BYTE the Cloud

Chris 0:00
All right, everyone. Welcome back for another deep dive. This time we're focusing on something super relevant for all you cloud engineers out there, especially if you're prepping for that AWS Solutions Architect Associate exam. We're talking about Amazon comprehend, that service that helps you make sense of all that text data floating around. So by the end of this deep dive, we want to be able to look at any situation and say, yep, comprehend is the tool for this job or Nope. Better use something else. We'll start broad get a feel for what comprehend is, why it's important, how it's being used out in the wild. Then we'll zoom in on the specifics, the features, the benefits and yeah, even the limitations sound good.

Kelly 0:39
Sounds like a plan. And I think this is going to be a really interesting one, because honestly, who isn't drowning in text data these days, emails, social media, documents, chat logs, it's everywhere. So being able to analyze all that extract meaning that's becoming a superpower. Okay?

Chris 0:53
So before we get lost in the sea of text, let's anchor ourselves with a clear definition. What exactly is Amazon comprehend. So

Kelly 1:00
imagine a service that can read and understand text just like you and I do, but it does it at a scale and speed we could only dream of that's comprehend. In a nutshell, it uses machine learning, specifically natural language processing, to extract insights from text

Chris 1:16
data. So it's not just counting words or finding keywords, it's actually grasping the meaning behind the words,

Kelly 1:21
exactly. It's understanding the context, the sentiment, the relationships between different concepts within the text.

Chris 1:28
Okay, that's pretty cool, but help me connect the dots here. Why should a cloud engineer care about this? How does this fit into their world? Oh, it

Kelly 1:35
fits in more ways than you might think. Think about all the applications you build, all the systems you manage. Chances are a lot of them involve text data in some way, customer reviews, support tickets, log files, social media feeds, the list goes on. Now, imagine being able to automatically analyze all that text, extract insights and use that information to improve your applications, make better decisions, even automate entire processes. Okay, I'm

Chris 1:58
starting to see the possibilities here, but I'm a real world example kind of guy, so give me some use cases, something concrete that shows me comprehend in action. All right, let's

Kelly 2:08
say you're building a social media monitoring platform for a big brand. You want to know what people are saying about their products, right? Of course, that's gold for any marketing team. Well, comprehend. Can analyze 1000s of tweets, Facebook posts, InstagRAM comments in real time. It can tell you whether the sentiment is positive, negative or neutral. It can even identify specific themes and topics that are trending.

Chris 2:32
So the brand knows what people love, what they hate, what they're talking about exactly,

Kelly 2:36
and they can use that information to fine tune their marketing campaigns, address customer concerns, even spot potential PR crises before

Chris 2:44
they blow up. Okay, that's one powerful use case.

Kelly 2:46
Now let's shift gears to healthcare. Imagine a hospital using comprehend to analyze patient records. It can extract key information, identify potential risk factors for certain diseases, even help doctors make more informed diagnoses. Wow, that's using technology for good, and there's so much more fraud detection and financial transactions, analyzing legal documents for compliance, even personalizing customer experiences based on their text interactions.

Chris 3:14
Okay, I'm convinced comprehend has some serious potential, but we've only scratched the surface here. Let's dive deeper, explore the features that make this service tick. Ready to roll up our sleeves?

Kelly 3:25
Absolutely. Let's do it. So where do we start? Comprehend has like a whole toolbox of features, each one designed to pull out different kinds of information from your text. I guess we could start with entity recognition and

Chris 3:38
see recognition, huh? Sounds pretty straightforward, does what it says on the tin, pretty much.

Kelly 3:42
Yeah, it's all about identifying the key players in your text. Think people, places, organizations, dates, even product names, anything that's a specific thing an entity comprehend, can spot it.

Chris 3:55
So it's like helping us understand who what the text is talking about, exactly. It's

Kelly 3:59
like having a super powered highlighter that picks out all the important nouns. Okay, got it. What else? All right. Next up, we've got sentiment analysis. Okay, this is where things get really cool, in my opinion.

Chris 4:09
Ooh, I'm intrigued. Lay it on me. So

Kelly 4:13
imagine being able to read between the lines, right? Not just seeing the words, but actually understanding the tone, the emotion behind them. That's what sentiment analysis does. Comprehend can tell you if a piece of text is positive, negative, neutral or even mixed. So

Chris 4:28
like if I had a bunch of customer reviews, I could use comprehend to see if people are loving my product or hating it exactly.

Kelly 4:35
And it's not just individual reviews. You could analyze 1000s of tweets, social media, comments, forum posts, whatever. Get a sense of the overall public opinion on anything your brand, a new product, a marketing campaign.

Chris 4:49
Wow. So it's like having a finger on the pulse of what people are feeling precisely. Okay, this is pretty impressive, and we're just

Kelly 4:54
getting started now. Let's say you've got a mountain of documents, reports, articles, research papers, whatever. And. Need to make sense of it all, figure out what the main themes are. That's where topic modeling comes

Chris 5:04
in. Topic modeling it is, but in a good way.

Kelly 5:07
It's like having a virtual librarian who can organize all your documents for you, automatically grouping them based on the topics they cover. So instead

Chris 5:15
of me having to read through everything comprehend, can just tell me what's

Kelly 5:19
what exactly. It saves you a ton of time and effort, lets you focus on the most relevant information. Okay, I like where this is going, but wait, there's more. Comprehend also lets you create custom models tailored to your specific needs. That's custom classification and entity recognition,

Chris 5:37
custom models. So now we're not just using comprehends built in knowledge. We're teaching it new tricks Exactly.

Kelly 5:43
Let's say you're working with like industry specific jargon, or you need to categorize data in a way that's unique to your business. With custom classification, you can train comprehend on your own data. Create a model that understands your specific terminology, your specific categories, so

Chris 6:00
I can teach comprehend to think like me. Basically,

Kelly 6:03
you got it. For example, let's say you're a healthcare provider. You want to automatically flag patient records that mention specific symptoms or diagnoses. You can train a custom bottle to do just that saves you hours of manual review. Okay,

Chris 6:17
the possibilities are pretty mind blowing here. But before we get too carried away, how does all this fit into the bigger picture of AWS, comprehend can't be a standalone thing,

Kelly 6:27
right, right? It's all about integration. Think of comprehend as one piece of your data processing puzzle. You might have data stored in S3 use Lambda functions to trigger comprehend jobs then feed the results into a database like DynamoDB, or even visualize them using QuickSight.

Chris 6:43
So it's all about connecting the dots using the right tool for the right job, exactly.

Kelly 6:47
And that's one of the beauties of comprehend. It's a managed service, meaning AWS handles all the infrastructure, the behind the scenes stuff. You can just focus on extracting insights, not managing servers. Less headache for us. I like it, plus it scales really well, so you can handle massive amounts of data and you only pay for what you use, so it's cost effective too.

Chris 7:07
Okay, hold on, hold on, before we go full fanboy on, comprehend, yeah, we gotta talk about limitations. No. Technology is perfect,

Kelly 7:13
true, true. Comprehend is powerful, but it does have some limitations. One thing to keep in mind, it's mainly designed for English text. It does support other languages, but the accuracy might not be as good. So

Chris 7:26
if I'm working with like multilingual data, I need to be aware of that

Kelly 7:29
exactly. Another thing is data preparation, like the quality of your data really impacts the quality of comprehens analysis, garbage in garbage. You got it. If your data is messy, inconsistent, poorly formatted, comprehends results might not be reliable, so clean data is key. Makes

Chris 7:46
sense. Okay, so we've covered the features, the good, the bad. I think we're ready for the next level. Let's see how this knowledge can help you crush that. AWS, solutions, Architect Associate exam. Ready for some exam style questions? Okay, let's put on our exam hands and tackle some practice questions. Imagine you're in the exam room. The clock is ticking. You see this question pop up. A company wants to automate the process of identifying customer complaints from social media posts. Which AWS service would you recommend? Ooh, that's

Kelly 8:16
a pretty common scenario, right? And yeah, Amazon comprehend would be your go to here, specifically its sentiment analysis feature. You could feed it all those social media posts, and it would tell you which ones are complaints, meaning, which ones have negative sentiment,

Chris 8:31
right? Makes sense. But what if the company also wants to know, like, what products those complaints are about? Ah, good point

Kelly 8:37
in that case, you'd want to use entity recognition as well. So comprehend could pick out the product names mentioned in those negative posts. Okay, so

Chris 8:45
we're not just finding complaints, we're getting details about them exactly. All right. Give me another one. Okay.

Kelly 8:50
How about this? How would you ensure that only authorized users have access to the sensitive data being analyzed by comprehend?

Chris 8:58
Hmm, security always important. I'm thinking, this is where I am comes in spot

Kelly 9:03
on IAM or identity and access management is your best friend for controlling access to anything in AWS and comprehend is no exception. You can use IAM policies to define who can access, comprehend, what they can do with it, what data they can see.

Chris 9:20
So we'd create specific roles and permissions for users who need to work with comprehend

Kelly 9:25
exactly. Okay,

Chris 9:25
I'm ready for a tougher one. All

Kelly 9:27
right, let's talk cost optimization. This comes up a lot in the exam. So the question is, a company wants to minimize costs associated with using comprehend. What are some strategies you can recommend?

Chris 9:37
Yeah, cost is always a factor. What are some best practices here? Well, first

Kelly 9:41
off, you want to make sure you're using the most cost effective API operations. Some are more computationally intensive, meaning they cost more so choose wisely, exactly. Then, if you've got a ton of documents to analyze, you can batch them together. Processing them in bulk is usually cheaper than doing them one by one. Batching got it. And finally, if. You're not in a hurry, consider using asynchronous analysis jobs. These run in the background, and they're often priced lower, okay,

Chris 10:06
so be smart about the operations batch when you can and go async if possible. You got it. This is really helpful stuff. Glad to hear it. I think we've covered a lot of ground here, from the basics of what Amazon comprehend is to its powerful features to how it fits into the AWS ecosystem, and even some tips for the exam. Yeah, we've definitely done a deep dive. So for all you cloud engineers out there, especially those prepping for the AWS Solutions Architect Associate exam, I think you're well equipped to not only answer questions about comprehend, but also to start using it in your own project. Absolutely.

Kelly 10:40
It's a super versatile service, and once you get the hang of it, the possibilities are endless. And

Chris 10:46
on that note, we'll wrap up today's Deep Dive. Huge thanks to our expert for sharing their knowledge and insights and to all of you listening. Thanks for joining us. We'll catch you on the next deep dive.