Some of the questions asked an answered are below:
Deanne Branham (00:10):
Thank you so much, Chris. And thanks everyone for attending. We really appreciate it, and hope that you find this quite interesting. It will be very interesting for me because I get to actually drill my manager. And that you don't always get that opportunity, and he has to actually be very nice about it, and he has to like it. So great opportunity for me, right?
Deanne Branham (00:31):So let's get started. And so just to let everybody know, we've actually had some questions that were submitted to us prior to this session. So what we're going to do is we're going to start off with those. And one of the biggest things that we're going to start off with is just talking about, Manish, about what you're really passionate about. What was the inspiration for you for starting Reltio back in 2011?
Deanne Branham (00:59):
And you can't be on mute.
Manish Sood (01:02):
Oh, sorry about that. Thank you for having me. Thanks, Chris, for facilitating this and Deanne, for driving this. To go back to your question about what I'm passionate about; data, data, and data. And in 2011 when I started Reltio, there were three key secular trends that we were starting to see emerging out of the landscape. In the enterprise, the number of applications was only going to grow.
Manish Sood (01:35):
And just to give you a simple statistic around that. When I started my career in Master Data Management back in the early 2000s, when we work with large enterprise customers. The upper end of complexity used to be half a dozen systems that they needed to integrate data from, or maybe a dozen systems at worse. Now the same customers are coming back and saying, "300 plus systems." Even a business like Reltio, runs on 80 plus different applications that we use today. And this number of applications in any given enterprise is only going to grow from this point on.
Manish Sood (02:15):
The second area that really stood out was digital transformation. Over the course of the last 24 months, we've all seen the rapid acceleration in digital transformation and digital adoption. But in 2011, it was very clear that that was a secular trend that was going to pick up steam as we moved forward.
Manish Sood (02:39):
And then the third area is cloud transformation. So in 2011, AWS was one of the main providers or the only provider. We decided that in order to solve this problem at scale, and make sure that we are not only scaling for one customer, but we could scale across multiple such customers, where the data would continue to grow, the number of applications or sources that we would have to integrate would continue to grow. To create an efficient backbone, public cloud was the best way through. And not only did we use it, but now we see our customers driving the adoption of public cloud infrastructure across their enterprise in a rapid, transformational manner. And those are the three secular wins that really gave us the insight that it was time for us to start working on Reltio as a software as a service capability built on the public cloud, available across multiple geographies, so that we could provide it as a capability to our customers.
Deanne Branham (03:44):
And what's really exciting about what you just said, was that you had the foresight to think that the cloud was the way to go. I know that's why a lot of [Reltians 00:03:53] are so excited to be here because that was already seated as the birthplace of Reltio. So for that, we're really proud that you were able to have that foresight in it. And it's great that we can take advantage of that.
Deanne Branham (04:08):
And so why we're talking about that, one of the questions that keeps coming up is around roadmaps. And so while a product roadmap often can be deemed maybe sensitive and typically not shared, I would love to really hear about some of the things in the pipeline, if possible. Like any type of new features or functionality, data services just a general overview, and then we can dig into some of the details.
Manish Sood (04:31):
Deanne, I can talk about some of the thematic things that we look at when we start to define our long-term strategy and how we need to influence our roadmap, and then convert it into the lower level feature functions that we need to move forward with. At the heart of what we do, if you think about the various concentric circles, the core set of capabilities are built around entity resolution or the ability to take records from multiple sources and create a unified ID around those records so that we can have a skeletal structure that we can start with. And this is, whether it is person information, organization information, product information, location information, or any such variants. When you think about suppliers, or when you think about patients, when you think about let's say assets, it could be a combination of these four basic things. But the core concept is take data in from multiple sources, create a universal ID for those, so that you can start to have a skeletal structure on which you will bring on more attribution.
Manish Sood (05:42):
Which takes us into the next layer, which is the Master Data Management type of capability. Because once you have done the matching, then the next natural question is, how do we decide on survivorship? What is the best value for us to present to the downstream consumers? And that's where the capabilities of the operational values or other types of things that we do from a survivorship standpoint, or even cleansing and enrichment type of capabilities come into play.
Manish Sood (06:12):
And then we further extend the envelope to look at capabilities that will allow us to build deeper, richer views of information. Because Master Data Management as a discipline has been focused on taking overlapping sets of information from different systems, creating a unified view out of it and deciding on the survivorship. But then there are customers who in the past, they used to build these capabilities outside MDM. But now they're asking us if this data can be co-resident as augmented capabilities inside the capabilities that we provide, which is where if you have enrichment providers, like Dun & Bradstreet or Axesor or other types of sources, where you get access to 200 additional attributes, which may not need to be mastered, but they certainly need to be augmented. In this view, that's where even the analysts now are starting to talk about the augmented MDM construct. And back in 2011, we started with the vision that we would create these augmented or 360 degree view type of capabilities that would take in relationships, that would take in transaction interaction type of data, to create this unified view.
Manish Sood (07:32):
And then the last piece is driving consumption of this information through APIs, through analytic type of data warehouses that are available, or the consumption of this data in data science type of standard formats that you are starting to get more used to, and also the user experience that we provide on top of it. So those are sort of the four key themes that we look at.
Manish Sood (08:00):
And then we look at the capabilities as to how can we go deeper in entity resolution or what better features we can provide on Master Data Management or the 360 degree view creation, or the assembly of or the consumption of this data through the various interfaces that we create. And this is where as we move forward, the roadmap is going to be not only strengthening the capabilities in each one of these areas, but also look at simplification that we can offer. Because a lot of you on this call have had experience with previous generation MDM deployments or building it out on your own. It is a hard problem to solve. And this is where the simplification or investment in simplification will go a long way. So that every company of any size can benefit from the core concepts of bringing data together from siloed systems, and being able to use it as a strategic data asset across the entire company.
Manish Sood (09:10):
Your digital transformation depends on it. Your adoption of cloud platforms for data management depends on it. Your ability to be independent of application strongholds depends on it. Because you will be able to take your strategic data assets and use it in every application or business process that you're trying to create. So that's how we're thinking about the roadmap and the capabilities. I know it's a very high-level answer, but I'm happy to dig into any of the specific areas there.
Deanne Branham (09:46):
Well, in one of those areas that actually had posed a question from one of our participants was we offer that large number of native integrations with those external data and service providers such as Dun & Bradstreet, and [inaudible 00:09:58] and this really covers the topic for that data augmentation because what is the roadmap for extending this and in which direction? So if we're thinking about those type of connectivities, and augmenting that data, where do we see the product going in that way?
Manish Sood (10:12):
For a product roadmap, what we are looking at is how do we bring more such integrations into the mix? So today we provide a limited number of data sources or enrichment providers, how do we go expand that area where we have more such providers that you can easily access or bring in data from either as pre-integrated capabilities, or we give you the capability to go ahead and extend the API's to pull in data from those sources. And that's where as we move forward, you will see some simplification that we will bring to the integration part of the equation, where bringing data into Reltio becomes simpler, or broadcasting data out of Reltio becomes much easier for you through local type of capabilities that we are working on.
Manish Sood (11:14):
In addition to that, having a bigger roster or a more expansive roster of enrichment services that you can pull from. And we are looking at various capabilities there in order to partner with some of the other enrichment providers, or create the self-service capabilities that will help you there. But the goal is to expand that. And then the simplification of the entire experience of what you have to do in order to stand up a Reltio deployment. Can we make it simple enough so that it's reducing your time to deploy? Because every time you go into an MDM deployment, the amount of time it takes, we have to make sure that we can keep shrinking that timeframe for you. So that the next data domain that you want to go handle, you're able to do it in a much rapid turnaround time.
Deanne Branham (12:10):
And that's a big focus for us. That time devalue and ensuring that whatever we can do from a self-service or a prebuilt connectivity, then that's going to be a great feature for our customers. And so also, one of the questions from the customers was really in respect to progressive stitching of data. So we might want to define that for some of the other customers and participants that are out there. But for progressive stitching of data, where are we going with that in terms for other connectors, data governance, data quality, even in respect to the dashboard.
Manish Sood (12:45):
Deanne, progressive stitching is a construct that is core to our fundamental thinking in terms of how you should handle the different types of entities that you're creating inside Reltio. For example, when we start a Reltio implementation, there is no need for you to define a physical data model that will be true or hold for the next two, three or five-year type of time horizon. Because the capabilities are defined in a manner where if you see a need for additional attribution, you can easily go in and add that without having to redefine or redesign the entire logical model that you put together inside Reltio. It's a canonical representation. It's a logical representation that you can keep extending as you move forward.
Manish Sood (13:42):
And that also gives us the ability to think about the progressive stitching type of a construct, which is nothing else but start with a skinny attribution list. Then as you expand your footprint, you can add more attributes as you move along. This can be true based on how you're expanding the scope of your deployment to house more attribution details, or new relationships that you want to onboard or new transactions and interactions that you want to bring in. But at the same time, it could also be tied to the quick wins that you need to score because the first step in this process can be that you establish a universal ID by just bringing in the matching attributes that you need to stitch together the information. Then you add more attribution to that mix. Then you go to the enrichment providers like Dun & Bradstreet and pull in additional attributes that are not needed for mastering, but are needed for reference inside this construct.
Manish Sood (14:47):
And that's where the progressive stitching helps because you can... As you are onboarding different data sources, you can keep expanding the scope of the information that will be stitched together for any given entity profile. This gives you a lot of flexibility, and it also allows you to address the 360 degree view concepts without boiling the ocean on day one.
Deanne Branham (15:12):
Which is so important, right? Because we need our customers to be able to get that value right away. And that phased in approach and having the flexibility within the platform from day one to be able to add that attribution with these, and to have that dynamic survivorship is really key to supporting that progressive stitching, which is kind of been a new term that's coming out from the analysts lately. And so it's really great to see that that was a forethought, back when this was actually formed as a product. So again, just another feature that I know, I'm proud of that we are really in line with where the market is going on that aspect.
Deanne Branham (15:52):
So now, let's change topics a little bit because we've had some questions come in around customer data platform. And because it seems nowadays that the hype is with the customer data platform, and people are often confused with MDM. And the truth is that they do share a lot in common, right? Data integration, data quality, data stewardship, and governance and things like that. MDM is really mature in that area. But CDPs are working to catch up in that. And then from the CDP side, you have the segmentation, the activation and the analytics, which is really where the strong suits for the CDP are, but MDM is catching up there in that area. So how do you see the current positioning of Reltio in the space and its evolution?
Manish Sood (16:36):
So Reltio, is focused on the multi domain MDM, and this means that we can handle any type of entity, whether it is the B2B customer record, or the product information, or the location type of data that you're bringing in. In some cases, customers are also using us if you think about some of the other verticals that we have established our footprint in. For managing policy type of information in insurance, for managing patient type of information in healthcare. These are the various domains that we can handle very easily with the flexible capabilities that we have, which allows us to solve for problems that are beyond the scope of marketing. And this is where there is a little bit of intersection between the CDP and the Reltio type of capabilities, where CDP platforms are focused on taking information for the person that you market to, and bring that information together because the core function that they're trying to serve is the activation of that audience in various marketing platforms downstream.
Manish Sood (17:53):
And these marketing platforms could range from social apps, where you need to surface the information or marketing automation type of applications where you need to surface the information, versus the way in which customers are thinking about this landscape where both of these capabilities are needed. I'll take an example of a retail customer in the apparel business. They have multiple CDPs that they use across different geographies, where they have markets in Japan, where they need to drive marketing in Japan through a specific set of applications that are only available in Japan. Then they have markets in China where they have the super apps that they need to communicate with from a marketing audience segmentation and activation perspective. And then they have the rest of the world where they have a marketing stack, which is somewhat different from the other markets that I just described.
Manish Sood (18:57):
In this case, they have three different CDPs that they use because CDPs are tailored for those specific markets for handling the activation of person information. But there is one single customer information hub, which is Reltio which is feeding all of these marketing needs and seeding the data in those CDP platforms for activation.
Manish Sood (19:23):
And as we move forward, one of the things that I foresee happening in this space is that the consolidation of data, unification of data across multiple touchpoints which span or go beyond marketing will continue to persist inside the Reltio type of foundations. Reltio type of foundations will feed the single source of truth information to these downstream CDP type of platforms, or marketing automation type of platforms because they're one set of recipients for the information that needs to be used in the marketing context. But when you have to develop your customer experience, omni channel experience where you need access to information in low millisecond type of response times, that's where the aggregated unified view available inside Reltio is going to be the key single source of truth that you're going to tap into. If you have a fulfillment process, you're going to tap into that. If you have a call center support process, you're going to tap into that. And that's where the capabilities or the foundational strength of why the data has to come from the Reltio type of single source of truth capabilities is going to become more important.
Deanne Branham (20:43):
Exactly because that CDP is just one use case, whereas Reltio can support multiple use cases across multiple lines of businesses. And the key there is sharing that common master data so that we can trust the information whether it's coming out of a CDP, or a CRM or fulfillment center. So great point.
Deanne Branham (21:02):
And by the way, thanks for adding in the implementation example because that was actually one of the questions of where do you see this type of solution being implemented in? And it is one of the use cases that we have for being utilized by our customer. So great foresight there as well.
Deanne Branham (21:20):
So the next question that I'm going to go to is really about where do you see the market of MDM in three to five years, and I'm asking this because we're really seeing a flip. The traditional MDM, the on-premise, it was very disciplined in its manner in the way that it was going forward. And now we are seeing a lot of the analysts bringing about things like augmented data management and progressive stitching. So what's your vision for the market in the next three to five years?
Manish Sood (21:50):
Well, before I answer that question. One of the things having been in the space for a long time. If you look at the secular trends that I talked about. The number of systems and sources is going to increase, it will continue to increase at a rapid pace, which then creates the need for a single source of truth. And the evolution of MDM as a concept that was initially used to feed data warehouses. Now, this concept of what I would call cold data that is important for your business because you're driving multiple business outcomes out of this core data set, that has to be provided for by a platform like Reltio that sits in the cloud, is a data plane that is independent of applications. Because the number of applications that you will have coming in the enterprise, or being phased out of the enterprise, that speed and pace is going to grow. But the data is the continuum, the core data is the continuum that you have to keep moving forward with because that drives the business processes that you're enabling, whether it is quote-to-cash process. Whether it is customer experience type of initiatives, digital experiences on your website, or e-commerce site that you're building, or the mobile apps that you're rolling out, you will need data as the fluid assets that you can plug into any and every of those experiences.
Manish Sood (23:23):
And that's where having that core data asset as a 24/7, always on, always available asset is going to be extremely important. The cloud becomes a perfect vehicle for that because your digital experiences are going to sit in some cloud or the other. They are going to be outside the perimeter of your four walls. You will have edge applications that you need to communicate with.
Manish Sood (23:49):
If you go back 20 years, everything used to be within the four walls of your enterprise. Now, most of the commerce is shifting towards being outside the four walls. And that's where you have to be prepared with this data asset, the single source of truth capabilities to be available in that manner. And that's the transition that we will see where in the next five to 10 years, I foresee that data plane will be independent of the application plane. And every application, every business process will need access to this data. They will contribute into this core data assets, but they will also consume out of this core data asset. And we have to make sure that our capabilities are ready for that kind of a transformation that is clearly visible and taking place in the enterprise. And we are there to support our customers through that kind of a transformational change.
Deanne Branham (24:51):
You made some really great points there specifically for people to think about, if these are the types of issues that they're going to foresee as well. And so based upon that, you're having a lot of conversations with executives. Can you share with us a little bit of what you're hearing is really top of mind for them when it comes to their data?
Manish Sood (25:14):
Well, this is the first time in my career where I've spent a lot of time in data management, as you have, Deanne. The data conversation has gone from the basement level to the C-suite level. Every company now at the executive leadership level is talking about how strategic and important is data for their business. Why is that? That is because it is now the single biggest friction point for every enterprise.
Manish Sood (25:49):
It goes back to the State of the Union in terms of the number of applications that they're struggling with, the weight of friction between those different applications that they're struggling with. And they have to solve that problem by making data have fluid acid across these different touch points. And that's where the conversations that we are having the various chief data officers, CIOs, business owners, on the sales and marketing front, or the customer experience front. They are all acknowledging and saying that the siloed data is the biggest friction point and they need to eliminate silos.
Manish Sood (26:31):
The converse of that is that you can't really eliminate every silo because it's not like you're going to sunset your CRM application. That's not going to happen, you're not going to sunset your ERP application, you need those applications to complete business processes. So instead of eliminating data silos, you have to unify the information from those data silos and make it available as an asset that every application can tap into, and every business process can tap into. And that's the strong signal as well as the content of the conversation that we are having over the C-suite level leaders across the entire enterprise landscape.
Deanne Branham (27:19):
And in that same topic of conversation then, what advice would you give to those who are really looking to convince their senior executives of the benefits of MDM specifically because now that they're really ripe for those types of conversations, and they're really open to them? How would they position this and specifically in terms of value?
Manish Sood (27:41):
It's a really interesting question. And something that we, as a team at Reltio have discussions about all the time as well. As well as discussing the same topic with the customers. The data management professionals, inherently understand that there is benefit, and value in having data that is of better quality, better consistency because it will impact multiple business outcomes. But in order for you to bring the rest of your organization along for the journey, you have to start tying it to the business outcomes that you can try. And these business outcomes can be as simple as we will finally have a unified ID that you will be able to use, as the customer traverses different parts of the landscape that you're enabling for them. And you will be able to see the entire journey in a unified manner. The value of retaining a customer and expanding with the customer, versus having to go and acquire a new customer. If we can look at those types of ROI metrics, and then tie the foundational things that we are doing from a data perspective into those types of business outcomes, that would be the starting point.
Manish Sood (29:03):
And this is in no way means our form to say that that is the only outcome because we all know that it drives multiple business outcomes. For example, one of the customers that we work with, they do their territory planning based on the data that is coming out of Reltio. They do their incentive compensation planning based on the data that comes out of Reltio. They do their product registrations through their website directly on top of the API that comes from Reltio. They also provide this information as a real-time update into their CRM system so that they can have better processes. But how do we take each one of these processes and ascribe a value to those so that we are able to quantify the return or the ROI for the business in those aspects? And that's where all of us across the industry have to get better at anchoring into those business value, positive business outcomes type of orientation. And that is how we will be able to educate and bring the rest of the organization along with us for the MDM journey.
Deanne Branham (30:14):
And I think that that's also one of the areas where our customer success managers are focusing on. How can they help communicate that to our customers, and even to prospects so that they can get the most value out of the platform?
Manish Sood (30:28):
And this is a journey where we are more than happy and willing to partner with our customers to make sure that we are hand holding them through the process. If you need our team to help you build that argument, we will help you there. So please reach out. Please tell us where you need help, and we'll jump in and work with you.
Deanne Branham (30:53):
So now I'm going to switch gears a little bit because I think it's really interesting that we talk about the free version of MDM that we released to the market earlier this year. It was really unprecedent. And from your perspective, what really drove you to help in making that decision that MDM should be free?
Manish Sood (31:16):
The perception around MDM, MDM is hard, MDM is complex, MDM is going to take a long time for us to get up and running. And it is such an expensive exercise that we can't afford it. We want to bring MDM, or the concept of MDM to the masses, and making sure that we can also illustrate along with that, that it is simple, it is straightforward, it is easy to get up and running, drove the thought process that the platform that we have created over the last 10 years. How can we bring that to the market in a manner where some of the most common use cases can be front and center, visible and easily solvable for our customers?
Manish Sood (32:06):
So that is why our first step in that direction was to look at person data as a use case that we see across many of our existing deployments, as well as prospects that we talked to. And we decided that we would launch a simplified version of it, which is on the same platform that we have from Reltio. But at the same time, it's packaged up for ease of use and simplicity of adoption, so that you can get up and running and started with the deployment, without even having to pay a dollar to Reltio. So once you like the capabilities, then you can always grow your footprint from there and make use of other domains that you can solve for, or larger volumes of data that you can bring into Reltio because it's the same platform with the elasticity of the cloud attached at the hip with it.
Deanne Branham (33:06):
Yup. And it's been extremely successful. And so we're really grateful that customers have taken advantage of this. And hopefully, it's really provided a lot of value in making sure that their data is in the shape that it needs to be used throughout the organization. So-
Manish Sood (33:21):
And it's great to see the uptake of this offering. Since the time we launched it at the beginning of the year, we have more than 400 registrations for the capability where customers are logging in and starting to use the capabilities on their own.
Deanne Branham (33:40):
Yup. And oh, looks like we had a question come in from the chat a couple of them. I'm going to start off with the last one that just came in, which was, "Some companies have taken a crowdsource approach to MDM and offering that to their customers to improve their own environments, any thoughts or plans to do something similar via Reltio?"
Manish Sood (33:59):
So the crowdsource approach that I've seen thus far being very successful is I'll give you an example one of our customers, they buy a lot of third party data sources in order to enhance or combine the information with their existing sources of information. But what they typically find is that most of the third party data sources lag behind in what is really happening on the ground in terms of the information that is latest and greatest. Because the data collection process for even those third party enrichment providers takes a little bit of time. They will get access to the information, they will assemble it, they will then clean it up, bring it back to you as an enriched data asset that you can combine with you.
Manish Sood (34:49):
In the meantime, your sales team or field teams are visiting the customer in the field and they get access to some of the information right then and there because this is a life sciences example where in some of the underserved markets like Africa, they know that the doctor no longer works there. So they are able to capture that information in the field, and provide it as a contribution into the Reltio data set. So that the time that it takes for them to gather that field level information and assemble it into a cohesive view that can then be shared with the rest of the organization is much shorter.
Manish Sood (35:33):
And that's how they're able to apply the concept of crowdsourcing in a controlled manner, through the types of capabilities that we have rolled out with them, where their field force is gathering that intel. And putting that into Reltio as a contribution that is then processed through a workflow process and brought up as the clean set of data to share with the rest of the organization. And in this case, there are more than 6,000 field personnel that are gathering that kind of an information almost on a daily basis and providing it back.
Deanne Branham (36:11):
So that's really interesting, specifically the points that you brought about with the enrichment, having that little lag and having that crowdsourcing approach that they just implemented, to be able to keep that data up to speed. So then, in that aspect, it really becomes part of the company itself to be able to open up into that crowdsourcing of their own data as part of that. And with the controls that you can put in place through security, I think that's something maybe that a lot of companies should be considering to keep their data [crosstalk 00:36:42].
Manish Sood (36:42):
Survivorship can be controlled. The contributions, who has rights to contribute, who doesn't have rights to contribute can be controlled. The governance flows can be controlled around that data. So there are lots of flexible capabilities that allow you to now put more eyeballs on the data. And from the very beginning of Reltio, our belief has been that more eyeballs we can get on the data, or more people we can get using the data, drives better quality of information. It's a closed loop. If you keep it under the covers, don't expose it to anybody, you will get less quality. But the more you expose the information, the more you plug it into different systems and more users that you give access to, the better the quality gets because that is where the crowdsourcing effect comes into play.
Deanne Branham (37:36):
And not only the better quality that you get, we all understand that master data, the value is in its consumption to begin with. So if you're not consuming that and utilizing it into your business process, then you're not leveraging the value that you can to the most extent that it [crosstalk 00:37:55].
Manish Sood (37:55):
In fact, you make a great point, Deanne. As a measure of value, we all should be measuring the consumption of this data through different endpoints, through different audiences as a measure of success. Because we can clean data all day long, we can unify it all day long. But if we can't drive consumption and use of that data, then it is not a strategic asset.
Deanne Branham (38:24):
Yup, exactly. And based upon what you said that all of these executives top of mind right now is that data and that consumption of data, that is something that everyone should be considering to be part of, "Where am I going to get value? Where am I going to drive efficiencies? And where am I going to get the quality that I need out of my business processes that I have?" So great points that you made there.
Deanne Branham (38:50):
There is one other question here on the chat. And it's really again back on that roadmap. A question about data governance and data quality. So here is in the improvement areas in that, that they're asking you about from a product standpoint, based on some of the things that we've just talked about. It sounds like that not only can this be a product roadmap question, but even a user roadmap question from a crowd source, but from a product, where do you see data quality and data governance coming within Reltio?
Manish Sood (39:20):
Data quality and data governance are core to how we want to progress the roadmap. One of the areas that we have strongly believed in from the very beginning is more of a philosophy that we adhere to, which is that you should be able to bring in data into Reltio from multiple sources. And then you should be able to assess and govern the quality of data based on the information that you're aggregating. This will give you more control over which parts of the data you need to share downstream, which ones you need to further improve on before you can open the gates to share it downstream.
Manish Sood (40:03):
And the next step in our evolution that we are working on right now is to assemble the surfacing of data quality anomalies directly inside the Reltio user interface, so that you don't have to wait to figure it out separately. As you bring in and assemble the information inside Reltio, we should be able to automatically point out where the deficiencies or the gaps are, so that you can then segment it in a manner that you can assign different people from a governance standpoint to work on those gaps or addressing those gaps. And this is something that we are in the design cycles with some of our partners. If you're working on some of the data quality type of work, please reach out. And we'll be happy to partner with you and share some of the early work that we are doing here, so that we can bring it to life for you and your use cases as well.
Deanne Branham (41:07):
That's a great request. I think that the more feedback that we get, and validation from the people that are actually using it, as we all know, that's what we want for our product. So another question came in, a couple two more questions. And we want to know the roadmap for Reltio's to support real-time syndication to streaming platforms like Kafka.
Manish Sood (41:31):
Making sure that we can make our data available through multiple interfaces and to downstream systems. So far, we're focused on some of the cloud native type of streaming message queue type of capabilities. For example, in AWS, we have the SQS, SNS capabilities. In GCP, we have the Pub/Sub capabilities. In Azure, we support the message Bus that Azure provides, so that we can stream data directly into it as a destination.
Manish Sood (42:06):
And moving forward, we are looking at the more prevalent and well-adapted type of capabilities like Kafka that we can provide as supported destinations that we will add support for. If you have immediate needs, our team has worked on what our solution or design pattern is that you can use today in the near-term that our experts are happy to share with you. I think, Chris, you have it on the community as well. So making sure that we can point our customers today to that, as well as a part of the roadmap, having that simple Direct Connect to Kafka is something that is on our roadmap, and we're working towards it. I don't have the specific timeline, but that is definitely a target for us.
Deanne Branham (42:57):
And I'm sure that they're just happy to hear that we're even thinking about it. So Kafka, Kafka is like tomato, tomato? I'm just wondering if that's what it was like. Anyway, there was one last question on the chat and again, another roadmap type of question. And it says, "We need flexibility in choosing what changes should be published based on certain attributes." I'm thinking really what they're saying here is conditional survivorship if I had to guess, based upon a value of one field.
Manish Sood (43:29):
Yeah, there are some new capabilities that we have rolled out into our streaming functionality. We are starting to support the full payload so that you don't have to make a GET API call once you pick up the message from the message queue. And there are also some filtering capabilities that we have added and enhanced, so we should make sure that we are able to share some of those details and get the additional feedback on how we should further continue to improve those capabilities from a streaming standpoint.
Deanne Branham (44:06):
Okay. Yup. I think I read that as a separate question. So thank you for picking up on that and answering it properly. I really appreciate that.
Deanne Branham (44:13):
Okay, so looks like I don't see any additional questions here in the chat. So Chris, do you want to wrap this up? Or how do you want to go about this?
Chris Detzel (44:29):
So Manish, this was great. I love kind of these great answers, but just how people just throw these questions at you. And you just boom, got it. And, Deanne, thanks so much for facilitating today. I loved it.
Chris Detzel (44:44):
We do have time for a question or two. So Deanne, we have one in the chat. It is, "Where can we get details on the streaming design patterns, and also enhanced filtering?"
Manish Sood (44:57):
Mark, we'll follow up on that and we'll have this posted on the community. And we'll also reach out to you to make sure that we can share the information with you.
Chris Detzel (45:07):
Good. If there are no other questions, this will be recorded and is recorded right now. And there is a webinar, [Venky 00:45:18]. I'll post that hopefully Monday or Tuesday. And so if there are no other questions, I'm just going to wrap up here.
Chris Detzel (45:26):
Thanks, everyone. Please go to community.reltio.com/events to sign up for the next couple of webinars. The next two are the one on Kafka that we just mentioned. Kafka, I'm not sure how you say that, Deanne. But I was saying Kafka, and then you said Kafka and then Manish said Kafka [crosstalk 00:45:47].
Deanne Branham (45:47):
It's a Midwest, Southern accent.
Chris Detzel (45:51):
Yeah. And then next week actually, we will be talking about matching and merging, I think, so that one should be really good as well. So thank you, everyone, for coming. And I'm just going to go ahead and wrap it up. And we'll see you on the community, and see you next week on the next webinar.
Chris Detzel (46:09):
Thank you, everyone. Thanks Manish and Deanne.
Manish Sood (46:11):
Thank you, everyone.
Deanne Branham (46:11):
See you on the community.
Chris Detzel (46:14):
Yes. I'm going to stay on for just a minute or two, but just in case. Every now and then, you'll get a question or two.
Chris Detzel (46:23):
That was great, Manish. Really spot on and [crosstalk 00:46:27].
Manish Sood (46:27):
Thank you. Thanks for setting it up. I really enjoyed it.
Chris Detzel (46:31):
Yeah, me too. I'm going to have to get Venky to do one of these.
Manish Sood (46:35):
There you go.
Speaker 4 (46:36):
Sign me up.
Chris Detzel (46:39):
All right. September and October. All right, everyone. I'm going to go ahead and stop it. And thanks, everyone.
Manish Sood (46:46):
Speaker 4 (46:46):
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