20. January 2018 12:00
by Aaron Medacco
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New Pluralsight Course: Visualizing Data with Amazon QuickSight

20. January 2018 12:00 by Aaron Medacco | 0 Comments

I've recently completed another course for Pluralsight, this time for Amazon QuickSight. QuickSight is a business intelligence offering within the AWS suite that allows you to import your data and analyze it using dynamic visualization. It's a rather young service, competing with other big-name products like Power BI and Tableau. It'll be interesting to see how this service evolves in the coming years given the pace at which Amazon Web Services moves. And while there are some limitations to the product which I think will be addressed soon, it's a fast and easy data analysis tool to use, especially if you're an AWS customer who already stores their data within the Amazon cloud. 

In Visualizing Data with Amazon QuickSight, I assume the viewer has no experience with Amazon QuickSight or with data analysis at all. The course begins by covering the basics such as account creation, setup and user access management. From there, it covers how to connect or import your data wherever it is to QuickSight. This might mean a flat file you want to import ad-hoc style, objects in S3, a Redshift cluster (which served as the primary data source for the course), or a database stored on-premises or with another provider. Then, I walkthrough how data preparation is done in QuickSight, which is essentially the process for taking data in it's unmodified, raw form and formatting it into a data set that will provide the most value in data analysis. Naturally, data analysis finishes out the course where we enter a deep-dive into the QuickSight data analysis interface and explore the different visualizations and features available to us.

Visualizing Data in Amazon QuickSight

Pluralsight courses are a lot of work, but I'm very satisfied with how this one turned out. There's a lot of demos, but being a very visual tool, that's not a surprise. Plus, "death by slides" is a real thing of which I've suffered through as a student myself. If you're curious about Amazon QuickSight and want to see how you might use it for your own data, go check it out

Cheers!

10. January 2018 00:06
by Aaron Medacco
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No Custom SQL Query Option in Amazon QuickSight

10. January 2018 00:06 by Aaron Medacco | 0 Comments

Whether you're practiced or new in using Amazon QuickSight to analyze your data, you're probably already aware of the fact that you define the data set for a SQL database source by either using the table selector found in the data preparation interface or you can write a custom SQL query. However, you've also probably noticed that the option to use a custom SQL query is sometimes absent from the interface when in data preparation:

Amazon QuickSight Missing SQL Option

This can happen sometimes, particularly when you have already defined and saved a data set using the table selector option. This doesn't mean you can't use the custom SQL query option. You just need to create a brand new data set from the data source so that you get into data preparation prior to the data set's creation. Doing this, you should now see the option to use custom SQL in the tables section. 

Cheers!

3. December 2017 18:42
by Aaron Medacco
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AWS re:Invent 2017 - Day 2 Experience

3. December 2017 18:42 by Aaron Medacco | 0 Comments

The following is my Day 2 re:Invent 2017 experience. Missed Day 1? Check it out here.

Day 2, I started off the day waking up around 11:30am. Needed the rest from the all-nighter drive Monday morning. Cleaning lady actually woke me up when she was making her rounds on the 4th floor. This meant that I missed the breakout session I reserved, Deploying Business Analytics at Enterprise Scale with Amazon QuickSight (ABD311). I'm currently in the process of recording a Pluralsight course on Amazon QuickSight, so I felt this information could be helpful as I wrap up that course. Guess I'll have to check it out later once the sessions are uploaded to YouTube. Just another reason to never drive through the night before re:Invent again.

After getting ready, I exposed my nerd skin to sunlight and walked over to the Venetian. This is where I'd be the majority of the day. I kind of lucked out because all of my sessions for the day besides the one I slept over were in the same hotel, and pretty back-to-back so I didn't have to get creative with my downtime. 

First session of the day was Deep Dive into the New Network Load Balancer (NET304). I was curious about this since the network load balancer's announcement recently, but never had a use case or a reason to go and implement one myself. 

AWS re:Invent 2017

I have to admit, I didn't know it could route to IP addresses.

AWS re:Invent 2017

Should have picked a better seat.

AWS re:Invent 2017

Putting it all together.

The takeaways I got was that the NLB is essentially your go-to option for TCP traffic at scale, but for web applications you'd still be mostly using the Application Load Balancer or the Classic Load Balancer. The 25% cheaper than ALB fact seems significant and it uses the same kinds of components used by ALB like targets, target groups, and listeners. Additionally, it supports routing to ECS, EC2, and external IPs, as well as allowing for static IPs per availability zone.

As I was walking out of the session, there was a massive line hugging the wall of the hall and around the corner for the next session which I had a reservation seat for (thank god). That session was Running Lean Architectures: How to Optimize for Cost Efficiency (ARC303). Nerds would have to squeeze in and cuddle for this one, this session was full. 

AWS re:Invent 2017

Before the madness.

AWS re:Invent 2017

Wasn't totally full, but pretty full.

AWS re:Invent 2017

People still filing in.

AWS re:Invent 2017

Obvious, but relevant slide.

I had some mixed feelings about this session, but thought it was overall solid. On one hand, much of the information was definitely important for AWS users to save money on their monthly bill, but at the same time, I felt a lot of it was fairly obvious to anyone using AWS. For instance, I have to imagine everybody knows they should be using Reserved Instances. I feel like any potential or current user of AWS would have read about pricing thoroughly before even considering moving to Amazon Web Services as a platform, but perhaps I'm biased. There were a fair number of managers in the session and at re:Invent in general, so maybe they're not aware of obvious ways to save money. 

Aside from covering Spot and Reserved Instance use cases, there was some time covering Convertable Reserved Instances, which is still fairly new. I did enjoy the tips and tricks given on reducing Lambda costs by looking for ways to cut down on function idle time, using Step Functions instead of manual sleep calls, and migrating smaller applications into ECS instead of running each application on their own instance. The Lambda example highlighted that many customer functions involve several calls to APIs which occur sequentially where each call waits on the prior to finish. This can rack up billed run time even though Lambda isn't actually performing work during those waiting periods. The trick they suggested was essentially to shotgun the requests all at once, instead of one-by-one, but as I thought about it, that would only work if those API calls were such that they didn't depend on the result of the prior. When they brought up Step Functions it was kind of obvious you could just use that service if that was the case, though.

The presenters did a great job, and kept highlighting the need to move to a "cattle" mentality instead of "pet" mentality when thinking about your cloud infrastructure. Essentially, they encouraged moving away from manual pushing, RDPing, naming instances thinks like "Smeagle" and the like. Honestly, a lot of no-brainers and elementary information but still a  good session.

Had some downtime after to go get something to eat. Grabbed the Baked Rigatoni from the Grand Lux Cafe in the Venetian. The woman who directed me to it probably thought I was crazy. I was in a bit of a rush, and basically attacked her with, "OMG, where is food!? Help me!"

AWS re:Invent 2017

Overall, 7/10. Wasn't very expensive and now that I think about it, my first actual meal (some cold pizza slices don't count) since getting to Vegas. 

Next up was ElastiCache Deep Dive: Best Practices and Usage Patterns (DAT305) inside the Venetian Theatre. I was excited about this session since I haven't done much of anything with ElastiCache in practice, but I know some projects running on AWS that leverage it heavily. 

AWS re:Invent 2017

About 10 minutes before getting mind-pwned.

AWS re:Invent 2017

Random guy playing some Hearthstone while waiting for the session to begin.

AWS re:Invent 2017

Sick seat.

Definitely felt a little bit out of my depth on this one. I'm not someone who is familiar with Redis, outside of just knowing what it does so I was clueless during some of the session. I didn't take notes, but I recall a lot of talk about re-sharding clusters, the old backup and recovery method vs. the new online managed re-sharding available, pros of enabling cluster mode (was clueless, made sense at the time, but couldn't explain it to someone else), security, and best practices. My favorite part of the session involved use cases and how ElastiCache can benefit: IoT, gaming apps, chat apps, rate limiting services, big data, geolocation or recommendation apps, and Ad Tech. Again, I was out of my depth, but I'll be taking a closer look at this service during 2018 to fix that.

After some more Frogger in the hallways, headed over to the Expo, grabbed some swag and walked around all the vendor booths. Food and drinks were provided by AWS and the place was a lot bigger than I expected. There's a similar event occurring at the Aria (the Quad), which I'll check out later in the week. 

AWS re:Invent 2017

Wall in front of the Expo by Registration.

There were AWS experts and team members involved with just about everything AWS scattered around to answer attendee questions which I though was freaking awesome. Valuable face-time with the actual people that work and know about the stuff being developed.

AWS re:Invent 2017

Favorite section of the Venetian Expo.

AWS re:Invent 2017

More madness.

Talked to the guys at the new PrivateLink booth to ask if QuickSight was getting an "endpoint" or a method for connecting private AWS databases soon. Ended up getting the de facto answer from the Analytics booth who had Quinton Alsbury at it. Once I saw him there, I'm like "Oh here we go, this guy is the guy!" Apparently, the feature's been recently put in public preview, which I somehow missed. Visited a few other AWS booths like Trusted Advisor and the Partner Network one, and then walked around all the vendor booths for a bit.

AWS re:Invent 2017

Unfortunately, I didn't have much time to chit chat with a lot of them since the Expo was closing soon. I'll have to do so more at the Quad. Walked over to the interactive search map they had towards the sides of the room to look for a certain company I thought might be there. Sure enough, found something familiar:

AWS re:Invent 2017

A wild technology learning company appears.

Spoke with Dan Anderegg, whose the Curriculum Manager for AWS within Pluralsight. After some talk about Pluralsight path development, I finished my beer and got out, only to find I actually stayed too long and was already super late to my final session for the day, Deep Dive on Amazon Elastic Block Store (Amazon EBS) (STG306). Did I mention how it's hard to try to do everything you want to at re:Invent? 

Ended up walking home and wanting to just chill out, which is how this post is getting done. 

Cheers!

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