Welcome to our fun dive into crafting a stellar dashboard using GA_Universe. If you're looking to bring your data visualization game to the next level, you're in the right spot. Let's roll up our sleeves and dive into the world of movies and reviews, because who doesn't love a good flick?

Our adventure begins with two trusty tables that are about to become our best friends: movies and reviews. Picture the movies table as the blockbuster list of our database, spotlighting each movie's ID, name, and genre. It's the VIP guest list to our exclusive data party. 🍿

Next, strutting down the red carpet, we have the reviews table, the life of our party. This table keeps tabs on the feedback for each movie, with columns for the movie it's referencing, the date of the review, and a singular number 1 called count you will see why later! and of course, the star of the show, the RatingValue. 🌟

Oh, and about those dates in the reviews table, they've got a special format: 2023-10-06T00:00:00. Picture it as the timestamp's way of dressing to the nines, where the time is always strutting its stuff as 000000, making sure our data stays as neat as a pin.

So, why does all this matter? Because, my friends, these two tables are about to tango together in the most spectacular dashboard dance you've ever seen. We're going to blend data, insights, and a dash of creativity to whip up a dashboard that not only tells a story but also sings and dances. Let's get this dashboard party started! 🎉

Before we pull back the curtain on our dashboard creation process, take a peek at the stars of the show through the two snapshots below. These images capture the essence of our 'movies' and 'reviews' tables, giving you a front-row seat to the data that will soon be lighting up our dashboard.

Step 1: Create a ROLAP CUBE!

All right, it's time to put our game faces on and create a ROLAP Cube! This cube is going to be our secret weapon in slicing and dicing the data for those movie buffs and critique connoisseurs. 🎲

Here's how we kick things off:

1. Start by selecting the data model that's holding our superstar tables: movies and reviews. Visualize them ready to be called up to the big leagues.
2. Now, crack open the data sources. Imagine it like opening the doors to a treasure trove, with all that precious data waiting for you.
3. Time to add a new data source. Think of it as scouting and signing a new talent to your team. This one's gonna be a keeper!
4. Give it a name. Remember, this name is sticking for life, like a tattoo, so choose wisely. Once you’ve christened your data source, it's set in stone.
5. Here’s where it gets techy - select ROLAP as your chosen one. For the uninitiated, ROLAP stands for Relational Online Analytical Processing, and it's all about handling your complex queries like a champ.
6. After that, resist the urge to fiddle around and leave the rest of the settings just as they are - let's keep it simple and slick.
7. Hit ‘Save’ and take a moment to feel that rush. You've just taken the first step towards creating a dashboard that's going to turn heads and drop jaws.

And voila! You’ve laid the foundation for some serious data analysis action. This ROLAP Cube is going to be the backbone of our dashboard, where all the magic begins. Next up, we'll be bringing this data to life, making it sing, dance, and maybe even do a backflip.

Step 2: Create timetable.

Alright, let’s shift gears and continue our dashboard journey with Step 2. After setting up our ROLAP cube, we’re diving into the realm of time. Because in the world of data, timing isn’t just everything; it’s the only thing. ⏳

Here’s how to build a robust timetable that'll serve as the backbone for time-based analysis:

1. Navigate your way: Start by heading over to the ‘Relational’ section and find the ‘Container DateTime’. It’s like finding the secret garden where all our time-related queries will grow.
2. Create a new entry: Add a new one to the mix. Think of it as planting a seed that’s going to sprout into a full-blown time-traveling tree.
3. Name your time traveler: Give it a name, and make it count because this is a one-and-done deal. No renaming, no backsies.
4. Assign a data source: For this example, we’re going to get cozy with MongoDB. Select it as your data source because that’s where our data is chilling.
5. Set the start date: This is your “Once Upon a Time” in the story of your data. Choose a start date for querying because every epic tale starts somewhere.
6. Years offset: Here’s where you decide the breadth of your narrative. Select how many years are generated for the timetable, essentially setting the stage for your historical and futuristic analyses.

Creating this timetable is like building a time machine for your data, where you can zip to any moment you need to analyze. And just like that, you’re ready to schedule the past, present, and future in your dashboard. Let’s keep the tempo up and the data flowing!

Step 3: Create Movie dimension.

Moving on to Step 3, we're going to create a dimension that's as crucial to our dashboard as popcorn is to movie night: the Movie Dimension. Here’s how we bring it to life:

1. Direct your path: In the GA_Universe of data, head over to ‘Multidimensional’ and then find the ‘Container Dimension’. This is where dimensions are not just imagined, but created.
2. Add a new star: Like casting a new lead actor, add a new dimension to your analytical screenplay.
3. Select your method: Choose ‘ROLAP’ again, because we’re consistent with our performance.
4. Edit the script: Click ‘edit query definition’ to start crafting the narrative of your dimension.
5. Set the scene: Drag and drop the movie table into the query. This is where the plot thickens.
6. Include all the details: Select all fields from the movie table because every character counts.
7. Finalize the act: Click ‘OK’ to seal the deal. Your stage is now set.

Next, add attributes as demonstrated in the table. The table showcases how the attributes should look: 'Movie' with 'ID' as the key column, marked as 'True' for the key flag, and 'Genre' with 'GenreName', not marked as a key.

A quick tip: Keep in mind that using 'GenreName' as a key column might lead to a plot twist if you have genres with the same name but different underlying keys. But, we’re in the clear for now, as we only deal with predefined genres – so no unexpected cliffhangers here.

And if you're feeling a bit like you're in a twisty thriller and can't find your way out, there's a plot device to help – the video tutorial. It’s like the director’s commentary on your favorite DVD; it’ll make everything crystal clear. So, give it a watch, and soon you'll be directing your own data-driven masterpiece. Lights, camera, action! 🎥📊

Step 4: Create time dimension

Step 4 is all about creating a dimension that keeps track of the sands of time: the Time Dimension. This dimension is not just important; it’s the very essence of trend analysis, pattern spotting, and chronological sorting. Let’s set the stage for this temporal wizardry:

1. Start your engines: Head to ‘Multidimensional’, then ‘Container Dimension’. It’s like the gateway to your data’s fourth dimension.
2. Create a new dimension: Add a fresh one into the mix. This is the realm where time starts to take shape.
3. Choose ROLAP: Stick with ‘ROLAP’ for that heavy-duty analytical lifting.
4. Tick IsTimeDim: Make sure to mark this dimension as a time dimension – this is where it gets its temporal superpowers.
5. Sculpt your dimension: Click ‘edit query definition’ to chisel out the contours of your time dimension.
6. Select your timepieces: Drag and drop the Time Table into your workspace. From here, it's like picking the ingredients for a timeless recipe.
7. Choose wisely: Select the ‘Key’, ‘Day’, ‘Month’, and ‘Year’ – these are your fundamental units of time, the building blocks of your temporal analytics.
8. Seal the deal: Click ‘OK’ to lock in your choices. You’re almost at the finish line.

Now, model your attributes just like the stars in the table – ‘Day’ as the key column with the ‘Key’ flag set to true, and ‘Month’ and ‘Year’ accompanying it without the key flag.

And remember, if you hit a wrinkle in time or get tangled in the temporal web, there’s a lifeline – the video tutorial. It’s like having a time-traveling guide by your side, ready to walk you through if you get stuck. So, take advantage if needed, and you’ll soon be the master of your own data-time continuum! ⏰📈

Step 5: Creating a cube

And now, for Step 5 – where we bring everything together and create the Cube. This isn’t just any cube; it’s a multidimensional marvel that will let us slice and dice our movie data through time. Follow these steps, and you’ll have a Cube worth showcasing on the main stage:

1. Set the stage: Make your way to ‘Multidimensional’ and then ‘Container Cube’. It’s the VIP lounge of our dashboard club, where the real magic happens.
2. Cast your Cube: Add a new one to the collection. This is where you breathe life into the framework of your analysis.
3. Name the star: Name your Cube. Make it memorable, make it snazzy, because this Cube is about to be the center of attention.
4. Stick with ROLAP: We’re consistent with our technology here; ROLAP is our go-to for its robustness and agility.
5. Add a dash of dimensions: Incorporate the movie and time dimensions you previously created. They're about to become best friends within this Cube.
6. Define the attributes: Create two values – ‘Rating’ as a double and ‘Count’ as a double. Both are set to ‘Sum’ because we want to aggregate those applause and headcounts.
7. Map your journey: In ‘Data Mapping’, hit ‘Edit Query Definition’. It’s like drawing the treasure map that leads to insights.
8. Gather your data: Drag and drop the Review Table into the query. This is where your data starts to find its purpose.
9. Select your tools: Choose all fields from the Review Table. We’re not leaving any stone unturned.
10. Connect the dots: Map the data meticulously. Line up ‘Movie’ with ‘ReviewTable -> Movie’, sync the ‘TimeDimension’ with ‘ReviewTable -> Date’, align ‘Rating’ with ‘ReviewTable -> RatingValue’, and match ‘Count’ with ‘ReviewTable -> Count’.

Creating this Cube is like conducting a symphony where every note is an insight waiting to be discovered. And if you ever feel like you're conducting in the dark, there's a tutorial video to light the way. Watch it if you’re puzzled, and it’ll guide you through, step by step, until your Cube is ready to take center stage in the data analytics orchestra. Let’s make it happen! 🧩📊

Step 6: Create Query In Page

Alright, now that our Cube is sparkling in the dashboard spotlight, let’s move on to Step 6 where we create a query that will serve as the lens through which we'll view our data-driven narrative.

1. Begin your exploration: In any empty page open the Data Description. It's like opening a book of spells where every spell is a new query that can reveal hidden insights.
2. Cast a new spell: Add a new Query. This is your blank canvas.
3. Clear the stage: Remove the default Relational Query. We're crafting a new performance from scratch.
4. Choose your model: Select the Model option and then our star performer, the Cube.
5. Set the scene on the X axis: Insert 'Movie' from the Movie Dimension onto the X axis. It's like setting the first actor on our stage.
6. Add hidden depth: Insert 'Rating' from values onto the X axis but keep it hidden – think of it as the backstage crew that’s essential but not seen.
7. More unseen support: Do the same with 'Count' – also from values, also hidden on the X axis. It’s the unsung hero that calculates the grand reveal.
8. Craft the grand reveal: Insert a calculated value and name it 'Average'. This is the grand illusion we're going to reveal to our audience.
9. Perform the calculation: Inside tasks, set it to be Rating/Count. Remember, this is your magic trick, so the internal names might differ; mine are (M3/M4), but yours may vary.
10. Test the spell: Use the start icon, usually in the top left, to see if your incantation works. It’s like a dress rehearsal.
11. Change the perspective: Drag and drop 'Month' from the Time Dimension into the Y axis. This will give us a timeline of our performance.
12. Another quick test: Hit the test button again. If all is well, you're ready for the final steps.
13. Seal the name: Save the query and rename it – make it something catchy, something memorable.
14. Bring on the visuals: Drag and drop a chart and a table onto your canvas.
15. Weave in the query: Link both elements to the query you’ve just perfected.
16. Choose your visualization: Opt for a Bar Chart from the Chart Settings. It's time to visualize the ovation of our performance.
17. The final touch: Save your creation and hit refresh. And there it is, the grand unveiling of your data on the dashboard stage.

Don’t worry if this feels like directing a blockbuster on your first go. There’s a video guide to help you nail every scene. So, if you're still feeling lost in the plot, give the video a watch. It’s like a behind-the-scenes featurette that can make you the Spielberg of data visualization! 🎬📊

And that's a wrap, folks! We've journeyed through the maze of data, crafted dimensions with the precision of master sculptors, and summoned insights as if by magic. Our dashboard, a once blank canvas, now thrums with the lifeblood of information, painting a story not just with numbers, but with bars and averages that speak louder than words.

As the curtains fall on our guide to dashboard mastery using GA_Universe, remember that this is only the beginning. Your dashboard is more than just charts and numbers; it's a living, breathing entity that will evolve with every new data point. So keep experimenting, keep analyzing, and most importantly, keep enjoying the show that is data visualization.

Feel free to revisit these steps, consult the video oracle whenever you're in doubt, and above all, trust in the power of your newfound knowledge. Now, go forth and turn your data into decisions, insights into actions, and numbers into narratives. Break a leg, data wizards, and may your analyses always be insightful! 🌟📈