Integrating Amazon QuickSight and QBusiness

Hi, everybody. My name is Rahul Eshwar. I am a Senior Product Manager with QuickSight. So the general theme over reInvent this past week was about AI, everything about AI. And you would see kind of most of the sessions talk about different aspects of it. And it was prevalent across all the different sessions. Kind of this quote stood out to me, and it kind of talks about what... are we expecting and what are we using AI for? It's to help users and individuals with increasing their own productivity. It's an aid and it's supporting different job functions and making life easier. And that's the goal of Gen AI. And the reason I kind of bring this up and kind of setting the stage is that this feature that I'll be talking about to you today is intended to do just that. It's to... bring and assist your users and yourselves in the ability to gain insights. So if you kind of look at this picture here, we typically are looking at a tool or we're going through our day-to-day processes and we have these binoculars on and we're looking at a very focused area and we're kind of doing our job and trying to get those answers to questions that we're needing. But what ends up happening is that as a result, we kind of miss that bigger picture, right? We didn't really see what else is out there, what else we could be connecting the dots on. This is actually New York, and we kind of miss that picture because we're just kind of focused on this specific task at hand. How does that kind of actually translate into what we do? So there's no shortage of data in general, but then you kind of think about data in these two. I guess, easy to kind of position methods in terms of structured and unstructured. What do we mean by those? Like unstructured data is kind of what we find in all our data-digging lives. You've got music, you've got PDF files, Word documents, emails, websites, and Unite. On the structured side, we have content that is organized, pre-built into databases. And you have this wall in between, you typically don't see one side to the other, and you kind of having to mine one independent of the other. And that's kind of should resonate to most of you. And this is kind of what the world looks like today. So we can talk about, there's no shortage of data. This particular, um, I think this is a really good question. statistics straight out. We're talking about exabytes of data in S3. I had to look up what exabytes was because it's such a large number. And that's not the only part. It's that you're also accessing this so many times, this information, over 15 million requests per second on this large amount of data. And that kind of stands out from just a structured perspective, right? And there's even more unstructured content like this. Just imagine the number of documents that you have or wikis and the folders that you're accessing on a semi-frequent basis. And again, to kind of bring this home, you can think that this is kind of like this uncompleted bridge. Both sides have data. There's no shortage of data as we've kind of just established. But they're really not connected with each other. There. near each other, you're able to kind of get from one to the other, but it's not very easy. So what ends up happening is that as a user, you get frustrated. You're frustrated because you probably have to log into multiple different applications. You have partial answers, like you know that this number is the way it is, but you don't know why. So now you've got to fire off an email to somebody else or Slack somebody and say, hey, can you help me explain this number? And you end up spending so much time doing this analysis and exercise that, unfortunately, you're spending less time on those high-value activities. So what are we hearing from customers and what are customers asking from us is that, hey, I want to be able to bring together these two worlds, the structured world with all my databases, data lakes, and data warehouses, and my unstructured content like my PDFs, Word documents, emails, websites, and be able to bring those two worlds together. So at reInvent last week, what we announced was the ability for us to now integrate Amazon QBusiness, which is our solution for unstructured data, and Amazon QuickSight, which is our answer for structured data. And by bringing these two worlds together, what we've ended up doing is providing customers the ability to be able to get insights from both unstructured content and structured content seamlessly. and within each product. I'll kind of go into the demos later to kind of show you what exactly I mean. But at this point, I want to kind of take a step back and just kind of talk about what are these tools? What is Amazon QuickSight? What is Amazon Q Business? What do they do? And then kind of talk about what this new feature and capability brings to each of these products independently. So Amazon Q Business is a... AI-powered assistant. Think about it as a chatbot, effectively, that's able to answer all these questions, provide summaries, able to generate content, and it's all secure. So that way, only the data that you should have access to is what data is being exposed. It has over 40 plus connections to a variety of different sources. Some of these you can see here. And what it allows is the... ability for users to be able to kind of discover content. Think of it as a very high-powered search. You're able to kind of ask questions, and it's able to mine across all these different sources and be able to pull back information that's relevant. You're able to upload documents and be able to ask questions against that and be able to kind of analyze those as well. You're able to create applications. and be able to take actions on those applications as well. So if there's something that you repeatedly are doing, then it'll suggest that, hey, why don't you go create an app for this? So that way you can automate that versus you having to kick off those things on a consistent basis. And you can take actions such as, hey, I want to be able to Slack this person, or I want to be able to kind of initiate this outbound action as well. So. On the right here, you can see an example of an output from Amazon Q Business. You can see, given the question about availability zones, it's able to kind of provide contextual text-based responses with sources cited, which are the ones and twos right there. So that way, you're able to kind of correlate this back to where Amazon Q Business was able to get the information from, thus increasing the trust in those answers. It provides context, so that way now you can ask follow-up questions against that same question and be able to then continue having this dialogue. You're able to also preserve these conversations in the conversation history, so you can always come back to them and then be able to kind of see what conversations you were having and then pick that up as well. So when you connect to data sources like... Salesforce, SharePoint, Google. As part of the process of going and getting all this information, the content is ingested into the Q business indexes and retrievers. The information is also protected and secure using the document permissions or ACLs. Using this, only the users that should have access to this information are exposed to the relevant information. So you can imagine that I have connected my Google Drive to QBusiness, and now I'm querying against that data. My expectation and what will be honored is that only the content that I have access to from my drive will be exposed to me. If another user were to upload their own documents and secured it, those would not be exposed in terms of the retrieval and the content that's generated back. So now going back to what did we announce last week. So when we think about how did these two worlds, we talked about Amazon QuickSight, we talked about the Q&A experience and the data story experience and all the different aspects there. And we talked about Amazon Q business and providing those unstructured responses. So how are these two worlds coming together? So when we think about the Amazon Q&A experience within QuickSight, you can think about, hey, now we're able to ask questions like we used to do before. But when we're getting those responses back, the multivisual responses, now we're also being able to pull in relevant content from Amazon Q business. So that way, not only am I getting answers from my databases and data sources. But I'm also getting these insights from documents and repositories that I may not have otherwise been able to make that connection. And similarly from a data story perspective. So now not only can I provide a prompt, select specific visuals, but I can also now upload documents from my own local repository. Something maybe I have authored, something that I want to use. in my narrative. And I'm also now also able to pull from the Q business index files. So as a result, we're utilizing all these different sources to create this beautiful looking rich narrative that has context and is able to provide specific insights. So let's jump into a demo and I think hopefully this will hit home and you'll be able to kind of relate that to a specific thing. So here in this particular demo, I'm going to be walking through an example where we're going to be a sales pipeline overview. So I have sales data coming in, I have different deals, and I'm ingesting all this information into QuickSight. So here I'm in my QuickSight screen, and you can see I already have a dashboard already built. We have KPIs like targets and due diligence, and what we're curious about right now is... by industry, how are we tracking to deals? So you can see here, we already have a pie chart against this, but I'm going to be using the Q&A bar on the top, and we're going to be asking a specific question such as, what are the deals by industry? And when I do so, you can see that I am behind the scenes, Amazon Q and QuickSight is asking the question, generating all these different visuals. And it's also summarizing the top left that there are 73 unique option days. But the cool part is you can see it also pulled from all these different sources like press releases, memos, executive summaries, and it's pulled some additional insights about deals by industry. I'm able to ask another question. Let's say I want to forecast deals by month. So. Behind the scenes, Amazon Qt QuickSight is using its own mechanisms by which to generate this forecast data. And you can see that here by opportunities. It's able to kind of summarize that to indicate what is the growth expectation. But what is also nice is that it found a relevant forecast document about the pipeline improvements that somebody had authored and is available in my Amazon Q business repository. As a result of doing this, what it's allowed me to do is be able to correlate the forecasted information here with additional insights that somebody had authored. Thereby being able to kind of correlate the two, I'm able to see does this really make sense? Is there some adjustments I need to do potentially? Are there some opportunities that do correlate to this? And maybe on which side of this? Is it going to be a positive trend or a negative trend that I need to be able to indicate? This may have resulted in me going to the work doc, Salesforce, or some other repositories to go mine this myself, or maybe I wouldn't have even bothered to do so. As a user, now I'm able to get all this information in context where I need the data the most without having to jump between different places. So let's take a look at. data stories. So again we're going to use the same example but instead of going through the dashboard itself I'm going to be able to go to the data, sorry there you go, so I'll be going to the good data story here. So you can see I'm able to kind of provide a prompt about give me a story about the sales pipeline, but I also want specific actions that can be taken so that we can improve our pipeline for next year. I'm able to provide specific visuals that I believe would be useful. And not only that, but let's say I wrote an internal memo that has some of those actions that I wanted to take. And I want to incorporate that into this build. As I'm building out this data story, you can see that Amazon Q in QuickSight is able to pull and generate text. It's able to provide bulleted information, utilize those charts. as meaningful in context, but it's also able to take some specific recommendations and actions that I had put in my memo into this overall story. What I've had to do otherwise potentially is export this out and then maybe copy and paste something else in and be able to go through this iteration, whereas ideally it should work like this. Pull relevant information as necessary. be able to provide a comprehensive overview and then allow me to kind of take an overall pass at this and then be able to send this off or share this with my colleagues. So you're probably thinking okay you know what this is probably going to take a while, this is a big integration, what are we going to do? Actually it's pretty straightforward and we kind of built it intentionally with that in mind. So you can see here I'm going to start all the way from basics. I'm going to start with hey let's assume you don't even have a QuickSight account. You don't have anything set up. What is it going to take? So you can see with a few short inputs, you're able to kind of get a QuickSight account created, right? That's pretty easy. And from here, you can see that there's an integration or there's an opportunity for you to create an application in QBusiness. We're actually going to go do it somewhere else. We're going to skip that for now. And then you can see that once I get my QuickSight account up and running, I can then, so it's going to like pull out additional samples to get started. And then what you can see is if I'm able to go in as an admin, I have a new area for under security permissions where I'm able to add Amazon QBusiness integration. In this particular example, I don't even have a QBusiness account created. So I'm able to provide an application name that is maybe meaningful, like QBusiness application. You're able to apply your own customer managed key if you wanted to do so. And when you click done, a new tab opens up. The application is already created. You're able to select what retriever or index you need. This allows QBusiness to be able to index those documents and files, et cetera, that you're pointing them to. You're able to create and select from any of those 40. unique data sources that Amazon Q business allows for. You can see if I select web crawler as an example, by providing a little bit of basic information about what domains I want to be able to index, where the files exist, etc. It will go off and then be able to index this behind the scenes and then allow for that retrieval. That's essentially it. What happens also behind, what is happening behind the scenes is that all your QuickSight Pro users are provisioned as QBusiness Pro users. This is part of the entitlement that you already have as a Pro user between those QBusiness and QuickSight. All the necessary security and permissions are being handled behind the scenes, and everything is a very seamless experience. And it's as easy as that to kind of get started. And then what will happen in the QuickSight side after this is that you will then obviously set up your topics and Q&A and dashboards, and you'll kind of start doing those parts. But the QBusiness integration and the insights that QBusiness offers will natively start coming through. So now that we kind of took a look at the QuickSight to QBusiness integration, let's take a look at what the other side of the world looks like, which is from QBusiness. pulling in QuickSight integration. So a couple of key highlights here. Amazon Q Business will now provide a native integration with Amazon Q QuickSight. What it allows the Q Business experience to do is get enriched answers by pulling in QuickSight visuals into the Q Business response. So if you recall all the way back when I kind of introduced Q Business, we saw that text-based narrative. Now we're able to kind of get QuickSight visuals there as well. As a result of doing this, Q Business users are now able to take advantage of QuickSights integration with structured data sources. And the nice part about all this is because it's under that same pro user umbrella, as long as you're a pro user, you're able to, for that one flat charge, be able to access both QBusiness as well as QuickSight. So from an experience perspective, you can see that that text-based response that QBusiness typically offers is now augmented with the multivisual response in this example. that QuickSight came back with. And that's not all. You're able to kind of click on this explore insights and you're able to navigate back into QuickSight. Because again, we know who you are and the user permissions, the way you're set up, you're able to navigate back and forth and provide that very rich experience. So in this particular case, if I wanted to drill down and learn more, as a user, I can do so very seamlessly and from the same viewpoint. So let's take a look at a demo and let's see what it looks like from that perspective here. So the stage here is that I'm a quick site, I'm an AWS customer and I am looking up my cost details and I want to look up information related to how I'm spending on AWS and where am I spending. All right so there should be a hopefully a relatable use case or data story for most of you. So here we're going to start by asking the question of what are my top spending services? So you can see here the responses coming back from QuickSight. It makes sense because you're kind of asking very KPI-oriented questions. You can see that this visual also represents, and it's kind of indicated in the bottom right, that it's been authored by QuickSight. Now, let's say I don't know what this S3 thing is. So I'm going to ask, what is S3? And you can see that the response first comes back from Amazon Q Business, citing different sources from public and local repositories about what is S3. Now, as a follow-up question to that, I want to be able to ask, showing amortized costs by service. Again, if you're able to kind of ask this question. we're able to kind of interpret that as a, hey, this should be answered by QuickSight. And it goes off and fires off that question, getting this, again, multivisual response. From here, you can see that I'm able to slice and dice, take all those particular actions that I would be able to do within Q and QuickSight today. But not only that, but let's say I want to kind of dive deeper on this particular area. By clicking on that export insights, it's taking that same prompt that I had provided back in context on this topic. So that way now I'm within the QuickSight world. From here, I can add to a pin board as an example. So that way it's always persisted and it's localized for me as a user within QuickSight. I'm able to then go back and forth, ask different questions, maybe navigate to a dashboard, be able to take all those different actions that I would have been able to do. In this case, let's say I will come back into Q Business and I want to continue my conversation here. And I want to say I want to compare what Glue and S3 is. The nice thing here is that it first starts off by explaining to me what is Glue, what is S3 and what are the differences. And then it's also able to come back with a quick site response about what is the cost differences between these two services. And you can see here where it kind of filtered down to only the two services that are of relevance. And it's providing me those insights and that information as well. And the nice thing is it's able to kind of, as a user, you're able to not only get the context of what are these two individual services, but you're also able to get the numerical context behind each of those. So you're able to kind of marry those two worlds and be able to kind of get those broader, richer insights across those two things. So that's from a Q business experience standpoint. You can see that that conversational experience is further enhanced by these rich visuals from QuickSight directly. So if we kind of take a look at what does it take now from Q business to set up this integration? It's equally simple to that QuickSight experience that we saw. If you're setting up from Q Business, you have a list of these different capabilities. Because Amazon QuickSight is a native integration, we have a new area for that. You can see there are three easy steps. If you don't have a QuickSight account, there's a wizard here that can walk you through that QuickSight account creation process. If you already have one, it's even simpler. In the same AWS account, same AWS region, you're able to point directly to that as long as your security and permissions are the same. From there, if you have the dashboards and topics created that are relevant, You need to share those with those users that have recently been set up, and you're off to the races, right? So it's that easy. Again, as long as the users are singly provisioned and you're able to kind of use that same information, you're able to translate that information back and forth, providing that seamless view for about users. And you can see that QuickSight has all of these different. data sets and data sources today. It's constantly growing. There's always more that are being added. But as a result of doing both of these integrations, you're able to kind of get the best of both worlds across all of these. So if we were going to think about this, kind of what are some of the key takeaways they should take away today? First and foremost, this with this announcement last week, the exciting part and the exciting thing is you're able to now get a unified insights across both structured and unstructured data. Structured with your data sources, databases, data warehouses, data lakes, and your unstructured data with your websites, documents, file repositories, and document repositories. You're able to get these insights within QuickSight in the Q&A experience. So as a user you're able to kind of ask those questions. In context, you're able to get those and get information from your unstructured data. You're also able to use data stories. You're able to kind of upload those files, if you remember, and be able to get insights from the Amazon Q business unstructured data there as well. And then similarly on the Q business side, you're able to get those single and multivisual responses from QuickSight in context in that conversational history. You're also able to deep link directly into QuickSight. So if I click down that Explore Insights, you saw that we're able to go directly into QuickSight, open up that topic or open up that Q&A, open up the dashboard. So you're able to provide that direct link and the synergy for the users. And kind of some of the key highlights, that embeddable experience, right? You're able to kind of take this experience. You're able to put this into your own application. You're able to kind of expose all these capabilities, whether it be Q&A or the chat experience for your users. And if you wanted more finer grain control, you're able to utilize APIs to be able to get that information as well. And the nice thing about all this is that it's available to all Q Pro users. So again, if you're a reader pro or an author pro, you are able to combine all this and be able to utilize both. QuickSight and QBusiness together. So there's no reason for you not to go try it out. And as I showed, it's very easy to get set up, very easy to get started. And the number of different use cases and options are quite far and less.

Hi, everybody. My name is Rahul Eshwar. I am a Senior Product Manager with QuickSight.

So the general theme over reInvent this past week was about AI, everything about AI. And you would see kind of most of the sessions talk about different aspects of it. And it was prevalent across all the different sessions. Kind of this quote stood out to me, and it kind of talks about what... are we expecting and what are we using AI for?

It's to help users and individuals with increasing their own productivity. It's an aid and it's supporting different job functions and making life easier. And that's the goal of Gen AI.

And the reason I kind of bring this up and kind of setting the stage is that this feature that I'll be talking about to you today is intended to do just that. It's to... bring and assist your users and yourselves in the ability to gain insights. So if you kind of look at this picture here, we typically are looking at a tool or we're going through our day-to-day processes and we have these binoculars on and we're looking at a very focused area and we're kind of doing our job and trying to get those answers to questions that we're needing. But what ends up happening is that as a result, we kind of miss that bigger picture, right?

We didn't really see what else is out there, what else we could be connecting the dots on. This is actually New York, and we kind of miss that picture because we're just kind of focused on this specific task at hand. How does that kind of actually translate into what we do?

So there's no shortage of data in general, but then you kind of think about data in these two. I guess, easy to kind of position methods in terms of structured and unstructured. What do we mean by those?

Like unstructured data is kind of what we find in all our data-digging lives. You've got music, you've got PDF files, Word documents, emails, websites, and Unite. On the structured side, we have content that is organized, pre-built into databases.

And you have this wall in between, you typically don't see one side to the other, and you kind of having to mine one independent of the other. And that's kind of should resonate to most of you. And this is kind of what the world looks like today. So we can talk about, there's no shortage of data. This particular, um, I think this is a really good question.

statistics straight out. We're talking about exabytes of data in S3. I had to look up what exabytes was because it's such a large number. And that's not the only part. It's that you're also accessing this so many times, this information, over 15 million requests per second on this large amount of data.

And that kind of stands out from just a structured perspective, right? And there's even more unstructured content like this. Just imagine the number of documents that you have or wikis and the folders that you're accessing on a semi-frequent basis.

And again, to kind of bring this home, you can think that this is kind of like this uncompleted bridge. Both sides have data. There's no shortage of data as we've kind of just established.

But they're really not connected with each other. There. near each other, you're able to kind of get from one to the other, but it's not very easy.

So what ends up happening is that as a user, you get frustrated. You're frustrated because you probably have to log into multiple different applications. You have partial answers, like you know that this number is the way it is, but you don't know why. So now you've got to fire off an email to somebody else or Slack somebody and say, hey, can you help me explain this number? And you end up spending so much time doing this analysis and exercise that, unfortunately, you're spending less time on those high-value activities.

So what are we hearing from customers and what are customers asking from us is that, hey, I want to be able to bring together these two worlds, the structured world with all my databases, data lakes, and data warehouses, and my unstructured content like my PDFs, Word documents, emails, websites, and be able to bring those two worlds together. So at reInvent last week, what we announced was the ability for us to now integrate Amazon QBusiness, which is our solution for unstructured data, and Amazon QuickSight, which is our answer for structured data. And by bringing these two worlds together, what we've ended up doing is providing customers the ability to be able to get insights from both unstructured content and structured content seamlessly.

and within each product. I'll kind of go into the demos later to kind of show you what exactly I mean. But at this point, I want to kind of take a step back and just kind of talk about what are these tools?

What is Amazon QuickSight? What is Amazon Q Business? What do they do?

And then kind of talk about what this new feature and capability brings to each of these products independently. So Amazon Q Business is a... AI-powered assistant. Think about it as a chatbot, effectively, that's able to answer all these questions, provide summaries, able to generate content, and it's all secure.

So that way, only the data that you should have access to is what data is being exposed. It has over 40 plus connections to a variety of different sources. Some of these you can see here.

And what it allows is the... ability for users to be able to kind of discover content. Think of it as a very high-powered search. You're able to kind of ask questions, and it's able to mine across all these different sources and be able to pull back information that's relevant.

You're able to upload documents and be able to ask questions against that and be able to kind of analyze those as well. You're able to create applications. and be able to take actions on those applications as well.

So if there's something that you repeatedly are doing, then it'll suggest that, hey, why don't you go create an app for this? So that way you can automate that versus you having to kick off those things on a consistent basis. And you can take actions such as, hey, I want to be able to Slack this person, or I want to be able to kind of initiate this outbound action as well.

So. On the right here, you can see an example of an output from Amazon Q Business. You can see, given the question about availability zones, it's able to kind of provide contextual text-based responses with sources cited, which are the ones and twos right there. So that way, you're able to kind of correlate this back to where Amazon Q Business was able to get the information from, thus increasing the trust in those answers.

It provides context, so that way now you can ask follow-up questions against that same question and be able to then continue having this dialogue. You're able to also preserve these conversations in the conversation history, so you can always come back to them and then be able to kind of see what conversations you were having and then pick that up as well. So when you connect to data sources like...

Salesforce, SharePoint, Google. As part of the process of going and getting all this information, the content is ingested into the Q business indexes and retrievers. The information is also protected and secure using the document permissions or ACLs.

Using this, only the users that should have access to this information are exposed to the relevant information. So you can imagine that I have connected my Google Drive to QBusiness, and now I'm querying against that data. My expectation and what will be honored is that only the content that I have access to from my drive will be exposed to me. If another user were to upload their own documents and secured it, those would not be exposed in terms of the retrieval and the content that's generated back. So now going back to what did we announce last week.

So when we think about how did these two worlds, we talked about Amazon QuickSight, we talked about the Q&A experience and the data story experience and all the different aspects there. And we talked about Amazon Q business and providing those unstructured responses. So how are these two worlds coming together?

So when we think about the Amazon Q&A experience within QuickSight, you can think about, hey, now we're able to ask questions like we used to do before. But when we're getting those responses back, the multivisual responses, now we're also being able to pull in relevant content from Amazon Q business. So that way, not only am I getting answers from my databases and data sources.

But I'm also getting these insights from documents and repositories that I may not have otherwise been able to make that connection. And similarly from a data story perspective. So now not only can I provide a prompt, select specific visuals, but I can also now upload documents from my own local repository. Something maybe I have authored, something that I want to use. in my narrative.

And I'm also now also able to pull from the Q business index files. So as a result, we're utilizing all these different sources to create this beautiful looking rich narrative that has context and is able to provide specific insights. So let's jump into a demo and I think hopefully this will hit home and you'll be able to kind of relate that to a specific thing. So here in this particular demo, I'm going to be walking through an example where we're going to be a sales pipeline overview.

So I have sales data coming in, I have different deals, and I'm ingesting all this information into QuickSight. So here I'm in my QuickSight screen, and you can see I already have a dashboard already built. We have KPIs like targets and due diligence, and what we're curious about right now is... by industry, how are we tracking to deals?

So you can see here, we already have a pie chart against this, but I'm going to be using the Q&A bar on the top, and we're going to be asking a specific question such as, what are the deals by industry? And when I do so, you can see that I am behind the scenes, Amazon Q and QuickSight is asking the question, generating all these different visuals. And it's also summarizing the top left that there are 73 unique option days. But the cool part is you can see it also pulled from all these different sources like press releases, memos, executive summaries, and it's pulled some additional insights about deals by industry. I'm able to ask another question.

Let's say I want to forecast deals by month. So. Behind the scenes, Amazon Qt QuickSight is using its own mechanisms by which to generate this forecast data.

And you can see that here by opportunities. It's able to kind of summarize that to indicate what is the growth expectation. But what is also nice is that it found a relevant forecast document about the pipeline improvements that somebody had authored and is available in my Amazon Q business repository.

As a result of doing this, what it's allowed me to do is be able to correlate the forecasted information here with additional insights that somebody had authored. Thereby being able to kind of correlate the two, I'm able to see does this really make sense? Is there some adjustments I need to do potentially?

Are there some opportunities that do correlate to this? And maybe on which side of this? Is it going to be a positive trend or a negative trend that I need to be able to indicate?

This may have resulted in me going to the work doc, Salesforce, or some other repositories to go mine this myself, or maybe I wouldn't have even bothered to do so. As a user, now I'm able to get all this information in context where I need the data the most without having to jump between different places. So let's take a look at.

data stories. So again we're going to use the same example but instead of going through the dashboard itself I'm going to be able to go to the data, sorry there you go, so I'll be going to the good data story here. So you can see I'm able to kind of provide a prompt about give me a story about the sales pipeline, but I also want specific actions that can be taken so that we can improve our pipeline for next year. I'm able to provide specific visuals that I believe would be useful. And not only that, but let's say I wrote an internal memo that has some of those actions that I wanted to take.

And I want to incorporate that into this build. As I'm building out this data story, you can see that Amazon Q in QuickSight is able to pull and generate text. It's able to provide bulleted information, utilize those charts. as meaningful in context, but it's also able to take some specific recommendations and actions that I had put in my memo into this overall story.

What I've had to do otherwise potentially is export this out and then maybe copy and paste something else in and be able to go through this iteration, whereas ideally it should work like this. Pull relevant information as necessary. be able to provide a comprehensive overview and then allow me to kind of take an overall pass at this and then be able to send this off or share this with my colleagues. So you're probably thinking okay you know what this is probably going to take a while, this is a big integration, what are we going to do?

Actually it's pretty straightforward and we kind of built it intentionally with that in mind. So you can see here I'm going to start all the way from basics. I'm going to start with hey let's assume you don't even have a QuickSight account.

You don't have anything set up. What is it going to take? So you can see with a few short inputs, you're able to kind of get a QuickSight account created, right? That's pretty easy. And from here, you can see that there's an integration or there's an opportunity for you to create an application in QBusiness.

We're actually going to go do it somewhere else. We're going to skip that for now. And then you can see that once I get my QuickSight account up and running, I can then, so it's going to like pull out additional samples to get started. And then what you can see is if I'm able to go in as an admin, I have a new area for under security permissions where I'm able to add Amazon QBusiness integration. In this particular example, I don't even have a QBusiness account created.

So I'm able to provide an application name that is maybe meaningful, like QBusiness application. You're able to apply your own customer managed key if you wanted to do so. And when you click done, a new tab opens up. The application is already created. You're able to select what retriever or index you need.

This allows QBusiness to be able to index those documents and files, et cetera, that you're pointing them to. You're able to create and select from any of those 40. unique data sources that Amazon Q business allows for. You can see if I select web crawler as an example, by providing a little bit of basic information about what domains I want to be able to index, where the files exist, etc. It will go off and then be able to index this behind the scenes and then allow for that retrieval. That's essentially it.

What happens also behind, what is happening behind the scenes is that all your QuickSight Pro users are provisioned as QBusiness Pro users. This is part of the entitlement that you already have as a Pro user between those QBusiness and QuickSight. All the necessary security and permissions are being handled behind the scenes, and everything is a very seamless experience. And it's as easy as that to kind of get started.

And then what will happen in the QuickSight side after this is that you will then obviously set up your topics and Q&A and dashboards, and you'll kind of start doing those parts. But the QBusiness integration and the insights that QBusiness offers will natively start coming through. So now that we kind of took a look at the QuickSight to QBusiness integration, let's take a look at what the other side of the world looks like, which is from QBusiness.

pulling in QuickSight integration. So a couple of key highlights here. Amazon Q Business will now provide a native integration with Amazon Q QuickSight. What it allows the Q Business experience to do is get enriched answers by pulling in QuickSight visuals into the Q Business response. So if you recall all the way back when I kind of introduced Q Business, we saw that text-based narrative.

Now we're able to kind of get QuickSight visuals there as well. As a result of doing this, Q Business users are now able to take advantage of QuickSights integration with structured data sources. And the nice part about all this is because it's under that same pro user umbrella, as long as you're a pro user, you're able to, for that one flat charge, be able to access both QBusiness as well as QuickSight. So from an experience perspective, you can see that that text-based response that QBusiness typically offers is now augmented with the multivisual response in this example. that QuickSight came back with.

And that's not all. You're able to kind of click on this explore insights and you're able to navigate back into QuickSight. Because again, we know who you are and the user permissions, the way you're set up, you're able to navigate back and forth and provide that very rich experience.

So in this particular case, if I wanted to drill down and learn more, as a user, I can do so very seamlessly and from the same viewpoint. So let's take a look at a demo and let's see what it looks like from that perspective here. So the stage here is that I'm a quick site, I'm an AWS customer and I am looking up my cost details and I want to look up information related to how I'm spending on AWS and where am I spending.

All right so there should be a hopefully a relatable use case or data story for most of you. So here we're going to start by asking the question of what are my top spending services? So you can see here the responses coming back from QuickSight. It makes sense because you're kind of asking very KPI-oriented questions. You can see that this visual also represents, and it's kind of indicated in the bottom right, that it's been authored by QuickSight.

Now, let's say I don't know what this S3 thing is. So I'm going to ask, what is S3? And you can see that the response first comes back from Amazon Q Business, citing different sources from public and local repositories about what is S3.

Now, as a follow-up question to that, I want to be able to ask, showing amortized costs by service. Again, if you're able to kind of ask this question. we're able to kind of interpret that as a, hey, this should be answered by QuickSight.

And it goes off and fires off that question, getting this, again, multivisual response. From here, you can see that I'm able to slice and dice, take all those particular actions that I would be able to do within Q and QuickSight today. But not only that, but let's say I want to kind of dive deeper on this particular area. By clicking on that export insights, it's taking that same prompt that I had provided back in context on this topic. So that way now I'm within the QuickSight world.

From here, I can add to a pin board as an example. So that way it's always persisted and it's localized for me as a user within QuickSight. I'm able to then go back and forth, ask different questions, maybe navigate to a dashboard, be able to take all those different actions that I would have been able to do.

In this case, let's say I will come back into Q Business and I want to continue my conversation here. And I want to say I want to compare what Glue and S3 is. The nice thing here is that it first starts off by explaining to me what is Glue, what is S3 and what are the differences. And then it's also able to come back with a quick site response about what is the cost differences between these two services.

And you can see here where it kind of filtered down to only the two services that are of relevance. And it's providing me those insights and that information as well. And the nice thing is it's able to kind of, as a user, you're able to not only get the context of what are these two individual services, but you're also able to get the numerical context behind each of those.

So you're able to kind of marry those two worlds and be able to kind of get those broader, richer insights across those two things. So that's from a Q business experience standpoint. You can see that that conversational experience is further enhanced by these rich visuals from QuickSight directly. So if we kind of take a look at what does it take now from Q business to set up this integration? It's equally simple to that QuickSight experience that we saw.

If you're setting up from Q Business, you have a list of these different capabilities. Because Amazon QuickSight is a native integration, we have a new area for that. You can see there are three easy steps.

If you don't have a QuickSight account, there's a wizard here that can walk you through that QuickSight account creation process. If you already have one, it's even simpler. In the same AWS account, same AWS region, you're able to point directly to that as long as your security and permissions are the same. From there, if you have the dashboards and topics created that are relevant, You need to share those with those users that have recently been set up, and you're off to the races, right? So it's that easy.

Again, as long as the users are singly provisioned and you're able to kind of use that same information, you're able to translate that information back and forth, providing that seamless view for about users. And you can see that QuickSight has all of these different. data sets and data sources today. It's constantly growing. There's always more that are being added.

But as a result of doing both of these integrations, you're able to kind of get the best of both worlds across all of these. So if we were going to think about this, kind of what are some of the key takeaways they should take away today? First and foremost, this with this announcement last week, the exciting part and the exciting thing is you're able to now get a unified insights across both structured and unstructured data.

Structured with your data sources, databases, data warehouses, data lakes, and your unstructured data with your websites, documents, file repositories, and document repositories. You're able to get these insights within QuickSight in the Q&A experience. So as a user you're able to kind of ask those questions.

In context, you're able to get those and get information from your unstructured data. You're also able to use data stories. You're able to kind of upload those files, if you remember, and be able to get insights from the Amazon Q business unstructured data there as well.

And then similarly on the Q business side, you're able to get those single and multivisual responses from QuickSight in context in that conversational history. You're also able to deep link directly into QuickSight. So if I click down that Explore Insights, you saw that we're able to go directly into QuickSight, open up that topic or open up that Q&A, open up the dashboard.

So you're able to provide that direct link and the synergy for the users. And kind of some of the key highlights, that embeddable experience, right? You're able to kind of take this experience.

You're able to put this into your own application. You're able to kind of expose all these capabilities, whether it be Q&A or the chat experience for your users. And if you wanted more finer grain control, you're able to utilize APIs to be able to get that information as well. And the nice thing about all this is that it's available to all Q Pro users.

So again, if you're a reader pro or an author pro, you are able to combine all this and be able to utilize both. QuickSight and QBusiness together. So there's no reason for you not to go try it out.

And as I showed, it's very easy to get set up, very easy to get started. And the number of different use cases and options are quite far and less.

Transcript for:Integrating Amazon QuickSight and QBusiness

Transcript for:
Integrating Amazon QuickSight and QBusiness