Cloud Computing Köln - Seite 2277 von 7049 - Neues zu Cloud Computing, Internet of Things und Technologien

For many businesses, business intelligence (BI) consists of data visualizations and dashboards. The problem is that dashboards are not the answer to every data need. Many users today are looking for rich data-experiences that are immediately accessible and seamlessly part of their day to day work. Surfacing insights in collaboration apps like Google Chat and Slack, infusing data into productivity apps like Google Docs or Slides, or triggering auto generated business processes such as updating paid media bids or using AI-powered bots are just a few of the ways information can be provided, integrated and operationalized.For these reasons, businesses need to think about delivering data and analytics to workers in a way that makes it meaningful and immediately productive. We call this moving beyond BI. Reflecting everyday data experiencesOn a daily basis, in almost everything we do, we use data analytics without being aware of it. When we sit down to watch our favorite streaming service, navigate traffic, shop online, work out using a smart watch, we rely on integrated data insights in our day-to-day activities.These experiences have influenced what we expect from data systems at work, and why businesses need a new approach for delivering data and analytics on the job.The Looker MarketplaceThe Looker platform helps businesses realize this new approach and move beyond BI by providing tailored off-the-shelf products or Looker Blocks™ which are ready for deployment. These data-driven experiences are focused on the needs of the business or department. These accelerators support:Modern BI & analytics: Democratize easy access to timely and trustworthy data enabling people to make better, faster, more confident data-driven decisions every day. Integrated insights: Infuse relevant information into the tools and products people already use, enhancing the experience of those tools and making teams more effective. Without even thinking about it, everyone at the company is making data-informed decisions.Data-driven workflows: Super-charge operational workflows with complete, near-real time data to optimize business processes. This allows companies to save time and money by putting their data to work in every part of their business.Custom applications: Create purpose-built tools to deliver data in an experience tailored to the job. By building the exact experiences people need, you can make your employees, customers and partners more effective and more efficient.The Looker Marketplace helps you find content to either deploy data-experiences into your Looker instance or to build new data experiences faster by taking building blocks from the marketplace and extending them in a reusable fashion.Moving Beyond BI with SolutionsAn example of such a solution is the Contact Center AI (CCAI) Insights, that you can explore in the Looker Marketplace.With CCAI Insights, Looker can leverage the power of AI to converse naturally with customers and resolve basic issues quickly, as well as improve future experiences and drive long-term customer satisfaction by measuring and analyzing customer interactions while improving overall efficiency. Using Google’s machine learning capabilities and Looker Blocks, you can easily identify resolutions that have worked well, and use data actions to automate contact center operations based on new insights.Another example is the Google Cloud Cost Management solution. Effective cloud cost management is important for reasons beyond cost control. A good cloud cost management solution provides you the ability to reduce waste and predictably forecast both costs and resource needs.Leveraging the Cloud Cost Management Block is a simple way to understand your cloud spend without data movement — your existing billing and platform utilization data remains in existing siloed cloud data warehouse platforms. Looker connects directly to the billing data in each respective cloud data warehouse, providing a consolidated reporting view of cloud spend across Google Cloud, AWS and Azure. You can see all your spend information in a single dashboard that can contain mutual filters such as date, skill teams, application name(s), and more. You can activate alerting notifications and schedule reports to be sent automatically via email, a messaging service, and to other destinations. This means that on day one, you’ll have real-time, accurate multi-cloud cost reporting.Build new data experiences and upload to the Looker MarketplaceDevelopers and Looker partners can create new content and publish it in the Looker Marketplace. The easiest way for you to get started is to visit the Looker Developer Portal and discover all the types of content you can build with our platform capabilities.From Nov. 9 – 11th, Looker is hosting its annual conference JOIN, where we’ll be showing how to:Build data experiences at the speed of businessAccelerate the business value with marketplace contentGrow your business with reusable analytics componentsThere is no cost to attend JOIN. Register here and learn how Looker helps organizations build and deliver custom data-driven experiences that goes beyond just reports and dashboards, scales and grows with your business, allows developers to build innovative data products faster, and ensures data reaches everyone.
Quelle: Google Cloud Platform

9. November 2021

da Agency

Going beyond the dashboard paradigm with Looker Components

These days, it’s no secret that traditional business intelligence (BI) is evolving. With the rise of embedded analytics, enterprises everywhere are beginning to seek out opportunities to augment their day-to-day workflows with real-time insights. These data-augmented workflows are what Looker calls “data experiences”. Some of these experiences are easy to identify and implement: maybe it’s as simple as embedding an analytics dashboard within an existing SaaS application, like Salesforce or Zendesk. Or a company may decide to monetize their analytics by embedding a Looker dashboard inside their own product, enhancing the value of the product for users.But some of these opportunities may come from embedding data even deeper into applications, so that insights are available the moment a knowledge worker needs to make a decision. These deeper types of experiences are where we think Looker truly shines as a platform.Looker’s approach to embedded analytics is to make it easier for our customers to continue to build, adapt, and extend their own data experiences by integrating data even deeper into their operational workflows. We also want to make it possible for more of our customers to build these custom data experiences by creating sensible but flexible abstractions for developers.Analytics as Reusable ComponentsLooker dashboards are integral to the product, providing a powerful interface to view, interact with, and dive deeper into your data. But data consumption via dashboards is really just one use case for data. There are other data experiences available on the Looker platform, such as exploration, navigation, data curation, and even taking action on your data that we can make easier for our customers to build.Historically, building these experiences had been challenging, primarily because most of these experiences required a fully custom font-end to be built from the ground up. And sometimes, the amount of time and resources a custom front-end on our API is prohibitive.With Looker Components, we hope to introduce a third way to embed data that’s easier to build than a fully-custom front-end on Looker’s API, but offers more flexibility than a monolithic iframe embedded dashboard. And the way we plan to do this is by identifying and exposing reusable patterns in our dashboards themselves. Dashboards as a CompositionWhat if we looked at dashboards not as a monolithic feature, but as a composition of different components and patterns, all of which work together to create a unified experience?Looker’s dashboards are primarily a composition of three components:Visualizations, which display queries from the database in a form that can be consumed by the userFilters, which provide an interface to interact with and manipulate the existing queries on the dashboardLayout, which enables a user to manipulate the size of the visualizations on the dashboardWhat if we made it possible for a developer to pull these powerful patterns out of their Looker dashboards and use them in their own applications?Introducing: Visualization ComponentsToday, we are proud to announce Looker visualization components – a new way to surface data from Looker in your application.Looker visualization components are an open source package that provides three high-level components to make it easy to build data experiences in any React application:Query: handles the data fetching and loads the response into contextVisualization: accepts the data returned by Query and utilizes configuration adapters to render the appropriately customized chart on a page.QueryFormatter: performs light data cleanup and normalization for the purpose of passing query data to a custom visualization.Using Looker’s SDK, our standard library of charts can be rendered through the use of the Query and Visualization components to request query data and parse the response through our visualization adapters. To build custom visualization that extends our out-of-the-box functionality, developers can use the QueryFormatter component to clean up Looker’s query response before sending the formatted data to a custom visualization that they would build.Unlike other methods of embedding that Looker offers, visualization components do not require an iframe to present, rendering instead on the client-side of an application. Developers interested in building custom front-end experiences with Looker no longer need to worry about choosing a vis library or worry about learning a new vis framework.Starting today our package will provide a small selection of visualizations for our customers to begin using. Our initial offering includes Scatter, Line, Area, Sparkline, and Table. These visualizations are an entirely separate visualization layer than the one that’s available within the core Looker product, so while they are compatible with many of the options in Looker’s visualization menu, we don’t have full parity with Looker’s native visualizations yet. These components have been a labor of love for our team for quite some time. We can’t wait to see how you decide to use visualization components in your applications on Looker.Introducing: Filter ComponentsAlong with meaningful improvements to make it possible for developers to declare individual visualizations outside of Looker, we’ve also made it possible to embed and use Looker dashboard filters in any application or extension on Looker. A large part of what makes Looker’s dashboard experience so powerful is the ability to filter data using our 12 different types of filters. Using our filter experience, dashboard users have the ability to build complex queries with Looker in a straightforward and streamlined way.Currently, the best way to use our Filter Components is within an embedded Looker Dashboard, but in the near future, we plan to introduce patterns that make it easy to combine Filter Components with our Vis Components. Using Filter Components with Embedded DashboardsUsing Looker’s embed SDK, developers can declare a filter component in their application and pass in a relevant dashboard ID to the component. The component will then render the fields displayed from the dashboard. One of the uniquely defining features of Looker’s filter components is that they are synced to a live Looker dashboard. That means, when you declare filter components in your application and link them to a Looker dashboard, any changes made to the filters on the Looker dashboard are automatically reflected in the filter components in your custom application. This is great for application developers because they get to declare filters in their embedded application and then offload the management to their SMEs, the analysts. They don’t have to spend their time making manual updates or changes to the filter experience.Looker’s filter components are also great for analysts because we get to bring them closer to product development. Rather than waiting for a developer to implement a change to a filter, an analyst can implement that change in a Looker dashboard and watch that be reflected in their custom application. This is part of our initiative to give analysts, the SMEs, more control over embedded applications created with Looker. Now, every data experience built on Looker can benefit from the powerful, flexible, and beautiful user experience that’s a defining feature of Looker’s dashboards. When we unlock the filtering experience for our embedded customers, we ultimately enhance the interaction with the data for all users of embedded applications on Looker.Building Compositions with ComponentsOur filter and visualization components are an exciting next step for the Looker platform, and make it possible to embed Looker data into a number of existing data experiences. We’re also excited by the possibility of our developer community choosing to build wholly bespoke experiences with our 150+ UI componentson Looker’s extension framework or within their own custom applications.The creativity that we can unlock by building entirely new compositions with Looker components is truly a next step in unlocking the value of composable analytics for the enterprise. To learn more about how using components can help your business grow through data experiences, watch this JOIN 2021 session.Related ArticleLooker lets you choose what works best for your dataEmbrace platform freedom with Looker. Learn about how we are expanding our features as a cloud platform to meet the unique needs of every…Read Article
Quelle: Google Cloud Platform