 Winston Edmondsson here, when you think big data services, you think CloudWik Technologies. I'm here with Manny Chabra of CloudWik Technologies. He's going to tell me a little bit about what he's here presenting at Hadoop Summit. Manny, thanks for being with us. No problem. Thanks a lot for interviewing us. My name is Manny Chabra. I am the presidency of the CloudWik Technologies. We are a Hadoop services company for the last three years participating in implementation and integration aspects of the Hadoop ecosystem in the enterprise world. And what we have seen is the prepondence of services which are required in the enterprises and we are developing those frameworks. And now we are releasing that for the outside of the Fortune 100 where we've seen most of the production services happening. And we're launching it for the medium enterprises. We're launching two kind of services. One is the managed services for clusters. It is to basically help you from the bare metal to deploy the clusters, manage the clusters, support 24% and kind of like run your day-to-day system administration tasks. The second part of the services which we have seen a lot happening is that offloading of the data from the data warehousing. You know, the acquisition of data at tarot datas or the green plums is very, very expensive. And what Hadoop has started becoming the lake, the data lake within the enterprises where you can take all the data which is sitting in the historical data which is sitting outside there is being ingested into Hadoop and then you can run some machine learning algorithms to find patterns in that one. And so there's a prepondence of the use cases which is very, very happening in the Fortune 100 and we think it is very, very applicable to enterprises outside the Fortune 100 in this area. So let's break that down a little bit. Tell me maybe a use case scenario. What type of business might come to you and prior to working with you, what might their system look like? I want to understand kind of where they were and then where you can help them progress to. Yeah, so if you see in the, especially the financial services, there are a lot of compliance and legal issue for them to handle the data for like historical for 10 years or so. And one of the challenge happens is there's so much of data sitting with them and it is not accessible right away. And a year by year they will basically have to go to buy tarot data or they had to buy oracle or the green plum spending millions of dollars in acquiring those new licenses because they had to maintain the data and the amount of data is increasing substantially. So we basically go in there and kind of help them in offloading that data at least the historical data from the enterprise data warehouse onto Hadoop. And that makes it cheaper. The cost comparisons are just beyond me. So you can practically have per terabyte acquisition cost on Hadoop with some in the range of $1,000. Whereas if you basically deploy on tarot data or green plum, you have to spend $100,000 per terabyte. And the tools with existing enterprise data warehouse are good for competition, but they're not that good for storage. So Hadoop can easily replace that storage part and leave the computational aspect onto the tarot data. While other applications are being on the Hadoop platform. So did I hear that right? In some situations, you're talking about one-one-hundredth of the cost? Yes. So immediately you're talking about just a cost benefit right off the bat. Before you even talk about potentially being able to extrapolate and benefit from the data just right off the bat, you're talking about saving lots of money. Lots of money. You can practically set up the clusters and provide services at just 30% of the yearly cost is maintenance. So if you have existing, you know, around let's say 200 terabyte and you have 10 licenses of tarot data or green plum, that cost will run you in millions of dollars, you know? So it's just basically offloading that to Hadoop. We'll basically save you a ton of money. And that's what we've seen, there's a lot of evidence which is happening in the financial services company like what we have done and implemented in Bank of America, JP Morgan Chase, American Express, a lot of these companies, same use cases coming again and again. Pretty incredible. So you take a business and now they are saving a lot of money. What's the next step? What are some of those additional benefits that you'll be able to offer? So once you basically have the data into the historical data, now just think about this thing. There is, this data was never available at one place any time in the history of the enterprise. So you have 10 years of historical data and you can run machine algorithms to find the patterns. And that patterns can basically give you such a historical premise to that that what has been actually happening in the business which is not available earlier. Now you can do whatever, because your data fabric is already there sitting on Hadoop. You can start syncing up other data sources onto Hadoop. You can take binary data from the main frames. You can take data from the other data enterprise data warehouses. And now you have one place of Data Lake is as it's called in the industry. And you can run with it. And you can present data whether you want to do data analytics on that or you want to do look at different patterns, fraud analysis, all of those things are available right at the one place. So you could argue in some respects that before now companies were flying blindly. They had no idea what was taking place. You're now able to use this data to let them actually understand what has been happening. What are the patterns, what are their customers and clients, what trends and patterns they can get from that? I, exactly. Because if earlier you know people who do analytics they would take one-tenth of the data and they'll have the one-tenth of data imported and they hear the answer from the one person out of that one-tenth of the data. So you practically were making these models and you're presuming that these models are correct on the businesses. You know, there's a lot of presumptions going on that okay, this is what it is coming from. But now you just have, just imagine that the one person doesn't contain the actual answer. The rest 99% contains the actual answer. So you were missing a lot of information. This is one scenario where Hadoop I think is going to be a sea change that's happening. And that's the start of the Hadoop. Practically all the tools once they become built in and you have the real-time streaming of the data coming to Hadoop and you have applications coming and now you can practically take that analysis and kind of do all kinds of different applications. So you might have some CIOs that are watching this and they think that what we're talking about sounds all well and good, but they're not very imaginative, they can't really grasp the true benefit. Is there any type of example of a trend that, not a specific company, but just something you can point to, a trend that was found or that was able to help a customer change the way they do business based on the information they've gathered from Big Data? Yeah, I mean, if you look at Hadoop as a service, Hadoop as a security service, which you've seen a lot happening in the financial services, earlier they were not able to collect all the log data from all the places where they have the systems into one place. And now they can grab all this data at one place and analyze the patterns. You can have the fraud patterns, you can have the information IP claims which basically going out and you can see all those patterns happening and those are not, one was not able to do that before. So that you will see a lot of these preponderance of evidence coming into the case. I mean, granted that they're two different worlds. One is the enterprise world which is basically has all the restrictions and everything and then there's one the Silicon Valley which has no legacy, they can come up with all these new models. But once you start with Hadoop, these convergence will start happening. That there is a requirement of these, what the new companies are doing, the use cases with the building in, you can start applying that to the enterprises and you can find a lot of uses in the enterprises. Now what we're talking about is it's not static. Things are changing every day and new services are coming online that you can really benefit these customers. Anything on the horizon that's exciting to you? I think the real, the next level I think is this real-time streaming. I think you've seen a lot of tools coming. There's a company called DataTorrent which is over here and then we have seen through the Twitter, the Storm and the Kafka platform, I think which is coming. So you practically can take all the analytics you've done. You can feed that into the mapping tables and as teamers you get the real streaming. You can practically go and see if the pattern matches. If the pattern matches then you can flag this for the fraud or any other kind of things. So those I think when you take all the learnings of the historical patterns and then apply the real-time is when you will see the real work being done. Pretty exciting stuff. Manny, what's the best way for people to get in touch with you? They can go to our website. They can check our website for all the use cases and everything and they can also send us email at salesascloudic.com and they can reach and we can provide the services and the use cases with them. Fantastic. Winston Edmonton for Studio B, checking out.