Data Science Tech Brief By HackerNoon

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Learn the latest data science updates in the tech world.

  1. From Data Fragmentation to Billion-Dollar Insights: The Vision of Manish Ravindra Sharath

    ٣٠ أكتوبر

    From Data Fragmentation to Billion-Dollar Insights: The Vision of Manish Ravindra Sharath

    This story was originally published on HackerNoon at: https://hackernoon.com/from-data-fragmentation-to-billion-dollar-insights-the-vision-of-manish-ravindra-sharath. Manish Ravindra Sharath unified fragmented enterprise data using PySpark & cloud-native systems,boosting efficiency 99% and driving multimillion-dollar growth. Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #enterprise-data-engineering, #manish-ravindra-sharath, #pyspark-data-pipeline, #cloud-data-architecture, #data-modernization-strategy, #hybrid-data-infrastructure, #enterprise-analytics, #good-company, and more. This story was written by: @sanya_kapoor. Learn more about this writer by checking @sanya_kapoor's about page, and for more stories, please visit hackernoon.com. Manish Ravindra Sharath transformed enterprise decision-making by architecting a unified PySpark-powered data pipeline that cut reporting time from 30+ hours to 30 minutes. His system achieved 99% efficiency, 40% cost reduction, and 30% faster deal closures—turning fragmented data into billion-dollar insights driving global business performance.

    ٧ من الدقائق
  2. Building a Layered Defense Against Web Scraping

    ٣٠ أكتوبر

    Building a Layered Defense Against Web Scraping

    This story was originally published on HackerNoon at: https://hackernoon.com/building-a-layered-defense-against-web-scraping. Discover how a three-layer data-protection model blends AI, risk-based gating, and legal context to stop web scraping while preserving user trust. Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #web-scraping, #data-protection, #ai-security, #product-strategy, #web-scraping-protection, #bot-mitigation, #risk-based-gating, #data-security-strategy, and more. This story was written by: @areejit1. Learn more about this writer by checking @areejit1's about page, and for more stories, please visit hackernoon.com. The web-scraping industry is no longer niche. Valued at USD 1.03 billion in 2025, it is projected to nearly double by 2030. Traditional defenses rate limiting, CAPTCHAs, IP bans are brittle against modern toolkits. A layered defense acknowledges this tension.

    ٩ من الدقائق
  3. Cosmo: The Graph Visualization Tool Built for Your Terminal

    ٢٣ أكتوبر

    Cosmo: The Graph Visualization Tool Built for Your Terminal

    This story was originally published on HackerNoon at: https://hackernoon.com/cosmo-the-graph-visualization-tool-built-for-your-terminal. Cosmo is a terminal-based interactive graph visualizer that automatically layouts and displays complex data structures for quick exploration. Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #visualization, #terminal, #cli, #graphs, #tui, #cosmo, #complex-data-structures, #gui-visualizer, and more. This story was written by: @hacker227143. Learn more about this writer by checking @hacker227143's about page, and for more stories, please visit hackernoon.com. Cosmo is a fast, interactive graph visualizer that makes graphs and trees easy to understand, beautifully arranged, and fully explorable without ever leaving your command line. Pass your data structures directly from code or file and see them come to life.

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  4. How Businesses Are Turning Space Data into a Tool for Risk, Resilience, and Sustainability

    ١٥ أكتوبر

    How Businesses Are Turning Space Data into a Tool for Risk, Resilience, and Sustainability

    This story was originally published on HackerNoon at: https://hackernoon.com/how-businesses-are-turning-space-data-into-a-tool-for-risk-resilience-and-sustainability. Satellites are reshaping insurance, supply chains, and sustainability—here’s how space data became core to global business strategy. Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #business-intelligence, #space-economy, #satellite-data, #sustainability-reporting, #supply-chain-analytics, #geospatial-intelligence, #space-technology, #earth-observation, and more. This story was written by: @150sec. Learn more about this writer by checking @150sec's about page, and for more stories, please visit hackernoon.com. The global space economy is evolving from exploration to infrastructure. Businesses across insurance, sustainability, and supply chains now rely on satellite data for real-time insights that help manage risk, track biodiversity, forecast disruptions, and meet new reporting standards. As costs drop and access expands, space data has become an essential layer of corporate intelligence—turning orbit into opportunity.

    ٦ من الدقائق
  5. How Data Innovation Changed a State’s Infrastructure Engine

    ١٠ أكتوبر

    How Data Innovation Changed a State’s Infrastructure Engine

    This story was originally published on HackerNoon at: https://hackernoon.com/how-data-innovation-changed-a-states-infrastructure-engine. Deepak Chanda modernized Massachusetts’ infrastructure systems through data-driven process innovation—turning inefficiency into lasting operational reform. Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-innovation-in-government, #infrastructure-analytics, #data-transformation, #process-automation, #massachusetts-transportation, #sql-data-pipeline-optimization, #real-time-anomaly-detection, #good-company, and more. 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. Amid bureaucratic stagnation in Massachusetts’ public works, Senior Data Analyst Deepak Chanda led a quiet revolution. By digitizing blueprint reviews and adding a simple SQL field to track project sign-offs, he cut delays and saved taxpayer dollars. His philosophy—good data should shape the world, not just describe it—continues to drive progress across healthcare and insurance.

    ٨ من الدقائق
  6. How to Optimize Your Marketing Budget Using Just Three Letters: MMM

    ٢٥ سبتمبر

    How to Optimize Your Marketing Budget Using Just Three Letters: MMM

    This story was originally published on HackerNoon at: https://hackernoon.com/how-to-optimize-your-marketing-budget-using-just-three-letters-mmm. Marketing Mix Modeling is a statistical analysis method used in marketing to determine the optimal allocation of resources. Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-science, #marketing-analytics, #machine-learning, #marketing, #marketing-budget, #marketing-mix-modeling, #media-mix-modelling, #adstock-and-saturation, and more. 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. Marketing Mix Modeling is a statistical analysis method used in marketing to determine the optimal allocation of resources. The goal of media mix modelling is to understand the impact of different marketing channels on the overall campaign effectiveness. Join me to discover how to optimise the marketing budget by implementing Robyn MMM.

    ٧ من الدقائق
  7. Here's How ShareChat Scaled Their ML Feature Store 1000X Without Scaling the Database

    ٢٥ سبتمبر

    Here's How ShareChat Scaled Their ML Feature Store 1000X Without Scaling the Database

    This story was originally published on HackerNoon at: https://hackernoon.com/heres-how-sharechat-scaled-their-ml-feature-store-1000x-without-scaling-the-database. How ShareChat scaled its ML feature store to 1B features/sec on ScyllaDB, achieving 1000X performance without scaling the database. Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #sharechat-ml-feature-store, #scylladb-scaling-case-study, #ml-feature-store-optimization, #sharechat-moj, #low-latency-ml-infrastructure, #scylladb-database-optimization, #p99-conf-sharechat-talk, #good-company, and more. This story was written by: @scylladb. Learn more about this writer by checking @scylladb's about page, and for more stories, please visit hackernoon.com. ShareChat scaled its ML feature store from failure at 1M features/sec to 1B features/sec using ScyllaDB optimizations, caching hacks, and relentless tuning. By rethinking schemas, tiling, and caching strategies, engineers avoided scaling the database, cut latency, and boosted cache hit rates—proving performance engineering beats brute-force scaling.

    ١٣ من الدقائق
  8. Why You Shouldn’t Judge by PnL Alone

    ٢٤ سبتمبر

    Why You Shouldn’t Judge by PnL Alone

    This story was originally published on HackerNoon at: https://hackernoon.com/why-you-shouldnt-judge-by-pnl-alone. PnL can lie. This hands-on guide shows traders how hypothesis testing separate luck from edge, with a Python example and tips on how not to fool yourself. Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #quantitative-research, #trading, #algorithmic-trading, #pnl, #udge-pnl, #profit-and-loss, #judge-profit-and-loss, #hackernoon-top-story, and more. This story was written by: @ruslan4ezzz. Learn more about this writer by checking @ruslan4ezzz's about page, and for more stories, please visit hackernoon.com. I’ve spent years building and evaluating systematic strategies across highly adversarial markets. When you iterate on a trading system, PnL is the goal but a terrible day-to-day signal. It’s too noisy, too path-dependent, and too easy to cherry-pick. A simple framework—form a hypothesis, measure a test statistic, translate it into a probability under a “no-effect” world (the p-value)—helps you avoid false wins, iterate faster, and ship changes that actually stick. Below I’ll show a concrete example where two strategies look very different in cumulative PnL charts, yet standard tests say there’s no meaningful difference in their average per-trade outcome. I’ll also demystify the t-test in plain language: difference of means, scaled by uncertainty.

    ١٣ من الدقائق
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