🔓 Unlock Real-Time Business Insights: Deploy Interactive Dashboards with Shiny and AWS 📊 Discover how you can transform your data into actionable insights with interactive web dashboards. Learn how Shiny and AWS can help you visualize and share data seamlessly across your organization, driving informed decision-making and boosting business performance. #DataAnalytics #BusinessIntelligence #Shiny #AWS #DataVisualization
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🚀 Thrilled to share one of my latest weekend projects - I've been diving deep into the possibilities of feeding PowerBI with real-time Adobe data… 📈 Despite the array of impressive features in Adobe Analytics' successor, Customer Journey Analytics, it lacks one vital element - real-time insights. That's why I wanted to come up with a creative integration between Adobe data collection with PowerBI via Microsoft Azure that is robust enough to not only fit as an interim solution. 🧠 Read the full story followed by a technical tutorial here: https://lnkd.in/eAzKqWEY #dataanalytics #adobe #azure #powerbI #realtimedata #techinnovation #bigdata #analytics #martech #dataarchitecture #enterprisearchitecture #adobeanalytics #aep #microsoftazure
When Latency Matters: Visualize real-time Adobe data in PowerBI
medium.com
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Research & Business Analyst| SCM |Data Analyst |Data Scientist | Business Intelligence Analyst | AI | ML |Data Visualisaztion
There are several reasons why business platforms should use Looker Studio (formerly known as Google Data Studio): 1. Free and Accessible: 📢 Looker Studio is a free to use tool for creating reports and dashboards. This makes it accessible to businesses of all sizes, regardless of their budget. 📢 With Looker Studio, anyone in the organization can create and share reports, democratizing data and fostering collaborative decision-making. 2. Powerful Data Visualization: 📢 Looker Studio offers a wide range of customizable data visualization tools, allowing businesses to create compelling and informative dashboards and reports. 📢 Users can choose from a variety of charts, graphs, and other visual elements, making it easy to communicate complex data in an easy-to-understand format. 📢 Looker Studio even supports interactive features, such as filters and drill-downs, allowing users to explore their data in more depth. 3. Integrates with Diverse Data Sources: 📢 Looker Studio can connect to a wide variety of data sources, including Google Analytics, Google Ads, Google Sheets, BigQuery, and many others. 📢 This allows businesses to consolidate all of their data into a single platform, making it easier to analyze trends and identify patterns. 📢 Looker Studio also allows for custom data connectors, further expanding its reach to even more data sources. 4. Collaboration and Sharing: 📢 Looker Studio makes it easy to share reports and dashboards with others within your organization. 📢 Users can create team workspaces to manage access and collaborate on projects. 📢 Looker Studio also allows for embedding reports and dashboards into websites and other applications, making them accessible to a wider audience. 5. Improved Decision-Making: 📢 By providing businesses with a clear and concise view of their data, Looker Studio helps them make better decisions about everything from marketing campaigns to operational efficiency. 📢 The ability to track key performance indicators (KPIs) and identify trends allows businesses to make data-driven decisions that are more likely to be successful. 6. Scalable and Secure: 📢 Looker Studio Pro offers a secure and scalable platform for managing large datasets and complex reports. 📢 With features like team workspaces and Google Cloud project linking, businesses can easily manage access and security for their data. 🔔 Looker Studio is a powerful and versatile tool that can help businesses of all sizes improve their data analysis, decision-making, and overall performance. Its free tier, diverse data integrations, and collaborative features make it a compelling choice for any business that wants to gain more insights from its data. #LookerCommunity #BusinessIntelligence #GetStartedWithLookerStudio #BecomeABetterDataAnalyst #DataStorytelling
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📊🚀 Considering the right reporting platform for your business? Let's dive into the Swydo vs. Looker Studio comparison and help you make an informed decision! 👇 🌟 Why Choose Swydo Over Looker Studio? 🎯 Ease of Use: Swydo is user-friendly, catering to all skill levels. With an extensive template library and a quick setup, your reports are ready in minutes. 🎯 Reporting Capabilities: Swydo offers comprehensive reporting features with customization options. You can even Whitelabel your reports, adding that professional touch. 🎯Live Customer Support: Need help? Swydo's support team is available 24/5 and is known for their responsiveness and expertise. We also offer personalized onboarding sessions. 🎯 Customer-Driven Approach: Unlike Looker Studio, Swydo actively listens to customer feedback, ensuring the platform remains user-friendly and adaptable. 🎯 Flexibility and Scalability: Swydo grows with your business. It's highly flexible, multi-channel, and cost-effective, making it an excellent choice for organizations of all sizes. Its user-friendliness, extensive features, excellent customer support, and scalability make it a reliable choice for businesses seeking a simple yet powerful reporting and analytics platform. #Analytics #MarketingReports #DataDrivenDecisions #Swydo 💬
Swydo vs Looker Studio
swydo.com
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Power BI embedded analytics allows the user to embed fully interactive Power BI reports and dashboards into a web application. This functionality is immensely powerful, as it opens the door to using the full capacity of a web application along with all the features that Power BI offers us. What’s more, adding visualisations directly from Power BI to your web applications speeds up the process and reduces expenditure. Find out how to easily embed your Power BI reports into web applications using the capabilities offered by Power BI embedded analytics and contact us today to help you! https://hubs.la/Q02mG3VS0 #powerbi #powerbiembedded #embeddedanalytics #webdevelopment #data #analytics #powerplatform
Embed Power BI Reports into Your Web Applications Using Power BI Embedded Analytics - ClearPeaks Blog
https://www.clearpeaks.com
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Analytics industry veteran. Product Evangelist @ Amplitude. Helping teams build better products. Author of the definitive book on Adobe Analytics.
Warehouse Native Analytics is an emerging trend that allows organizations to leverage data they already have in warehouses like Snowflake to do digital analytics. It is part of the trend towards composability. Amplitude is the only digital analytics vendor that offers a hybrid approach to warehouse native analytics - allowing you to reap the benefits of traditional SaaS and new composable models instead of having to pick one or the other. We believe in meeting organizations where they are when it comes to data. A while back, I did a 101 type webinar on warehouse native analytics. You can see a link to this video in the comments...
Amplitude Fully Replatforms on Snowflake with Snowflake Native Amplitude
amplitude.com
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Interactive dashboards not only provide advantages for end-users but for dashboard builders as well. Streamlining navigation and building high-performing dashboards that improve the efficiency, flexibility, and effectiveness of the data exploration process. Read more about what you can do with interactive dashboards in this article from GoodData Senior Product Manager, Miroslav Koldus. #dataanalytics #datavisualization #dataviz #businessintelligence #bi #interactivedashboards #datadashboards
Beyond Static Reporting: Interactive Dashboards
medium.com
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Allow more users to view your embedded Tableau content with on-demand access. On-demand access uses Connected Apps and group-level permissions to authenticate users without creating accounts in Tableau—making it easier to manage and grow your user base. Matt Longieliere, Product Manager, Tableau explains how it works: tabsoft.co/46VTb8O
Extend Access to Embedded Tableau Content with On-Demand Access
tableau.com
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The most common reason I hear that an org is staying on Adobe Analytics is their use of data feeds. It’s often related to the web of pipelines and transforms that are derived from the clickstream asset and the complexity of the data itself: they don’t want to break anything. Some have even said that their users don’t use Adobe Analytics UI, anymore. It’s effectively just the data feed. In those cases, it begs the question: why still pay for Adobe Analytics? Collecting event clickstream is the easy part. If you can’t build in-house solutions (look hard enough and you’ll find an engineer that is already storing streaming events), tools like Snowplow and others are readily available to start accumulating live events and it doesn’t have to be an indecipherable puzzle of events, props, eVars and post_product_lists (the WORST) being delivered hours later on a batch schedule. The small army of SQL engineers dedicated to untangling and maintaining that AA data feed can be put toward activating live clickstream with triggered journeys, modeled audiences, training AI with data designed for your business in a schema that your users understand. “But what about the post-processed columns?”. I promise, if you describe what those eVars are doing, any decent SQL engineer can quickly emulate persistence and attribution with some windowing functions. When used only as a data feed, there’s really nothing special about what Adobe Analytics is doing! On the analysis side, what IS extremely difficult is modeling clickstream data into something that is explorable while remaining performant and cost-efficient. It’s easy to be prescriptive and model clickstream with the exact dimensions and metrics you want, but when you’re trying to find relationships among hundreds of different columns and create new calculations on the fly against millions and billions of rows, it takes months and can be challenging to optimize processing costs for even the most skilled engineers. That ability to explore has been Adobe Analytics strength, and when you own and design your own schemas, CJA plays that role allowing you to generate rapid insights not just with the clickstream, but any other customer data that may be sitting next to it in the data warehouse. The AA data feed tends to be an anchor. When the industry talks about leveraging 1st-party data, that includes breaking free from batch processed 3rd-party data feeds. Own and control your data while putting it in the places that make it most valuable. It might be your cloud data warehouse, or Adobe’s Experience Platform. Regardless, it’s time to start thinking about how to get out from under data feeds while getting more value out of clickstream data.
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Agreed! It’s time to modernize and eliminate tech debt, while significantly improving latency and overhead in the data pipeline for first-party, clickstream data. It’s time for your clickstream data to be a first-class citizen in the enterprise data strategy. Modernizing to CJA is the answer.
The most common reason I hear that an org is staying on Adobe Analytics is their use of data feeds. It’s often related to the web of pipelines and transforms that are derived from the clickstream asset and the complexity of the data itself: they don’t want to break anything. Some have even said that their users don’t use Adobe Analytics UI, anymore. It’s effectively just the data feed. In those cases, it begs the question: why still pay for Adobe Analytics? Collecting event clickstream is the easy part. If you can’t build in-house solutions (look hard enough and you’ll find an engineer that is already storing streaming events), tools like Snowplow and others are readily available to start accumulating live events and it doesn’t have to be an indecipherable puzzle of events, props, eVars and post_product_lists (the WORST) being delivered hours later on a batch schedule. The small army of SQL engineers dedicated to untangling and maintaining that AA data feed can be put toward activating live clickstream with triggered journeys, modeled audiences, training AI with data designed for your business in a schema that your users understand. “But what about the post-processed columns?”. I promise, if you describe what those eVars are doing, any decent SQL engineer can quickly emulate persistence and attribution with some windowing functions. When used only as a data feed, there’s really nothing special about what Adobe Analytics is doing! On the analysis side, what IS extremely difficult is modeling clickstream data into something that is explorable while remaining performant and cost-efficient. It’s easy to be prescriptive and model clickstream with the exact dimensions and metrics you want, but when you’re trying to find relationships among hundreds of different columns and create new calculations on the fly against millions and billions of rows, it takes months and can be challenging to optimize processing costs for even the most skilled engineers. That ability to explore has been Adobe Analytics strength, and when you own and design your own schemas, CJA plays that role allowing you to generate rapid insights not just with the clickstream, but any other customer data that may be sitting next to it in the data warehouse. The AA data feed tends to be an anchor. When the industry talks about leveraging 1st-party data, that includes breaking free from batch processed 3rd-party data feeds. Own and control your data while putting it in the places that make it most valuable. It might be your cloud data warehouse, or Adobe’s Experience Platform. Regardless, it’s time to start thinking about how to get out from under data feeds while getting more value out of clickstream data.
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This is a very useful guide for any Analytics Engineers starting out with the Adobe Experience Platform. There are different ways to prepare data in AEP, so this explores one of them, the Data Prep feature. I know many businesses are starting their journeys on AEP, so practical “How To” guides like this are very valuable. https://lnkd.in/e2pJFx2f
How To Guide – Adobe AEP Data Prep - Station10
https://station10.co.uk
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