Data-driven product leader with a goal to make data analytics accessible and bring a user-centric approach to enterprise software.View the profile
About the talk
For many companies, going multi-cloud is a competitive advantage, and sometimes a necessity. Multi-cloud allows organizations to meet users where they are and expedite their transformation journey to deliver a compelling customer experience. Learn how to break down data silos in your environment and see how you can run analytics in a multi-cloud world.
Speaker: Emily Rapp
Google Cloud Next ’20: OnAir → https://goo.gle/next2020
Subscribe to the GCP Channel → https://goo.gle/GCP
product: BigQuery; fullname: Emily Rapp;
event: Google Cloud Next 2020; re_ty: Publish;
Hey everyone. Welcome to analytics in a multi-cloud world. I'm Emily Rapp product manager. We are facing a data 175 zettabytes zeros. 21 zeros of data in the world by 2025. Where is it coming from? We have cat videos server laws. Monitoring, there's retail data. We are thinking about eCommerce. It's a lot more than just that final transaction. It's every point on the cell cycle. Manufacturing, my washing machine is connect to the internet and therefore generating data. We have
all of this data at our fingertips, but we just can't quite get to it because we're living in this world of data silos. There's organizational separation, it Department are often centralized and they are separate from the central data Department. If there is one which right? Even then further separated into the business unit and those business units also has analysts data scientist working and trying to understand problems. It's fragmented, you have data originating from a bunch of different sources. It's all in different formats with
various levels of processing. This means that our analysts are data scientists are users. Are users are using too many tools. Have to get data from too many places and they're making too many copies. Why is it happening component is shown in one of the Gartner Cloud. Adoption surveys 81% of companies who were using more than one cloud provider. And so, that means that multi Cloud management is becoming actually it is a true challenge, it leaders, they want to be agile, flexible secure. An analyst and data scientists, the ones that are actually doing the
day-to-day work with it. We're just trying to help their organization make the right decision. and even if organizations, decide to have a centralized data approach we talked about earlier, there's still always going to be separate business units, subsidiaries partners multi-cloud, We need to solve for these macro challenges, So today we're introducing Bakery on me across clouds. You don't have to leave big Prairie your familiar interface. But now you can actually Reach Out Reach Out Across
The Silo Bakery on me is now in Elsa. And what's really cool is that it's powered by an toes, we don't have to be copying of data. As a data analyst, in the marketing department, Bakery Olney, enables me to use historical sales data in my upcoming marketing campaigns, using our orders data, we're going to validate the hypothesis that we should be focusing. Our marketing efforts Beyond just food and beverage our first query uses the hyperloglog approximation function to sort the Department's by number of orders. We are using a read-only external connection retail, read
to get the data from the orders, external table return, the department, sorted, by number of orders. And as we can see, all top 10 are either food or beverage this validates, our hypothesis that we should be focusing, our marketing efforts on this customer, segment, household, or personal care product purchases. Now, we need to build a list of IDs using our customer data set. The customer data has personal information, including name and zip code and we need that. However, we do have a d identified user ID field that we can use in our
campaigns. Our next query will build our audience segment buyers of household a personal care products. Since our canteens are regionalized, we only want customers from Oregon or Washington. We have a list of IDs that can be used in any marketing. Activation Channel. We want this data to be accessible to all marketers, not just the list. So I use our right connection to export, clear result to the marketing folder that they have access to. And that is how you can use Bakery on me for data-driven marketing activation. That was pretty cool. So let's
talk about multi Cloud analytics to your data. First, we have to break down those silos. Get you to getting inside faster. It's cost-efficient no moving or copying you just instantly query instantly get your results. With a consistent experience. It doesn't matter if your data is in or you can just use the same standards to equal the same Big Bill dashboard data. It's not just numbers, it's not just fight storage and some data center somewhere. It's the way that we can actually communicate. We can tell stories we can answer
questions. We want you to be able to have to actually work across those data files, that David, that was at your fingertips. Let's get closer to it. And we're able to do that because under the hood, please answer us. I think about big Prairie bigquery is the separation of storage and compute. What does that mean? It means you can scale up and say, hey sometimes, what? Things are going crazy, you may need a little bit more compute, in other cases, Maybe? We were thinking about how do we saw this dude? Asylum question,
but the challenge was we have to figure out how to get compute to the data. Even if that data is in another cloud. The bakery on me, we run the computer Buster's answers clusters, we have a secure connection because it's really critical. We think of that, single pane the control. Only the clear result actually passes through the big three routers and then our secure connection to the next region AWS or azure. That connection to bring the results but the cheapest has its choice for you. You can bring them back or you can do everything within
8 Bakery on. Me is a fully managed service. A question I hear is, oh, so I have to use my calls or my computer, we got that covered. We do need your storage and it's really critical that. You maintain the access control to that storage. With the Computer Resources, running locally, all of us on behind-the-scenes and you can just answer those questions. So how do we actually solve some of those business scenarios with a gray on me? This isn't funny. This is my old world up
until recently number when I joined a query I was the infamous marketing analytics as measurement specifically. How many people saw my God? It's a surprising hard question. And actually even harder, if it's actually think about figured out what's going on in my marketing campaign on my site. What impact do those two have on my sales? What's think about, how can we solve that problem, how can we see the impact? We could visualize. So you've been query, query, Google, analytics,
360, add data in Google cloud and then tap into your Ecommerce data and apps data that's on AWS. S3 liquor you can do the dashboard. So you or those Executives don't have to worry about. Can actually look at what the audience behavior is and purchasing and it's pretty amazing, what seeing something visually can do is like there's a spice, I'm building a dashboard data comes from all of the different places and more importantly, making sure that if you share that
dashboard with someone, they're not going to see something that they shouldn't. Challenging. A little bit deeper say something. I'm sure probably many of you are familiar with okay, my business teams. Do you need to use the app SmartThings and we need that data and it needs to be formatted and easy to get to and so did you end up running? Start the process, Los endo's crossbody, tailpipe lines. What happens if those pipelines go down? So, I actually seen it where? Instead of fixing the companies will sometimes just hire Consultants to respond to tickets. To answer the question, it's that
complicated. Bakery on me. It's not always just about the like getting using your existing were closed and how you can optimize them. You have to pay for some reason. Every app always ends up going into different S3 bucket with parquet file. Today you have the thousands of jobs that we talked about running and we're trying to do is build audience list and see if he files of your active users. Replace that with a single SQL query that any analyst can run. Let's think about how data scientist can actually use
the data from sales. But reach new audiences. Let's get started with Bakery on me in the bakery URI on Google Cloud. Choose a public Cloud region where your data is located and run your query, the same query, you would use to work with data that stored on gcp. The clearing a path to the other public cloud. And all of the computer is done within that public, Cloud region, the results are returned to the big query. Why? Or you can choose to export the results, directly back to your data storage on that. Public Cloud, which
means, there is no cost Cloud movement of results or data. You can start using bigquery on the right away. There's no need to do any formatting or transformation of your data Bakery on needs supports for Matt such as a burro CSV to Json or icy and Parkay you also don't need to move or copy your raw data out of the other public Cloud, do any cluster management or provision any resources, all computation occurs within big queries multi-tenant service which is running on the region where the data is currently located behind the scenes, Big Quarry. Quarry Engine is running on.
Our Aunt has clusters within the big Curry, managed service. We get the data from data stored within your account. Only once you authorize permission, we are your other public clouds. I am rolls. Those rules are tied to a bakery on a connection object. You can change Grant or revoke access at any time and the connection object can be shared to multiple users. Within that same project we maintain a secure connection to bring your clear results back to Google Cloud. Welcome to Bakery Olney. So we decide
which means think about coming in to storage and take those audience and do things like Ever had that experience where you buy something and you still see the ad over and over and over again and you're like, I bought that thing already stop wasting your ads on me. Now we actually saw that because we can tie that Commerce Ada to the ad talked to him in a safe and secure way. So let's recap embrace, the flexible multi Cloud analytics solution with bigquery on me.
We're going to break down, silos. Get straight to the getting inside part of data analytics, the fun part. Anyways, having a consistent experience across clouds. It doesn't matter where your data sets are, you should be able to use the standard sequel Bakery interface, right? Your queries filled your dashboard. It's all about taking that consistency and familiarity to accelerate the time to insights. You want to be able to pick up in the morning to check your phone, not have to worry about riding, a whole ton of different queries in
different tools before, you know, the state of your business. And all this is possible because of a mantis. Dremel was OK. Google, what powers Bakery? Anthos, is that next day? Thinking about gardener quote 81% of companies, probably actually more than that. I think about to have some Hardware business. And so by bringing the data to you, we bring the compute to where your data is. We were at the infrastructure don't worry about spending up cluster is
managing them, we got that you focus on driving the business, doing some really cool data science, Making the decisions you need to stay. Not worrying about how do I set this up and what type of wine should I run? And I have to hire a whole bunch of people to just answer tickets. Let's get started, get started with the Curry on me. Let's take it to the next level. Take your multi Cloud analytics strategy that you've built from a platform and it perspective and bring it to your data Bakery on me. So if you're interested,
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