Custom Tag Manager Templates
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This document discusses custom tag manager templates, including why templates are useful, common community tags, and a demonstration of a data layer event repeater tag template. Templates allow for robust, helpful tags and variables to be built in a sandboxed, secure environment. A prototype is shown requiring only a few lines of code and no settings to add a tag, with debugging available through the console. The presentation encourages building custom templates and provides a link to a guide on single-page application tag management.
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弍亰仂 亳亠仄 ClusterFuzz, 仗仂亰于仂仍ﾑ亠亶 仂亠于亳 仗仂于亠从 弍舒亰亠舒 Chrome 仆舒 仆舒仍亳亳亠 磶于亳仄仂亠亶 于 亠亢亳仄亠 亠舒仍仆仂亞仂 于亠仄亠仆亳 亳 仗仂仍亳 于仂仗仂亳亰于仂亟亳仄亠 亠亰仍舒 亳仍亠亟仂于舒仆亳 从舒亢亟仂亞仂 从仂仆从亠仆仂亞仂 弍仂. 亟 仗仂亟亠仄仂仆亳仂于舒仆 仗亠亳仄亠于舒 亳仗仂仍亰仂于舒仆亳 舒亰仍亳仆 舒仆亳舒亶亰亠仂于 亳 LibFuzzer, 弍亳弍仍亳仂亠从亳 亟仍 仆舒仗舒于仍亠仆仆仂亞仂 舒亰亰亳仆亞舒. 亟亠 仗亳于亠亟亠仆舒 仗仂亟仂弍仆舒 舒亳亳从舒 于亳亟仂于 磶于亳仄仂亠亶, 仆舒亶亟亠仆仆 于 Chrome. 弌仍舒亠仍亳 亰仆舒ﾑ 仂 仗仂亟于仂亟仆 从舒仄仆 舒仗亠亟亠仍亠仆仆仂亞仂 舒亰亰亳仆亞舒; 仂 仂仄, 从舒从 仄仂亢仆仂 亰舒仗亳 于仂亳 仂弍于亠仆仆亠 舒亰亰亠 于 亳仆舒从亠 Google 亳 仗仂仍亳 于仂亰仆舒亞舒亢亟亠仆亳亠 亰舒 仆舒亶亟亠仆仆亠 磶于亳仄仂亳.Serverless? How (not) to develop, deploy and operate serverless applications.
Serverless? How (not) to develop, deploy and operate serverless applications.gjdevos
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Some of our lessons learned on how (not) to develop, deploy and operate serverless applications.
Presented at CfgMgmtCamp 2018 in Ghent.More from Markus Baersch (20)
Piwik PRO Near Real-Time Alerting [MeasureCamp]
Piwik PRO Near Real-Time Alerting [MeasureCamp] Markus Baersch
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際際滷s from MeasureCamp Berlin 2024-09-21"Clever & Smart" Conversion Management - Efficient Tagging in Google Tag Manager
"Clever & Smart" Conversion Management - Efficient Tagging in Google Tag Manager Markus Baersch
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際際滷s from Analytics Pioneers Summit 2024 Munich (09-2024)GA4 Without Cookies [Measure Camp AMS]![GA4 Without Cookies [Measure Camp AMS]](https://cdn.slidesharecdn.com/ss_thumbnails/2024-04ga4withoutcookiesmeasurecampams-240420113718-9d03124b-thumbnail.jpg?width=560&fit=bounds)
GA4 Without Cookies [Measure Camp AMS] Markus Baersch
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際際滷s from my untypically short session from MeasureCamp Amsterdam 2024 
Consent & Tag Management - die ultimative Checkliste Markus Baersch
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際際滷s zum Vortrag auf dem SEAcamp 2024 in Jena am 18.04.2024
![First Party Conversion Tracking [SEAcamp]](https://cdn.slidesharecdn.com/ss_thumbnails/firstpartyconversiontracking-230425224909-ccebf3e2-thumbnail.jpg?width=560&fit=bounds){kind=tracking}
First Party Conversion Tracking [SEAcamp] Markus Baersch
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(Leicht zensierte) Fassung der 際際滷s zum Vortrag auf dem SEAcamp 2023. 
![Server-Side: L旦sung f端r alles? [OMX]](https://cdn.slidesharecdn.com/ss_thumbnails/server-sidetagging-markusbaersch-221115124419-fe5cefd7-thumbnail.jpg?width=560&fit=bounds)
Server-Side: L旦sung f端r alles? [OMX] Markus Baersch
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際際滷s zum Vortrag "Server-Side: L旦sung f端r alles? - Kann serverside Tracking mein Google Analytics wirklich retten und was sind die Alternativen?" OMX Salzburg, November 2022
Google Ads Conversiontracking ohne Cookies -SEA CAMP Markus Baersch
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際際滷s zur Session beim SEAcamp 2022 in Jena
Google Analytics 4 : 10 Stolperfallen, 10 Verbesserungen + 5 Tipps [Campixx 2... Markus Baersch
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際際滷s zur Session auf der Campixx im Juli 2022. GA4/GTAG Data Capture Alternatives
GA4/GTAG Data Capture Alternatives Markus Baersch
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1. The document discusses alternatives to using gtag.js for data capture and tracking, including building a custom tracking script, using existing solutions like Tealium, The JENTIS Approach, or GA4 Destination, or integrating with server-side Google Tag Manager.
2. It notes some issues with relying solely on gtag.js, including lack of control over session handling and consent modes. Building a custom tracking script could offer more flexibility but requires more work.
3. Existing solutions were also discussed but may have dependencies, payload sizes, or lack open sources options that could be issues. Overall the document considers different options for replacing gtag.js and their tradeoffs.
Google Tag Manager Templates Markus Baersch
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際際滷s zum Analytics Pioneers Meetup in D端sseldorf am 14.06.2022.Tracking ist nicht kaputt!
Tracking ist nicht kaputt! Markus Baersch
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際際滷s zum Vortrag auf dem OMT 2021 in Mainz. Hinweis: Der Vortrag "Quo Vadis Conversiontracking" von der konversion.digital Konferenz aus dem Oktober 2021 ist im Wesentlichen hierin enthalten. 
Server-Side Google Tag Manager: Was, wie und warum Markus Baersch
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際際滷s zum Vortrag auf der CAMPIXX 2021 vom 26.08.Google Consent Mode / MC Europe 2021
Google Consent Mode / MC Europe 2021 Markus Baersch
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Google Consent Mode allows websites to continue tracking users with Google Analytics and Ads even without consent. The author argues that Consent Mode does not actually give users control over their data and tracking continues without the knowledge of the website owner or user. However, using Consent Mode with Google Tag Manager is praised as it allows custom consent settings and reduces the number of triggers needed compared to implementing consent without Tag Manager.First Party Data Collection
First Party Data Collection Markus Baersch
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This document discusses challenges with data collection due to tracking blockers, ITP, ETP and GDPR/ePrivacy regulations. It recommends using first-party data collection and secure IDs to overcome these challenges. Specifically, it suggests loading tracking scripts from your own server to avoid blockers, using server-side or encrypted IDs to deal with ITP cookie expiration, and building your own first-party data collection endpoint to respect user consent and enhance collected data. Examples of collection scripts and endpoint options are provided.
Tracking-Herausforderungen 2020 Markus Baersch
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ber neue und alte Herausforderungen f端r die Webanalyse. Folien zum MarTech Insights Webinar vom 22.04.2020
Analytics Hacks II SEAcamp 2019 Markus Baersch
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Folien zur Session auf dem SEAcamp Hannover November 2019. 
Rendering Bots erkennen Markus Baersch
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Analytics Challenge Beitrag 2019: Bot Marker zur Identifizierung von Headless Browsern & bekannten Bots. Die fehlende Tonspur kann z. T. ersetzt werden durch den passenden Blogbeitrag unter https://www.markus-baersch.de/blog/headless-browser-in-google-analytics-erkennen/ Recently uploaded (20)
ev3-software-tutorial-dc terminologia en ibgles.ppt
ev3-software-tutorial-dc terminologia en ibgles.ppthectormartinez817322
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en ingles esta prressetnacion es muy buena lasdla lkaskl siempreew aaslkd llasaslas as asasd lk aslk al kjal kj allks2024 Archive - Zsolt Nemeth web archivum
2024 Archive - Zsolt Nemeth web archivumZsolt Nemeth
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The 2024 Archive the Hollywood-Actresses.Com site new years collection.
Archivate blogging, link and clipart by Gigabajtos as Nemeth Zs. Selfpublisher active many organum or media-medium, written, comment, feed about Amazon books. Plus include 5.-Yearsbook (12.-NewsLetter).
Scaling & Measurement, Classification, and Types
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Scaling and Measuring usefiul for Data analysis and Research Purpose.Plant Disease Prediction with Image Classification using CNN.pdf
Plant Disease Prediction with Image Classification using CNN.pdfTheekshana Wanniarachchi
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Plant diseases pose a significant threat to agricultural productivity. Early detection and classification of plant diseases can help mitigate losses. This project focuses on building a Plant Disease Prediction system using Convolutional Neural Networks (CNNs). The system leverages NumPy, TensorFlow, and Streamlit to develop a model and deploy a web-based application. The final model is also containerized using Docker for efficient deployment.
MTC Supply Chain Management Strategy.pptx
MTC Supply Chain Management Strategy.pptxRakshit Porwal
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Strategic Cost Reduction in Medical Devices Supply Chain: Achieving Sustainable ProfitabilityUpdated Willow 2025 Media Deck_280225 Updated.pdf
Updated Willow 2025 Media Deck_280225 Updated.pdftangramcommunication
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Updated with the edits we last spoke Bhavana2025-03-03-Philly-AAAI-GoodData-Build Secure RAG Apps With Open LLM
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2025-03-03-Philly-AAAI-GoodData-Build Secure RAG Apps With Open LLM
https://aaai.org/conference/aaai/aaai-25/workshop-list/#ws14
Design Data Model Objects for Analytics, Activation, and AI
Design Data Model Objects for Analytics, Activation, and AIaaronmwinters
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Explore using industry-specific data standards to design data model objects in Data Cloud that can consolidate fragmented and multi-format data sources into a single view of the customer.
Design of the data model objects is a critical first step in setting up Data Cloud and will impact aspects of the implementation, including the data harmonization and mappings, as well as downstream automations and AI processing. This session will provide concrete examples of data standards in the education space and how to design a Data Cloud data model that will hold up over the long-term as new source systems and activation targets are added to the landscape. This will help architects and business analysts accelerate adoption of Data Cloud.Herding behavior Experimental Studies --AlisonLo
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My experimental studies on information cascades and herding behavior, comparing Bayesian belief updating with other behavioral heuristics that account for the observed behaviors
HIRE MUYERN TRUST HACKER FOR AUTHENTIC CYBER SERVICES
HIRE MUYERN TRUST HACKER FOR AUTHENTIC CYBER SERVICESanastasiapenova16
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Its hard to imagine the frustration and helplessness a 65-year-old man with limited computer skills must feel when facing the aftermath of a crypto scam. Recovering a hacked trading wallet can feel like an absolute nightmare, especially when every step seems to lead you into an endless loop of failed solutions. Thats exactly what I went through over the past four weeks. After my trading wallet was compromised, the hacker changed my email address, password, and even removed my phone number from the account. For someone with little technical expertise, this was not just overwhelming, it was a disaster. Every suggested solution I came across in online help centers was either too complex or simply ineffective. I tried countless links, tutorials, and forums, only to find myself stuck, not even close to reclaiming my stolen crypto. In a last-ditch effort, I turned to Google and stumbled upon a review about MUYERN TRUST HACKER. At first, I was skeptical, like anyone would be in my position. But the glowing reviews, especially from people with similar experiences, gave me a glimmer of hope. Despite my doubts, I decided to reach out to them for assistance.The team at MUYERN TRUST HACKER immediately put me at ease. They were professional, understanding, and reassuring. Unlike other services that felt impersonal or automated, they took the time to walk me through every step of the recovery process. The fact that they were willing to schedule a 25-minute session to help me properly secure my account after recovery was invaluable. Today, Im grateful to say that my stolen crypto has been fully recovered, and my account is secure again. This experience has taught me that sometimes, even when you feel like all hope is lost, theres always a way to fight back. If youre going through something similar, dont give up. Reach out to MUYERN TRUST HACKER. Even if youve already tried everything, their expertise and persistence might just be the solution you need.I wholeheartedly recommend MUYERN TRUST HACKER to anyone facing the same situation. Whether youre a novice or experienced in technology, theyre the right team to trust when it comes to recovering stolen crypto or securing your accounts. Dont hesitate to contact them, it's worth it. Reach out to them on telegram at muyerntrusthackertech or web: ht tps :// muyerntrusthacker . o r g for faster response.Large Language Models (LLMs) part one.pptx
Large Language Models (LLMs) part one.pptxharmardir
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**The Rise and Impact of Large Language Models (LLMs)**
**Introduction**
In the rapidly evolving landscape of artificial intelligence (AI), one of the most groundbreaking advancements has been the development of Large Language Models (LLMs). These AI systems, trained on massive amounts of text data, have demonstrated remarkable capabilities in understanding, generating, and manipulating human language. LLMs have transformed industries, reshaped the way people interact with technology, and raised ethical concerns regarding their usage. This essay delves into the history, development, applications, challenges, and future of LLMs, providing a comprehensive understanding of their significance.
**Historical Background and Development**
The foundation of LLMs is built on decades of research in natural language processing (NLP) and machine learning (ML). Early language models were relatively simple and rule-based, relying on statistical methods to predict word sequences. However, the emergence of deep learning, particularly the introduction of neural networks, revolutionized NLP. The introduction of recurrent neural networks (RNNs) and long short-term memory (LSTM) networks in the late 1990s and early 2000s allowed for better sequential data processing.
The breakthrough moment for LLMs came with the development of Transformer architectures, introduced in the seminal 2017 paper "Attention Is All You Need" by Vaswani et al. The Transformer model enabled more efficient parallel processing and improved context understanding. This led to the creation of models like BERT (Bidirectional Encoder Representations from Transformers) and OpenAIs GPT (Generative Pre-trained Transformer) series, which have since set new benchmarks in AI-driven text generation and comprehension.
**Core Mechanisms of LLMs**
LLMs rely on deep neural networks trained on extensive datasets comprising books, articles, websites, and other textual resources. The training process involves:
1. **Tokenization:** Breaking down text into smaller units (words, subwords, or characters) to be processed by the model.
2. **Pretraining:** The model learns general language patterns through unsupervised learning, predicting missing words or the next sequence in a text.
3. **Fine-tuning:** Adjusting the model for specific tasks, such as summarization, translation, or question-answering, using supervised learning.
4. **Inference:** The trained model generates text based on user input, leveraging probabilistic predictions to produce coherent responses.
Through these mechanisms, LLMs can perform a wide range of linguistic tasks with human-like proficiency.
**Applications of LLMs**
LLMs have found applications across various domains, including but not limited to:
1. **Content Generation:** LLMs assist in writing articles, blogs, poetry, and even code, helping content creators enhance productivity.
2. **Customer Support:** Chatbots and virtual assistants powered by LLMs provide automated yet contIntroduction to database and analysis softwares suitable for.pptx
Introduction to database and analysis softwares suitable for.pptxnabinparajuli9
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This ppt provides brief introduction and major strengths and limitations of database and analysis softwares suitable for health research.
Custom Tag Manager Templates
- 1. Custom Tag Manager Templates Demo: Build Robust & Helpful Tags & Variables Markus Baersch
- 2. Why Templates? Sandbox API vs. JS / HTML Limited JS Sandboxed = Secure(?) Transparency Updates CSP safe Gallery!!! It is not that hard!
- 3. Rocket Science?! My most successful Custom Variable GTM Template
- 4. Community Tags More typical vendors available Amplitude Awin Criteo Hubspot Klaviyo Mailchimp Matomo Outbrain Snapchat Snowplow Taboola TikTok Piwik PRO
- 6. Race Conditions: CM vs. GTM Tag Template: repeat certain events when 鍖red Tasks: 1. get dataLayer copy 2. Find events to repeat 3. Push to dataLayer again
- 8. Full Tag Template: 41 lines of unformatted code
- 9. Prototype: Only a few lines!
- 11. Prototype: Debugging (sort of)
- 12. Prototype: Adding tag No settings required
- 13. Prototype: test in console
- 14. Prototype: results console / Tag Assistant
- 15. Done ;)
- 16. Build! Missing Manual (focus on ssGTM) markus-baersch.de/gtmbook
- 17. Thank you! :) Questions? or feedback? markus-baersch.de/bsky