Data Science Tech Brief By HackerNoon

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Learn the latest data science updates in the tech world.

  1. 98% of Data Strategies Fail: Let's Fix It

    2024. 08. 02.

    98% of Data Strategies Fail: Let's Fix It

    This story was originally published on HackerNoon at: https://hackernoon.com/98percent-of-data-strategies-fail-lets-fix-it. Learn how to fix failing data strategies using the '5 W's' framework. Transform your approach to KPIs and drive real business value with actionable insights. Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-strategy, #kpi-management, #business-intelligence, #data-driven-decisions, #executive-leadership, #analytics-roi, #data-roi, #data-governance, and more. This story was written by: @liorb. Learn more about this writer by checking @liorb's about page, and for more stories, please visit hackernoon.com. Even the most well-equipped organizations can find themselves serving up a mess instead of actionable insights. Here's a step-by-step process of fixing your data strategy, ensuring that you're serving up actionable data instead of a recipe for disaster. In the following sections, we'll dive into the common data strategy nightmares.

    11분
  2. How To Measure The Results Of In-App Events When Onelinks Don’t Work

    2024. 07. 30.

    How To Measure The Results Of In-App Events When Onelinks Don’t Work

    This story was originally published on HackerNoon at: https://hackernoon.com/how-to-measure-the-results-of-in-app-events-when-onelinks-dont-work. How To Measure The Results Of In-App Events When Onelinks Don’t Work Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #analytics, #onelink, #inapp-events, #marketing, #app-store, #mobile-apps, #digital-marketing, #good-company, and more. This story was written by: @socialdiscoverygroup. Learn more about this writer by checking @socialdiscoverygroup's about page, and for more stories, please visit hackernoon.com. Many app developers and marketing managers face the challenge of accurately measuring the impact of In-App Events (IAEs) on the App Store. While IAEs have proven effective for re-engaging users, attracting new downloads, and increasing revenue, traditional tracking methods like OneLink don’t actually include IAEs. Major mobile attribution platforms confirm that currently there is no way to track IAEs properly. At Social Discovery Group, our portfolio of 60+ dating and entertainment brands is supported by a team of over 100 marketers dedicated to app growth and development. We’re used to measuring all our marketing efforts in terms of financial value. Eventually, we’ve managed to develop our own composite way to evaluate IAEs, and are going to share it with you.

    6분
  3. How AI-Powered Data Mapping is Democratizing Data Management

    2024. 07. 27.

    How AI-Powered Data Mapping is Democratizing Data Management

    This story was originally published on HackerNoon at: https://hackernoon.com/how-ai-powered-data-mapping-is-democratizing-data-management. Learn how AI-powered data mapping is transforming data management, making it more accessible and efficient for everyone. Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-mapping, #data-management, #big-data, #ai-powered, #ai-powered-data-management, #democratizing-data-management, #data-science, #ai-powered-data-mapping, and more. This story was written by: @kristenburke. Learn more about this writer by checking @kristenburke's about page, and for more stories, please visit hackernoon.com. AI is revolutionizing data mapping by automating and simplifying the process, making data management more efficient and accessible for businesses and non-technical users alike.

    8분
  4. Data Engineering: What’s the Value of API Security in the Generative AI Era?

    2024. 07. 27.

    Data Engineering: What’s the Value of API Security in the Generative AI Era?

    This story was originally published on HackerNoon at: https://hackernoon.com/data-engineering-whats-the-value-of-api-security-in-the-generative-ai-era. Discover the importance of API security in the age of Generative AI. Learn how robust API protection ensures data integrity. Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-engineering, #generative-ai, #ai-regulation, #api-security, #data-security, #data-privacy, #threat-detection, #cybersecurity-best-practices, and more. This story was written by: @karthikrajashekaran. Learn more about this writer by checking @karthikrajashekaran's about page, and for more stories, please visit hackernoon.com. API security is crucial in the era of Generative AI, ensuring data integrity, protecting user privacy, and enabling secure and efficient AI integration. Robust API protection helps prevent unauthorized access, data breaches, and potential misuse of AI capabilities.

    6분
  5. Say Goodbye to Outdated Diagrams: Automate Your Infrastructure Visualization

    2024. 07. 25.

    Say Goodbye to Outdated Diagrams: Automate Your Infrastructure Visualization

    This story was originally published on HackerNoon at: https://hackernoon.com/say-goodbye-to-outdated-diagrams-automate-your-infrastructure-visualization. Automate your infrastructure diagrams. Guide helps you maintain fresh, accurate visuals with minimal effort, perfect for managing Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #visualization, #cloud-infrastructure, #terraform, #diagram, #infrastructure-as-code, #cloud, #aws, #infrastructure-visualization, and more. This story was written by: @vladimirf. Learn more about this writer by checking @vladimirf's about page, and for more stories, please visit hackernoon.com. Tired of making awesome infrastructure diagrams that become outdated as soon as you save them? Yeah, me too. Luckily, there are tools out there to help.

    7분
  6. Why C-Suite Executives Won’t Cut it Without Data Skills Anymore

    2024. 07. 25.

    Why C-Suite Executives Won’t Cut it Without Data Skills Anymore

    This story was originally published on HackerNoon at: https://hackernoon.com/why-c-suite-executives-wont-cut-it-without-data-skills-anymore. Modern executives must master data skills to navigate data privacy, cybersecurity, and strategic decisions. Learn why C-suite leaders can't afford to lag behind Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-literacy, #thought-leadership, #leadership-skills, #data-skills, #data-governance, #data-visualization-tools, #cybersecurity-executives, #hackernoon-top-story, and more. This story was written by: @znenad079. Learn more about this writer by checking @znenad079's about page, and for more stories, please visit hackernoon.com. Every industry generates massive amounts of data, which is now being used for better decision-making. One of today’s most pressing challenges for executives is data privacy concerns and cybersecurity. Modern executives must have data skills to understand the flow of valuable data in their company and know how to make it work for them.

    7분
  7. Meet New & Improved BigQuery: Single, Unified AI-Ready Data Platform

    2024. 07. 20.

    Meet New & Improved BigQuery: Single, Unified AI-Ready Data Platform

    This story was originally published on HackerNoon at: https://hackernoon.com/meet-new-and-improved-bigquery-single-unified-ai-ready-data-platform. Google has gone a step further and unified key data Google Cloud analytics capabilities under BigQuery - now the single, AI-ready data analytics platform.  Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-analytics, #google-bigquery, #bigquery-and-google-cloud, #ai-integration, #big-query-and-gemini, #good-company, #hackernoon-top-story, #real-time-data-analytics, and more. This story was written by: @googlecloud. Learn more about this writer by checking @googlecloud's about page, and for more stories, please visit hackernoon.com. We’ve gone a step further and unified key data Google Cloud analytics capabilities under BigQuery, which is now the single, AI-ready data analytics platform. BigQuery incorporates key capabilities from multiple Google Cloud analytics services into a single product experience that offers the simplicity and scale you need to manage structured data in BigQuery tables, unstructured data like images, audience and documents, and streaming workloads, all with the best price-performance.

    10분
  8. Decoding Transformers' Superiority over RNNs in NLP Tasks

    2024. 07. 19.

    Decoding Transformers' Superiority over RNNs in NLP Tasks

    This story was originally published on HackerNoon at: https://hackernoon.com/decoding-transformers-superiority-over-rnns-in-nlp-tasks. Explore the intriguing journey from Recurrent Neural Networks (RNNs) to Transformers in the world of Natural Language Processing in our latest piece: 'The Trans Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #nlp, #transformers, #llms, #natural-language-processing, #large-language-models, #rnn, #machine-learning, #neural-networks, and more. This story was written by: @artemborin. Learn more about this writer by checking @artemborin's about page, and for more stories, please visit hackernoon.com. Despite Recurrent Neural Networks (RNNs) designed to mirror certain aspects of human cognition, they've been surpassed by Transformers in Natural Language Processing tasks. The primary reasons include RNNs' issues with the vanishing gradient problem, difficulty in capturing long-range dependencies, and training inefficiencies. The hypothesis that larger RNNs could mitigate these issues falls short in practice due to computational inefficiencies and memory constraints. On the other hand, Transformers leverage their parallel processing ability and self-attention mechanism to efficiently handle sequences and train larger models. Thus, the evolution of AI architectures is driven not only by biological plausibility but also by practical considerations such as computational efficiency and scalability.

    10분
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