Data Science Tech Brief By HackerNoon – Détails, épisodes et analyse

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.
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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.

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.

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.
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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.

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.
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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.

This story was originally published on HackerNoon at: https://hackernoon.com/when-ab-tests-arent-possible-causal-inference-can-still-measure-marketing-impact.
Learn how to measure marketing impact without A/B tests using causal inference, Diff-in-Diff, synthetic control, and GeoLift.
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This story was written by: @radiokocmoc_l45iej08. Learn more about this writer by checking @radiokocmoc_l45iej08's about page, and for more stories, please visit hackernoon.com.

In many real‑world settings, running a randomized experiment is simply impossible. We’ll walk through Diff‑in‑Diff, Synthetic Control, and Meta’s GeoLift. We show how to prep your data, and provide ready‑to‑run code.

This story was originally published on HackerNoon at: https://hackernoon.com/why-data-quality-is-becoming-a-core-developer-experience-metric.
Bad data secretly slows development. Learn why data quality APIs are becoming core DX infrastructure in API-first systems and how they accelerate teams.
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This story was written by: @melissaindia. Learn more about this writer by checking @melissaindia's about page, and for more stories, please visit hackernoon.com.

In API-first systems, poor data quality (invalid emails, duplicate records, etc.) creates unpredictable bugs, forces defensive coding, and makes releases feel risky. This "hidden tax" consumes time and mental energy that should go to building features. The fix? Treat data quality as core infrastructure. By using real-time validation APIs at the point of ingestion, you create predictable systems, simplify business logic, and build developer confidence. This turns a vicious cycle of complexity into a virtuous cycle of velocity and better architecture. Bottom line: Investing in data quality isn't just operational hygiene—it's a direct investment in your team's ability to ship faster and with more confidence.

This story was originally published on HackerNoon at: https://hackernoon.com/srilatha-samalas-agile-intelligence-approach-to-enterprise-reporting-as-a-strategic-asset.
Srilatha Samala transforms enterprise reporting with Agile Intelligence, automation, and real-time dashboards that boost visibility and decision speed.
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This story was written by: @jonstojanjournalist. Learn more about this writer by checking @jonstojanjournalist's about page, and for more stories, please visit hackernoon.com.

Srilatha Samala revolutionized enterprise reporting by replacing fragmented, manual processes with automated, real-time dashboards powered by JIRA APIs, Power BI, and custom scripts. Her Agile Health Dashboard, predictive models, and workflow automation cut reporting time by 75%, improved audits, and turned data into a true strategic asset.

This story was originally published on HackerNoon at: https://hackernoon.com/the-hidden-cost-of-bad-data-why-its-undermining-your-ai-strategy.
Poor data quality is undermining your AI strategy. Uncover the hidden costs and follow our roadmap to transform bad data into a high-ROI strategic asset
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This story was written by: @rubenmelkonian. Learn more about this writer by checking @rubenmelkonian's about page, and for more stories, please visit hackernoon.com.

Poor data quality is a massive hidden cost that silently sabotages expensive AI projects and drains company resources. The "1-10-100 Rule" proves that proactive prevention is exponentially cheaper than fixing failures downstream. The solution requires a systematic approach, starting with a data audit and establishing continuous data governance, which ultimately transforms data from a liability into a high-ROI strategic asset.

This story was originally published on HackerNoon at: https://hackernoon.com/data-platform-as-a-service-a-three-pillar-model-for-scaling-enterprise-data-systems.
DPaaS solves the enterprise data scalability paradox with declarative policies, multi-plane architecture, and continuous reconciliation.
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This story was written by: @anilkumarkandalam. Learn more about this writer by checking @anilkumarkandalam's about page, and for more stories, please visit hackernoon.com.

Enterprise data platforms hit scaling limits because centralized teams can't grow fast enough to handle organizational complexity. Data Platform as a Service (DPaaS) solves this through declarative policies, multi-plane architecture, and continuous reconciliation. Enabling self service autonomy that delivers significant operational overhead reduction and faster development without proportional engineering headcount growth.

This story was originally published on HackerNoon at: https://hackernoon.com/how-rag-improves-database-management.
RAG is transforming database management with accurate retrieval, real-time insights, and natural language querying to help teams manage and understand data inte
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This story was written by: @victorhorlenko. Learn more about this writer by checking @victorhorlenko's about page, and for more stories, please visit hackernoon.com.

RAG transforms database management by combining intelligent retrieval with LLMs to deliver accurate, real-time, natural-language insights across structured and unstructured data. It enhances accuracy, speeds decision-making, reduces manual querying, and sets the stage for conversational, AI-driven data systems.