. You'll also have the option to access the full list of interview questions if you'd like to review more of the questions available or focus on specific topics.

what is a portfolio

A portfolio is a collection of case studies that can be shared with potential employers. Portfolios can be stored on public websites like GitHub, Kaggle, or Tableau, or on your blog. Your portfolio can also be linked in your resume. This will give you examples of how you approached data tasks in the past that you can talk about in your interview.

about other platforms (blogs for sharing your portfolio)

Blog platforms like Medium, WordPress and Google Sites are personalized and ownable. Blogs aren't as code-focused as Kaggle and GitHub, so you'll have to store your code somewhere else. And there might be a few extra steps you'll have to take to display code on blogs. But you can show off your expertise, write about your process in your own voice, and show thought leadership in your field

how can personal websites be a great host for your portfolio?

Creating a personal website to host your portfolio is a great option because you can also use it to showcase aspects of your personality or background that contribute to your professional brand. For example, you might share a compelling experience that reflects your ability to collaborate, be resilient, or not give up.

If an interviewer says, "Tell me about yourself," it's important to limit your response to topics related to data analytics.

If you are asked to tell an interviewer about yourself, your goal is to positively and accurately represent yourself using past and present experiences and skills. Experiences and skills gained from previous work of any kind can be useful to share.

what if you don't have the data?

If you don't have access to this kind of data from a previous position, you can still indicate the scope you were accountable for and strengthen the language you use when describing your responsibilities by including action words like provided, created, developed, supported, implemented, and generated. For example: "I implemented a new scheduling system that led to 95% of the team meeting deadlines."

Suppose you want to add a description of your code to your Kaggle notebook. What button would you click to create the proper cell?

In R, you can use Markdown to format non-code text. The + Markdown button adds a Markdown cell, which you can use to type and format non-code descriptions in your Notebooks. Going forward, you can use code cells to represent the content of your portfolio.

about the kaggle platform (sharing your portfolio)

Kaggle has a broad data science community you could join. It hosts a lot of competitions for users to join in and offers all kinds of learning opportunities. This is a great option if you enjoy connecting with other data analysts.

An elevator pitch gives potential employers a quick, high-level understanding of your professional experience. What are the key considerations when creating an elevator pitch? Select all that apply.

Key considerations of an elevator pitch include keeping it short, considering your audience's interests, and focusing on your process.

what is an essential part of the interview process?

Negotiating a job offer is an essential part of the interview process, even for entry-level roles.

what is important when answering a case studies questions?

On top of answering the question, you also want to make sure that you're communicating the steps you've taken and the assumptions you made about the data. One of the reasons potential employers are interested in case studies is because they show your thought process and problem-solving skills. Showing the steps you took to reach your conclusion can help them get a good idea of how you work

Stage 4: Decision-making

Once your last interview concludes, it is advisable to ask about next steps as well as a timeline of when a hiring decision will be made. Take note that the process can take anywhere from 4 to 6 weeks as things get finalized and all other interviews are wrapped up. You can receive one of three responses: an offer letter, a rejection letter, or no communication. Receiving a job offer is very exciting and something you can take pride in. However, don't feel pressured or obligated to accept the first offer you are presented. Feel free to ask for time to consider, do your research on a fair salary or benefits package, and be open-minded and willing to compromise.

types of notebooks in kaggle

Scripts: Typically code-only documents. Cells can be formatted in R or Python only. They execute each cell as code sequentially. RMarkdown scripts: Cells can be formatted in R and RMarkdown only. These files are preferred by many R authors. Jupyter Notebooks: Cells can be formatted in Markdown, R, or Python. These are most suited to flexibility.

what are the four stages of the interview process?

Stage 1: Introduction (resume and portfolio) Stage 2: The skill test interview (case study) Stage 3: The compatibility interview (optional) Stage 4: Decision-making

Stage 1: Introduction (resume and portfolio)

The goal of the introductory interview is for the recruiter to get to know you. Their goal is to find out who you are and assess your background. This is your chance to shine. Have your portfolio and resume ready and be prepared to speak concisely about your qualifications, experience, and skills using specific examples from both. This is the part of the interview when the interviewer usually answers questions about the company and the position. It's also an opportunity for the applicant to outline how the skills they used in past roles can translate into the position they are applying for.

Stage 2: The skill test interview (case study)

This is usually your second interview and it will often be conducted by a fellow data analyst or data engineer. In this interview, you will be given a technical assessment that will consist of testing your SQL and programming skills. You will also be asked to complete a case study or a behavioral test. Your potential employer wants to know if you can do the job that you are interviewing for and they will be focused on getting you to demonstrate your skills. Make sure you are prepared with well-formed answers and highlight your technical knowledge and problem-solving skills. Most interviewers will ask applicants questions related to their problem-solving abilities. In this video, Sally provides specific examples of past challenges and how she used her problem-solving skills to overcome them.

Imagine that an interviewer asks, "How do you maintain data integrity?" What topics does this question give you the opportunity to discuss? Select all that apply.

This question gives you the opportunity to discuss the methods you use for error checking and validation as part of your data cycle process. In addition, you can point out that reliability and accuracy are essential parts of good data analysis and any issues with your data can have a major impact on data-driven business decisions.

During an interview, you will likely respond to technical questions, practical knowledge questions, and questions about your personal experiences. What strategies can help you prepare to respond effectively? Select all that apply.

To prepare for an interview, write down answers to common questions, brainstorm examples from your own experiences, and practice your responses until they feel natural and unrehearsed.

how do career counselors recommend you create your resume

When you create your resume, the way you present your skills can capture the attention of a recruiter or a hiring manager. Many career counselors recommend that you customize your resume each time you apply for a job so that your experience and skills align as closely as possible with the requirements listed in the job description.

publishing your first dataset on kaggle

https://medium.com/analytics-vidhya/publishing-your-first-dataset-on-kaggle-6be8c37e59e8

instructions if you want to use a custom URL for your portfolio

https://support.google.com/sites/answer/9068867

how to publish on wordpress

https://wordpress.com/learn/get-published/

resources to explore other case studies

medium.com/search github.com/search public.tableau.com kaggle.com

what makes a great portfolio?

they are personal, unique, and simple

Q&A: interviewer asks you to talk about how you approach data cleaning

you might highlight your case study to outline how you've cleaned data before. After giving them a quick explanation of the case study, you can describe your process and show them how you successfully completed the analysis.