Gerryson Mehta

Learning Tableau is like learning to use a fancy data picture maker! No coding required. Here's why:

Drag-and-Drop Friendly: Tableau uses drag-and-drop features, so you can build charts and dashboards without needing a ton of tech skills.

Focus on Exploring Data: Tableau is more about understanding your data by making pictures (visualizations) of it, not writing complicated code.

Some things that can help you learn Tableau faster:

Knowing a little about data: Knowing things like data types and tables is like having some photography basics before using the fancy camera (Tableau).

Spreadsheet skills: If you're comfortable with spreadsheets like Excel, you'll pick up Tableau quicker because they both involve organizing data.

Problem-solving: Good problem-solving skills are like knowing what kind of picture you want to take. They help you use Tableau to answer your questions about the data.

The bottom line: You can be a Tableau whiz without being a tech pro! But a little data knowledge and some spreadsheet skills can give you a head start.

Imagine Tableau 8.3 and 9.0 as versions of a data picture maker. Version 9.0 has some cool new features:

• Groups: Make special groups in your data to study them better, like looking at just fruits from your grocery list.
• Drill Down Control: Have more control over how data is calculated, like making sure you only add apples and oranges, not the whole shopping list.
• Easier Mixing Data: Combine data from different places (spreadsheets, databases) more easily, like putting fruits from two stores together.
• New Picture Types: See your data in new ways, like charts with two lines for even more info. You can also make dashboards more interactive.
• Faster Work: The picture maker works quicker, so you can see your data pictures faster.

Overall, Tableau 9.0 is a bigger and better toolbox for making data pictures! There might be other smaller changes, but these are the main ones.

Data scientists are like detectives, uncovering secrets from data. Tableau helps them with this detective work in a few ways:

• Spotting Clues: Tableau's charts and graphs help data scientists see patterns and trends in data easily, like a magnifying glass for data.
• Sharing Findings: Data scientists can use Tableau to create clear pictures (visualizations) to explain their findings to everyone, even those who aren't data experts.
• Telling the Data Story: Tableau helps data scientists tell a clear story about what the data means, using charts and graphs instead of words.
• Testing Ideas Quickly: Imagine creating draft pictures in Tableau before finalizing them. That's what data scientists can do to test their ideas with visualizations before diving into code.

Even though Tableau isn't used for the toughest detective work (building models), it's a great tool for data scientists to see clues, share findings, and tell data stories in a clear way.

A Tableau developer is like a data superhero with a mix of skills:

• Data Wrangler: They collect data from everywhere (databases, spreadsheets) and clean it up for Tableau, like wrangling horses for a show.
• Data Artist: They use Tableau to create charts and dashboards that tell clear stories from the data, like painting pictures with data.
• Data Analyst (sometimes): They might also uncover interesting trends or patterns in the data, like a detective finding clues.
• Tech Expert: They know all the ins and outs of Tableau, like a mechanic who knows how to fix a car.
• Communicator: They explain the data stories in charts and dashboards to others, like a teacher explaining things to students.

So, Tableau developers turn raw data into clear and understandable stories, making them valuable assets in the data world!

Choosing between Tableau and Informatica is like picking a data skill! Here's why Tableau might be a better first choice:

Tableau: Imagine a tool that makes data easy to understand with charts and graphs, like a translator for your data. It's easier to learn and there's a big demand for people who can do this.

Informatica: This tool is like a data organizer, sorting and managing huge amounts of data behind the scenes. It's more technical and for specific jobs.

Think of it like this:

Learn Tableau first, like learning how to talk about data.\

Then you can learn Informatica later, like learning how to organize data behind the scenes.

Both are valuable, but Tableau is a great first step, especially for beginners!