We are pleased to share that the team from Phlyt, experts in cloud-native development, has joined Red Hat to enable us to help even more customers with digital transformation initiatives. Red Hat already equips customers across industries with the people, process, and technology needed for an era when every CIO is a cloud operator.
Quelle: CloudForms
There’s no one path to finding success as a Red Hatter. Red Hat Quality Engineer Dita Stehlikova, for instance, didn’t start out looking for a career in IT – but she fell in love with open source early on. Read her story!
Quelle: CloudForms
Red Hat is honored to be recognized by CRN for our innovation with Red Hat OpenShift and Red Hat Enterprise Linux (RHEL). The annual award program showcases innovative vendors in the IT channel across 47 different technology categories. Learn more.
Quelle: CloudForms
Many organizations use external identity providers like Google or Microsoft to manage authentication across their applications — and many may wish to bring this functionality to their cluster management, too. In Mirantis Kubernetes Engine 3.5.0, we’ve introduced support for external OpenID Connect (OIDC) providers to help you do just that. OIDC enables you to authenticate … Continued
Quelle: Mirantis
As digital transformation accelerates, the data available to organizations about their products, customers, and markets is growing exponentially. Turning this data into insights will be critical to innovating and growing. Furthermore, the capacity to make data-driven decisions must be pervasive in organizations, accessible to a broad range of employees, and simple enough to apply to day-to-day decisions as well as the most strategic. However, a major barrier to achieving this vision is a gap in access to the tools for analysis and building broad-based usage.Looker’s semantic model enables complex data to be simplified for end users with a curated catalog, pre-defined business metrics, and built-in transformation. We’ve always been platform first, and this is an expansion of that strategy. We are extending our investment here to power more data rich experiences and aim to provide access to the Looker model more directly in other tools. By bringing governed data directly to end users in tools they are already familiar with, this will democratize access to trusted data across organizations.Google Workspace is everything you need to get anything done, all in one place. Google Workspace includes all of the productivity apps you know and love—Gmail, Calendar, Drive, Docs, Sheets, Slides, Meet, and many more. Whether you’re returning to the office, working from home, on the frontlines with your mobile device, or connecting with customers, Google Workspace is the best way to create, communicate, and collaborate.Now, with the Connected Sheets integration with Looker, users can interactively explore data from Looker in a familiar, spreadsheet interface. The integration creates a live connection between Looker and Sheets, meaning that data is always up to date and access is secured based on the user exploring the data. Common tools like formulas, formatting, and charts make it easy to perform ad-hoc analysis. This integration will be available in preview by December 2021, with GA next year. You can sign up to hear when the Connected Sheets and Looker integration is available.And that’s not all. Looker dashboards are critical to keep teams focused on the metrics that matter. We will be releasing a Google Workspace Add-on that enables visuals from those dashboards to be embedded in Google Slides. Embedded visuals in Slides can be refreshed so that people are always seeing the latest data.Self-service business intelligence (BI) tools have also gained widespread adoption among business users, with a drag-and-drop, graphical user interface that makes exploring data easy. This flexibility is critical in democratizing analytics, but it also introduces risk that for the most important data may be duplicated or inconsistent definitions are introduced. With Looker’s upcoming Governed BI Connectors, we will give organizations the flexibility of self-service, while allowing users to leverage their governed, trusted data in those tools too. Users will be able to live connect from BI tools to Looker’s semantic model. From there, they can use the familiar self-service tool they are used to for analytics, even mashing up governed data with their own data. Connectors will be available for Google Data Studio, Tableau, and more. These connectors will be made available as they are ready in the coming year, with the full set being available in preview by the end of 2022. You can register to stay up to date on preview availability for Governed BI Connectors.With these new capabilities, everyone in an organization can be empowered to make more data-driven decisions, in whatever tool they are familiar with, all powered by consistent, trusted data. To learn more about Looker’s semantic model as well as these new capabilities, tune into our JOIN session discussing ‘What’s New for Data Modelers’.
Quelle: Google Cloud Platform
Data science can be applied to business problems to improve practices and help to strengthen customer satisfaction. In this blog, we address how the addition of Looker extends the value of your Google Cloud investments to help you understand your customer journey, unlock value from first-party data, and optimize existing cloud infrastructure. Data is a powerful tool While everyone doesn’t need to understand the nuts and bolts of data technologies, most people do care about the value data can create for them — how it can help them do their jobs better. Within the data space, we are seeing a trend of ongoing failure to make data accessible to “humans” – the industry still hasn’t figured out how to put data into the hands of people when and where they need it, how they need it. What if everyone in your organization could analyze data at scale, and make more-informed, fact-based decisions? Data and insights derived from data are valuable but only if your users see it. We think Looker helps solve that. Solutions tell a larger story of how it all fits together Across all verticals and industries, businesses benefit from knowing and understanding their customers better. Many business goals are to increase revenue by improving product recommendations and pricing optimization, improving the user experience through targeted marketing and personalization, and reducing churn while improving retention rates. To help reach these goals, key strategies should focus on understanding customer needs, their motivations, likes and dislikes, and using all available data – in other words, put yourself in the shoes of your customer. Our goal with Looker solutions is to offer the right level of out-of-box support that allows customers to get to value quickly, while maintaining the necessary flexibility. We aim to offer a library of data-driven solutions that accelerate data projects. Many solutions include Looker Blocks (pre-built pieces of code that accelerate data exploration environments) and Actions (custom integrations) that get customers up and running quickly and lets you build business-friendly access points for Google Cloud functionality like BQML, App Engine and Cloud Functions. Below, you’ll find a sampling of the newest Looker solutions. Listening to customers by looking at the dataLooker’s solution for Contact Center AI (CCAI), helps businesses gain a deeper understanding and appreciation of their customers’ full journey by unlocking insights from all their company’s first-party data. Call centers can converse naturally with customers and deliver outstanding experiences by leveraging artificial intelligence. CCAI‘s newest product —CCAI Insights — reviews conversations support agents are having, finding and annotating the data with the important information, and identifying the calls that need review. We’ve partnered with the product teams at CCAI to build Looker’s Block for CCAI Insights, which sets you on the path to integrating the advanced insights into your first-party data in Looker, overlaying business data with the customer experience.Sentiment Analysis Dashboard: identifies how customers feel about their interactionsBusinesses can better understand contact center experiences and take immediate action when necessary to make sure the most valuable customers receive the best service. Realizing full business value of First-Party dataLooker for Google Marketing Platform (GMP) provides marketers the power to unlock the value of their company’s first-party data to more effectively target audiences. The Looker Blocks and Actions for GMP offer interactive data exploration, slices of data with built-in ML predictions and activation paths back to the GMP. This strategic solution continues to evolve with the Looker Action for Google Ads (Customer Match), the Looker Action for Google Analytics (Data Import) and the Looker Block for Google Analytics 4 (GA4).The Looker Action for Customer Match allows marketers to send segments and audiences based on first-party data directly into Google Ads. Reach users cross-device and across the web’s most powerful channels such as Display, Video, YouTube, and Gmail. The entire process is performed within a single screen in Looker, and is able to be completed in a few minutes by a non-technical user. The Looker Action for Data Import can be used to enhance user segmentation and remarketing audiences in Google Analytics by taking advantage of user information accessible in Looker, such as in CRM systems or transactional data warehouses.The Looker Block for Google Analytics 4(GA4) expands the solution’s support with out-of-the-box dashboards and pre-baked BigQuery ML models for the newest version of Google Analytics.The Looker Block offers up reports with flexible configuration capabilities to unlock custom insights beyond the standard GA reporting. Customize audience segments, define custom goals to track and share these reports with teams who do not have access to the GA console.From clinical notes to patient insights at scaleTaking a look at the Healthcare vertical, theLooker Healthcare NLP API Block serves as a critical bridge between existing care systems and applications hosted on Google Cloud providing a managed solution for storing and accessing healthcare data in Google Cloud. The Healthcare NLP API uses natural language models to extract healthcare information from medical text, rapidly unlocking insights from unstructured medical text and providing medical providers with simplified access to intelligent insights. Healthcare providers, payers, and pharma companies can quickly understand the context and relationships of medical concepts within the text, such as medications, procedures, conditions, clinical history, and begin to link this to other clinical data sources for downstream AI/ML. Specifically, the natural language processing (NLP) Patient View (pictured below) allows you to review a single selected patient of interest, surfacing their clinical notes history over time. It informs clinical diagnosis with family history insights, which is not currently captured in claims, and captures additional procedure coding for revenue cycle purposes.NLP Patient View Dashboard: details on specific patients’The dashboard below shows the NLP Term View which allows users to focus on chosen medical terms across the entire patient population in the dataset so they can start to view trends and patterns across groups of patients. NLP Term View Dashboard: relate medical terms across your datasetThis data can be used to: Enhance patient matching for clinical trials Identify re-purposed medicationsDrive advancements for research in cancer and rare diseasesIdentify how social determinants of health impact access to careManaging Costs Across CloudsEffective cloud cost management is important for reasons beyond cost control — it provides you the ability to reduce waste and predictably forecast both costs and resource needs. Looker’s solution for Cloud Cost Management offers quick access to necessary reporting and clear insights into cloud expenditures and utilization. This solution brings together billing data from different cloud providers in a phased approach: get up and running quickly with Blocks optimized for where the data is today (Google Cloud, AWS or Azure) as you work towards more sophisticated analysis for cross-platform planning and even cloud spend optimization with the mapping of tags, labels and cost centers across clouds.Multi-cloud Summary Dashboard: a single view into spend across AWS, Azure and GCPThe Looker Cloud Cost Management solution provides operational teams struggling to monitor, understand, and manage the costs and needs associated with their cloud technology with a comprehensive view into what, where and why they are spending money.Making better decisions with Looker-powered dataLeading companies are discovering ways to get value from all of that data beyond displaying it in a report or a dashboard. They want to enable everyone to make better decisions but that’s only going to happen if everyone can ask questions of the data, and get reliable, correct answers without using outdated or incomplete data and without waiting for it. People and systems need to have data available to them in the way that makes the most sense for them at that moment. It’s clear that successful data-driven organizations will lead their respective segments not because they use data to create reports, but because they use it to power data experiences tailored to every part of the business, including employees, customers, operational workflows, products and services. As people’s way of experiencing data has evolved, more than ever before, dashboards alone are not enough. You can use data as fuel for data-driven business workflows, and to power digital experiences that improve customer engagement, conversions, and advocacy. From Nov. 9 – 11th, Looker is hosting its annual conference JOIN, where we’ll be showing new features, including how we help to:Build data experiences at the speed of businessAccelerate the business value with packaged experiences Unleash more insights for more people in the right way – Deliver data experiences at scaleThere is no cost to attend JOIN. Register hereand 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
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
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
Mit In-App-Messaging können Kunden gezielte Nachrichten in Mobil- oder Webanwendungen anzeigen lassen und ein personalisiertes Benutzererlebnis bieten. Wenn ein Endbenutzer mit einer Mobil- oder Webanwendung beschäftigt ist, können Kunden In-App-Messaging nutzen, um relevante Inhalte anzuzeigen und so hochwertige Benutzeraktionen zu fördern, z. B. Wiederholungskäufe, Werbung für wichtige Inhalte und Benutzer-Onboarding. Nach der anfänglichen Implementierung können diese Nachrichten über die Pinpoint-Konsole erstellt und gestartet werden, ohne dass Änderungen am Code vorgenommen werden müssen.
Quelle: aws.amazon.com
AWS Security Hub unterstützt jetzt Endpunkte von Amazon Virtual Private Cloud (VPC) über AWS PrivateLink, sodass Sie API-Aufrufe an Security Hub sicher von Ihrer VPC aus initiieren können, ohne dass diese Aufrufe das Internet durchqueren müssen. AWS-PrivateLink-Unterstützung für Security Hub ist jetzt in allen AWS-Regionen verfügbar, in denen Security Hub verfügbar ist. Um die neue Funktion auszuprobieren, können Sie die VPC-Konsole, die API oder das SDK aufrufen, um einen VPC-Endpunkt für Security Hub in Ihrer VPC zu erstellen. Dadurch wird eine elastische Netzwerkschnittstelle in den von Ihnen angegebenen Teilnetzen erstellt. Die Schnittstelle hat eine private IP-Adresse, die als Eingangspunkt für den Datenverkehr dient, der für den Security Hub bestimmt ist. Mehr über die Integration von Security Hub mit PrivateLink erfahren Sie hier.
Quelle: aws.amazon.com
