#tableau tutorial

[analyticspursuit]

Data Visualization: Key to Making Data Relatable

The last time you looked at a table of data and thought "I'm just not sure how to make sense of this," you weren't alone. It's not that the information was unimportant, or even that the topic was particularly complicated—it's just that you weren't sure how to present it in a way that would help you understand what it meant and how it could be used.

That's where data visualization comes in. Data visualizations are charts and graphs that take data from a variety of sources and turn them into something you can see, understand, and act on. They can be simple bar charts or complex scatterplots, but they all have one thing in common: they make information more accessible than ever before.

In this short video, we're going to explore why data visualizations are so important for businesses today, how they work, and where you can find them online!

[pythonjobsupport]

Tableau LOD (Level of Detail) Expressions Explained - FIXED, INCLUDE, EXCLUDE - Complete Tutorial

LET’S CONNECT #tableau #analytics #lod #calculation Practice Questions and other digital products … source

[courseswebs]

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[zora28]

Data Visualization Using Tableau,Using Tableau To Visualize Data,Visualization Using Tableau,Tableau For Beginners Data Visualisation,How To Visualize Data Using Tableau,Data Visualization Using Tableau Tutorial,Tableau Visualisation,Data Visualisation With Tableau

[datasciencedoug]

How to Union Data in Tableau: A Quick and Easy Guide

[multimystica]

Welcome!

I'm a Brazilian Tarot reader and Oraculist just trying to make a living to pay for college and help with house expenses, I work with the following divination methods:

Tarot (Rider Waite; Osho's Zen Tarot; Tarot of the Holy Grail)

Lenormand a.k.a. Petit Lenormand ( French Cartomancy, or Gypsy Deck if you're Brazilian)

Vera Sibilla Italiana (a.k.a. Italian Cartomancy)

Elder Futhark (a.k.a. Runes)

Very sporadically I use the pendulum and radiestesy & radionic graphics as well.

My main objective with this profile is to work professionally with divination and spirituality online. If you want to know more about myself before you book a reading or service feel free to ask, I'm an open book.

As this is a professional page and not only a hobby, I plan to charge for my readings, I take payments via Paypal or PicPay (if you're in Brazil, I take payments via pix as well).

However, I also intend to serve spirituality itself, so once a week I'll answer simple questions with 6 card Lenormand readings free of charge via Tumblr's ask function.

My rates in US Dollars:

$5 - 1 card reading using Osho's Zen Tarot Deck

$5 - 3 runes reading using Elder Futhark Runes

$10 - 6 card reading using the Lenormand Deck

$10 - 3 card reading using Rider Waite's Tarot Deck

$25 - Pack of three 6 card readings using Lenormand Deck

$25 - Pack of three 3 card readings using Rider Waite's Tarot Deck

$50 - Lenormand Grand Tableau reading + 3 clarifying questions.

$60 - 1 hour of unlimited questions using your oracles of choice (from those currently avaliable) + 1 Osho's Zen Tarot card advice.

Readings can be made online (texts or videocalls if the app of choice supports it, you choose) via Tumblr Chat, Discord, WhatsApp, or delivered on a PDF via e-mail. I'll always send pictures of the cards drawn and explain everything.

Other services I offer:

$30 - Spiritual Guidance and Advice Sessions ( 1 hour sessions via Discord or Whatsapp Messenger)

$60 - Tutorial on Energetically Cleansing Spellwork (delivered via Discord, E-mail or PDF)

$120 - 30 days of Spiritual Guidance and Advice + three 6 card readings with Lenormand (via Discord or Whatsapp Messenger)

On Spellwork:

I can perform certain types of spellwork, such as:

Abundance, prosperity & wealth rituals

Self-love, self-esteem & self-respect rituals

Peace and positivity rituals

Those don't have a fixed pricing, the price is to be discussed depending on the severity of the situation, on the pricing of the required materials to perform the ritual, and on the financial situation of the client.

I may as well prescribe baths and rituals which you'd have to do yourself. If you come to me just for the prescription of baths or rituals I just charge the symbolic value of $5 for said prescriptions; however, if you booked a reading or another service with me and I find it to be useful or necessary in your situation, I'll do it free of charge.

Onto the much necessary disclaimer:

I DON'T do binding or karmic return rituals. Do not even ask about it. It goes against my values as a light-worker. Divine justice is there for a reason. I'm not here to rip off anyone so if you really need a certain service and can't afford it just message me about it and I'll see what I can do to help for FREE.

Most importantly: I am not a scammer, I'd rather be scammed than be seen as a scammer so you don't even need to pay upfront, I don't care to work for free if it means I'll get to help people with my cards.

Payment info:

Paypal info: colorfulpurplerose@gmail.com

PicPay Info: @multimystica Pix (for Brazilians): visualkei138@gmail.com

I just want to make an honest living, if you don't want a reading at all yet want to make a difference, feel free to donate any value to either of the payment methods stated above. Thank you!

[deletedg1rl]

24 November 2023

ok so here's list of tasks that'll take only a few minutes:

talk about interview with that guy.

emails.

talk about relocation plans and offer letter with HR.

choose a book to start.

text that person on reddit.

message that guy.

here's a list of things that takes time:

project report of tableau.

complete the chatbot tutorial.

start a book.

start my file on at least one person.

write journal.

i am going to schedule all of this like this.

8 am to 9 am -> chatbot/bath.

9 am to 10:30 -> chatbot.

10:30 am to 11 am -> emails, talk about relocation and offer letter with HR, talk about interview with that one guy, message that guy.

11 am to 12 pm -> choose a book, look through all my resources, text that person on reddit.

1:30 pm to 2:30 -> chatbot.

2:30 pm to 4 pm -> tableau report.

5 pm to 6 pm -> read whatever book i've chosen.

7 pm to 8 pm -> write in my journal, start a file on one person.

10 pm to 11 pm -> plan tommorow.

[vivekavicky12]

Cracking the Code: A Beginner's Roadmap to Mastering Data Science

Embarking on the journey into data science as a complete novice is an exciting venture. While the world of data science may seem daunting at first, breaking down the learning process into manageable steps can make the endeavor both enjoyable and rewarding. Choosing the best Data Science Institute can further accelerate your journey into this thriving industry.

In this comprehensive guide, we'll outline a roadmap for beginners to get started with data science, from understanding the basics to building a portfolio of projects.

1. Understanding the Basics: Laying the Foundation

The journey begins with a solid understanding of the fundamentals of data science. Start by familiarizing yourself with key concepts such as data types, variables, and basic statistics. Platforms like Khan Academy, Coursera, and edX offer introductory courses in statistics and data science, providing a solid foundation for your learning journey.

2. Learn Programming Languages: The Language of Data Science

Programming is a crucial skill in data science, and Python is one of the most widely used languages in the field. Platforms like Codecademy, DataCamp, and freeCodeCamp offer interactive lessons and projects to help beginners get hands-on experience with Python. Additionally, learning R, another popular language in data science, can broaden your skill set.

3. Explore Data Visualization: Bringing Data to Life

Data visualization is a powerful tool for understanding and communicating data. Explore tools like Tableau for creating interactive visualizations or dive into Python libraries like Matplotlib and Seaborn. Understanding how to present data visually enhances your ability to derive insights and convey information effectively.

4. Master Data Manipulation: Unlocking Data's Potential

Data manipulation is a fundamental aspect of data science. Learn how to manipulate and analyze data using libraries like Pandas in Python. The official Pandas website provides tutorials and documentation to guide you through the basics of data manipulation, a skill that is essential for any data scientist.

5. Delve into Machine Learning Basics: The Heart of Data Science

Machine learning is a core component of data science. Start exploring the fundamentals of machine learning on platforms like Kaggle, which offers beginner-friendly datasets and competitions. Participating in Kaggle competitions allows you to apply your knowledge, learn from others, and gain practical experience in machine learning.

6. Take Online Courses: Structured Learning Paths

Enroll in online courses that provide structured learning paths in data science. Platforms like Coursera (e.g., "Data Science and Machine Learning Bootcamp with R" or "Applied Data Science with Python") and edX (e.g., "Harvard's Data Science Professional Certificate") offer comprehensive courses taught by experts in the field.

7. Read Books and Blogs: Supplementing Your Knowledge

Books and blogs can provide additional insights and practical tips. "Python for Data Analysis" by Wes McKinney is a highly recommended book, and blogs like Towards Data Science on Medium offer a wealth of articles covering various data science topics. These resources can deepen your understanding and offer different perspectives on the subject.

8. Join Online Communities: Learning Through Connection

Engage with the data science community by joining online platforms like Stack Overflow, Reddit (e.g., r/datascience), and LinkedIn. Participate in discussions, ask questions, and learn from the experiences of others. Being part of a community provides valuable support and insights.

9. Work on Real Projects: Applying Your Skills

Apply your skills by working on real-world projects. Identify a problem or area of interest, find a dataset, and start working on analysis and predictions. Whether it's predicting housing prices, analyzing social media sentiment, or exploring healthcare data, hands-on projects are crucial for developing practical skills.

10. Attend Webinars and Conferences: Staying Updated

Stay updated on the latest trends and advancements in data science by attending webinars and conferences. Platforms like Data Science Central and conferences like the Data Science Conference provide opportunities to learn from experts, discover new technologies, and connect with the wider data science community.

11. Build a Portfolio: Showcasing Your Journey

Create a portfolio showcasing your projects and skills. This can be a GitHub repository or a personal website where you document and present your work. A portfolio is a powerful tool for demonstrating your capabilities to potential employers and collaborators.

12. Practice Regularly: The Path to Mastery

Consistent practice is key to mastering data science. Dedicate regular time to coding, explore new datasets, and challenge yourself with increasingly complex projects. As you progress, you'll find that your skills evolve, and you become more confident in tackling advanced data science challenges.

Embarking on the path of data science as a beginner may seem like a formidable task, but with the right resources and a structured approach, it becomes an exciting and achievable endeavor. From understanding the basics to building a portfolio of real-world projects, each step contributes to your growth as a data scientist. Embrace the learning process, stay curious, and celebrate the milestones along the way. The world of data science is vast and dynamic, and your journey is just beginning.  Choosing the best Data Science courses in Chennai is a crucial step in acquiring the necessary expertise for a successful career in the evolving landscape of data science.

[paulgadzikowski]

[Image description: Preview panel for the comic strip at the link. Tom Thumb, Princess Huncamunca, Lord Grizzle, Glumdalca the giantess, King Arthur, Queen Dollalolla, and Merlin of The Opera Of Operas stand in the tableau of the final scene. The Doctor, fugitive incarnation, of Doctor Who stands next to Merlin. Merlin is saying, “Ah yes, there’s nothing like bringing a roomful of spontaneous murder-suicides back to life for convincing them all to look on the bright side.” Unfortunately there are not image descriptions at the main Hero of Three Faces site. End description.]

The Hero of Three Faces is fanfiction crossovers, but it’s comic strips with stick figures, but they’re triangles. Preview panel only. Click here for full cartoon. Or see the on-site navigation tutorial. Or see this blog’s FAQ, or my archive tumblog’s FAQ. Cartoons may contain unmarked spoilers. Cartoons linked from Tumblr 10:00 (Central US time) daily are the previous day’s new update and the posts are pinned to the top of this blog. Cartoons linked from Tumblr 22:00 daily are from the archive and the posts are pinned only during annual summer hiatus of new updates.

[analyticspursuit]

6 Best Data Visualization Software for Exploring Data | Data Visualization Tools

In this video, we'll be taking a look at 6 of the best data visualization software for exploring data. These tools allow you to explore your data in a way that is both intuitive and visually stunning. If you're looking for ways to improve your business intelligence skills, then you need to check out these data visualization tools.

By using these tools, you'll be able to make sense of your data and make important decisions based on it. So put on your data visualization hat and let's take a look at some of the best options out there!

[pythonjobsupport]

How to use Joins in Tableau | Tableau Tutorials for Beginners

This is our fourth of 5 tutorials on Tableau. In this series we will learn the UI of tableau as well as how to effectively create … source

[estbenas]

DATA VISUALIZATION USING TABLEAU | USING TABLEAU TO VISUALIZE DATA | VISUALIZATION USING TABLEAU | TABLEAU FOR BEGINNERS DATA VISUALISATION | HOW TO VISUALIZE DATA USING TABLEAU | DATA VISUALIZATION USING TABLEAU TUTORIAL | TABLEAU VISUALISATION | DATA VISUALISATION WITH TABLEAU

Data Visualization Using Tableau,Using Tableau To Visualize Data,Visualization Using Tableau,Tableau For Beginners Data Visualisation,How To Visualize Data Using Tableau,Data Visualization Using Tableau Tutorial,Tableau Visualisation,Data Visualisation With Tableau

Visit : https://cognitec.in/course/data-visualization-using-tableau-40-hrs

[tech-insides]

The Ultimate Data Science Interview Preparation Guide: Tips and Resources

Preparing for a data science interview can be a daunting task, given the breadth and depth of knowledge required. However, with the right approach and resources, you can navigate this process successfully and land your dream job. Here’s an ultimate guide to help you prepare effectively for your data science interview.

Understanding the Data Science Interview Process

Data science interviews typically consist of several stages, each designed to assess different aspects of your skills and knowledge. These stages often include:

Resume Screening: Highlighting relevant skills, experiences, and projects.

Technical Screening: Initial technical questions or online assessments.

Coding Interview: Solving coding problems and demonstrating algorithmic thinking.

Technical Interview: In-depth questions on data science concepts, tools, and techniques.

Behavioral Interview: Assessing soft skills, cultural fit, and problem-solving approach.

Case Study/Project Presentation: Presenting a past project or solving a case study.

Tips for Effective Data Science Interview Preparation

1. Strengthen Your Foundations

Mathematics and Statistics: Understand key concepts in probability, statistics, linear algebra, and calculus.

Programming Skills: Be proficient in programming languages like Python or R. Practice coding problems on platforms like LeetCode, HackerRank, and CodeSignal.

Data Manipulation and Analysis: Gain expertise in using libraries such as pandas, NumPy, and SQL for data manipulation.

2. Master Key Data Science Concepts

Machine Learning: Understand algorithms, model evaluation, and tuning techniques. Practice implementing algorithms from scratch.

Data Visualization: Learn tools like Matplotlib, Seaborn, and Tableau to effectively communicate data insights.

Big Data Technologies: Familiarize yourself with tools like Hadoop, Spark, and cloud platforms (AWS, Google Cloud, Azure).

3. Work on Real Projects

Kaggle Competitions: Participate in Kaggle competitions to solve real-world problems and gain hands-on experience.

Personal Projects: Develop and showcase personal projects that highlight your skills and creativity. Use GitHub to share your code and document your work.

4. Prepare for Behavioral Interviews

STAR Method: Structure your answers using the Situation, Task, Action, Result (STAR) method to provide clear and concise responses.

Common Questions: Practice answering common behavioral questions, such as discussing your strengths and weaknesses, handling conflicts, and working in teams.

5. Mock Interviews

Practice with Peers: Conduct mock interviews with friends or peers to simulate the interview experience.

Professional Services: Consider using professional mock interview services to get feedback from experienced interviewers.

Essential Resources for Data Science Interview Preparation

Online Courses and Tutorials

Coursera: Offers courses from top universities on data science, machine learning, and AI.

edX: Provides access to courses from institutions like Harvard and MIT.

Udacity: Offers nanodegree programs focused on data science and machine learning.

Books

"Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron: A practical guide to implementing machine learning algorithms.

"Python for Data Analysis" by Wes McKinney: Essential for learning data manipulation with pandas.

"The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman: A comprehensive book on statistical learning methods.

Websites and Blogs

Towards Data Science: A popular Medium publication with articles on various data science topics.

Analytics Vidhya: Offers tutorials, blogs, and courses on data science and analytics.

KDNuggets: Provides news, tutorials, and resources related to data science and machine learning.

Practice Platforms

LeetCode: Offers a wide range of coding problems for practice.

Kaggle: Hosts data science competitions and provides datasets for practice.

Interview Kickstart: Provides specialized training programs, including a Data Science Interview Preparation Course designed to help you ace your interviews.

Conclusion

Preparing for a data science interview requires a structured approach, combining theoretical knowledge with practical experience. By following this guide and utilizing the recommended resources, you can enhance your preparation and increase your chances of success. Remember, consistent practice and continuous learning are key to excelling in data science interviews.

For more in-depth training and personalized coaching, consider enrolling in Interview Kickstart’s Data Science Interview Preparation Course. Our program is designed to help you master the skills and strategies needed to succeed in data science interviews and secure positions at top companies.

[datasciencedoug]

Tableau Tutorial - How to Copy and Paste Any Data Into Tableau

[accelebrate]

Frequently Asked Questions About Tableau Training Courses

In today's data-driven world, the ability to visualize and interpret data is a highly sought-after skill. Tableau, a leading data visualization tool, has become an essential asset for businesses and professionals alike. If you're considering enrolling in a Tableau training course, you likely have several questions. This blog aims to address the most common questions and concerns prospective students have about Tableau training courses.

Why Should I Learn Tableau?

Learning Tableau can significantly boost your career prospects. Here are a few reasons why you should consider learning Tableau:

High Demand for Tableau Skills: Industries require professionals who can analyze and visualize data effectively.

Ease of Use: User-friendly interface, making it accessible to both technical and non-technical users.

Career Advancement: Can lead to better job opportunities and higher salaries.

Data-Driven Decision Making: Enable you to make informed decisions based on data insights.

What Can I Expect from a Tableau Training Course?

A Tableau training course typically covers the following topics:

Introduction to Tableau: Understanding the basics of Tableau, its interface, and key features.

Data Connection: Learning how to connect Tableau to various data sources, such as Excel, SQL databases, and cloud services.

Data Preparation: Cleaning and preparing data for analysis.

Creating Visualizations: Building a variety of charts and graphs to represent data visually.

Dashboard Design: Combining multiple visualizations into interactive dashboards.

Advanced Features: Exploring advanced Tableau functionalities, such as calculated fields, parameters, and forecasting.

Do I Need Prior Experience in Data Analysis to Learn Tableau?

No prior experience in data analysis is necessary to start learning Tableau. Most courses begin with the basics and gradually progress to more advanced topics. However, having a basic understanding of data and statistics can be helpful.

Are Tableau Training Courses Expensive?

The cost of Tableau training courses can vary widely based on factors such as course length, depth of content, and provider. Free resources, such as tutorials and webinars, are available online, but paid courses are recommended for more structured and comprehensive training. These courses can range from a few hundred to several thousand dollars. 

What Certifications are Available for Tableau?

Tableau offers several certification exams to validate your skills:

Tableau Desktop Specialist

Tableau Desktop Certified Associate

Tableau Desktop Certified Professional

Tableau Server Certified Associate and Professional

How Do I Choose the Right Tableau Training Course?

Choosing the right Tableau training course depends on your goals, current skill level, and learning preferences. Here are some factors to consider:

Course Content: Ensure the course covers the topics you need to learn, from basics to advanced features.

Instructor Expertise: Look for courses taught by experienced and certified Tableau professionals.

Learning Format: Decide whether you prefer self-paced online courses, live virtual classes, or in-person training.

Reviews and Ratings: Check reviews and testimonials from previous students to gauge the quality of the course.

Choose Accelebrate for Comprehensive Tableau Training

If you're ready to embark on your Tableau learning journey, consider Accelebrate, a renowned provider of high-quality training courses. Accelebrate offers a wide range of Tableau courses designed to meet the needs of beginners and advanced users alike. Accelebrate’s expert instructors provide hands-on training, ensuring you gain practical experience and confidence in using Tableau. Whether you're looking to enhance your career prospects or improve your data visualization skills, Accelebrate has the right course for you.

With the right training, you can master Tableau and unlock the full potential of your data. Start your Tableau journey today and take the first step towards becoming a data visualization expert.

For more information visit: https://www.accelebrate.com/tableau-training

[sanjanabia]

Data Doesn't Lie: Using Data Analytics to Drive Product Decisions

In today's data-driven world, intuition alone isn't enough for product success. Making informed decisions about product features, marketing strategies, and user experience requires a deep understanding of user behavior and market trends. This is where data analytics steps in, empowering product managers to leverage the power of data for smarter product decisions. This blog dives into the world of data analytics for product management, exploring how data can be used to optimize products and drive growth. We'll also highlight how a product management certification can equip you with the skills to translate data insights into actionable product strategies.

From Gut Feeling to Data-Driven Decisions: The Power of Product Analytics

Traditionally, product decisions were often based on assumptions and experience. Data analytics, however, offers a more objective and evidence-based approach. By analyzing user data, product managers can gain valuable insights into:

User Behavior: How users interact with the product, what features they use most, and where they encounter friction points.

Market Trends: Emerging trends and competitor analysis can inform product development and identify potential market opportunities.

Customer Satisfaction: Sentiment analysis of user reviews and feedback can reveal areas for improvement and areas where the product excels.

Product Performance: Metrics like user engagement, retention, and conversion rates provide a quantitative understanding of how the product is performing.

Data Analytics in Action: How Product Managers Leverage Data

Data analytics plays a crucial role in various aspects of product management:

Product Development: Data can inform what features to build, prioritize, and test. A/B testing allows product managers to compare different versions of features and see which ones resonate better with users.

Product Optimization: Data analysis helps identify areas for improvement in the user experience. By analyzing user behavior patterns, product managers can pinpoint friction points and optimize the product flow.

Marketing and User Acquisition: Data empowers product managers to target marketing campaigns to specific user segments and optimize marketing spend for better ROI.

Retention Strategies: Data helps identify users at risk of churn and allows product managers to develop targeted retention strategies to keep them engaged.

Equipping Yourself for Data-Driven Product Management: Product Management Certification

Data analytics plays an increasingly important role in product management. Equipping yourself with the skills to collect, analyze, and interpret data is essential for success. A product management certification can provide a comprehensive foundation in data analytics for product managers, covering:

Essential Data Analytics Tools and Techniques: Learn about popular data analytics tools like Google Analytics, Mixpanel, and Tableau, and how to utilize them effectively for product analysis.

Data-Driven Decision Making: Develop the skills to translate data insights into actionable product strategies and roadmaps.

Metrics that Matter: Understand key product metrics that go beyond vanity metrics and learn how to track and analyze them effectively.

A/B Testing for Optimization: Master the principles of A/B testing and how to use it to optimize product features and user experiences.

Beyond the Product Management Certification: Continuous Learning

The field of data analytics is constantly evolving, with new tools and techniques emerging regularly. Here's how to stay ahead of the curve:

Explore Online Resources: Numerous online platforms offer courses, tutorials, and articles on data analytics for product managers.

Practice Makes Perfect: The best way to solidify your understanding is through hands-on practice. Participate in online data analytics challenges, analyze datasets relevant to your industry, and experiment with different data tools.

Stay Informed: Follow industry leaders and publications focusing on data analytics and product management. This ensures you're updated on the latest trends and best practices.

Engage with the Product Management Community: Join online forums dedicated to product management and data analytics. Connect with other product managers and data enthusiasts to share knowledge and experiences.

Conclusion: Data – The Compass for Product Success

Data analytics plays a transformative role in product management, empowering informed decision-making and accelerating product growth. By leveraging data effectively, product managers can gain a deeper understanding of their users, optimize product offerings, and drive business success. A product management certification can be a stepping stone, equipping you with the foundational knowledge and skills to navigate the data-driven world of product management. Remember, the journey of learning data analytics is continuous. Embrace a growth mindset, stay curious, and continuously expand your knowledge to become a data-driven product leader.

This blog has explored the importance of data analytics in product management and how it empowers data-driven decision making. If you're interested in sharpening your data analysis skills and propelling your product management career forward, consider pursuing a product management certification. With dedication and a commitment to continuing learning, you can unlock the power of data and become an invaluable asset in any product-driven organization.