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Using C3S' reanalysis data ERA5 and ECMWF Medium-range Control Forecast data, the Reuters Climate Monitor shows how far current temperatures depart from the 1961–1990 average, putting everyday weather into a clear climate context. More:

Copernicus ECMWF

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12,989 views • 1 month ago •via X (Twitter)

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Watch as the East Pacific Morphs into a Monster El Niño - the strongest ever observed! This visual is different - it shows how surface and subsurface temperatures have heated dramatically since last fall - relative to October’s ocean state. The heat travels there under the surface from an overheated West Pacific Warm Pool. It’s a testament to all the excess heat being stored in the oceans now-a-days coming back to haunt us as it’s released back into the active climate system, increasing extreme weather and climate patterns like heat, floods, droughts, and fires. This is real Data visualization not AI slop. #ElNino

Watch as the East Pacific Morphs into a Monster El Niño - the strongest ever observed! This visual is different - it shows how surface and subsurface temperatures have heated dramatically since last fall - relative to October’s ocean state. The heat travels there under the surface from an overheated West Pacific Warm Pool. It’s a testament to all the excess heat being stored in the oceans now-a-days coming back to haunt us as it’s released back into the active climate system, increasing extreme weather and climate patterns like heat, floods, droughts, and fires. This is real Data visualization not AI slop. #ElNino

Jeff Berardelli

18,647 views • 20 days ago

Exploring the mind-blowing ARCO-ERA5 dataset: hourly data for almost 300 climate variables, available globally from 1940 onwards!🤯 All packaged into a single cloud-friendly Zarr file, and loadable with a single line of Python code - crazy! Below: a month of wind waves + swell:

Exploring the mind-blowing ARCO-ERA5 dataset: hourly data for almost 300 climate variables, available globally from 1940 onwards!🤯 All packaged into a single cloud-friendly Zarr file, and loadable with a single line of Python code - crazy! Below: a month of wind waves + swell:

Dr Robbi Bishop-Taylor 🦋

60,562 views • 2 years ago

$Polymarket self-calibrating weather-trading Python bot (Full Guide) run the smartest weather-trading bot with 0 coding knowledge after reading this article: what's inside: > github with full Python code > trading 20 cities & 4 continents > 3 forecast sources {ECMWF, HRRR, METAR} > EV+ automatic calculation for each trade > auto-sizing based on the Kelly Criterion > full-data storage {forecast, trade, resolution} > self-calibration based on snapshots & data logic of the bot: • get 3 type of forecasts from Open-Meteo API • compare station data to 1h forecasts to get real data • calculate +EV per $1 using the {min_ev} parameter • detemine size based on Kelly Criterion • run a 1000$ test-simulation using the strategy • snapshot each trade, forecast, and resultion • auto-calibrates every 30 forecasts per city This bot won't print you $500 next day after setup, but it will give you a sandbox for testing own strategies.$

Polymarket self-calibrating weather-trading Python bot (Full Guide) run the smartest weather-trading bot with 0 coding knowledge after reading this article: what's inside: > github with full Python code > trading 20 cities & 4 continents > 3 forecast sources {ECMWF, HRRR, METAR} > EV+ automatic calculation for each trade > auto-sizing based on the Kelly Criterion > full-data storage {forecast, trade, resolution} > self-calibration based on snapshots & data logic of the bot: • get 3 type of forecasts from Open-Meteo API • compare station data to 1h forecasts to get real data • calculate +EV per $1 using the {min_ev} parameter • detemine size based on Kelly Criterion • run a 1000$ test-simulation using the strategy • snapshot each trade, forecast, and resultion • auto-calibrates every 30 forecasts per city This bot won't print you $500 next day after setup, but it will give you a sandbox for testing own strategies.

Movez

93,175 views • 5 months ago

Me entering 2025 as the far right claims Europe, climate change spirals out of control, bird flu looms, a thick rapist is about to be US President again, AI starts to advance so far nobody will know what’s real and the broligarch billionaires start to use our data against us.

Me entering 2025 as the far right claims Europe, climate change spirals out of control, bird flu looms, a thick rapist is about to be US President again, AI starts to advance so far nobody will know what’s real and the broligarch billionaires start to use our data against us.

Supertanskiii

244,085 views • 1 year ago

Traditional physics-based models struggle with extreme rainfall, often overestimating light events while underestimating extreme precipitation. Our new hybrid climate model, NeuralGCM, more accurately simulates extreme rainfall, mean precipitation (with a 40% bias reduction compared to CMIP6 models), and the diurnal cycle of precipitation. These improvements are a direct result of training the model on NASA satellite observations, not just reanalysis data.

Traditional physics-based models struggle with extreme rainfall, often overestimating light events while underestimating extreme precipitation. Our new hybrid climate model, NeuralGCM, more accurately simulates extreme rainfall, mean precipitation (with a 40% bias reduction compared to CMIP6 models), and the diurnal cycle of precipitation. These improvements are a direct result of training the model on NASA satellite observations, not just reanalysis data.

Google Research

16,267 views • 6 months ago

How can we address the scarcity of data required for specialized AI? Learn about Simula, a framework that reframes synthetic data generation as dataset-level mechanism design. By using reasoning to architect datasets from first principles, Simula enables fine-grained control over coverage, complexity, and quality. More →

How can we address the scarcity of data required for specialized AI? Learn about Simula, a framework that reframes synthetic data generation as dataset-level mechanism design. By using reasoning to architect datasets from first principles, Simula enables fine-grained control over coverage, complexity, and quality. More →

Google Research

142,586 views • 4 months ago

How to build your own weather trading bot Every weather trader making money on Polymarket follows the same 7 steps. Free data. Simple formula. Repeat daily Traders making $20k-$180k all started here free APIs, basic math the crowd ignores, and patience Here's the playbook: Step 1: Pick 2-3 cities Don't try to trade everything. Start with NYC, Chicago, and one international city. Learn how the forecast behaves for those exact locations. Fewer cities = faster feedback loop Start copy-trading any trader even with $10 → Step 2: Pull free forecast data Open-Meteo API free, no API key, updates every 6 hours. NOAA official US government forecasts, 85-90% accurate at 1-2 days. Windy / Ventusky, visual model viewers to sanity-check your data These are the same data sources the top weather traders use. All free. All public Step 3: Turn forecasts into probabilities The market shows 8-12 temperature buckets (25°C, 26°C, 27°C). Your job: calculate the real probability for each bucket based on the forecast Simple method: > take the forecast daily max > assume ±1.5°C error range > simulate 50,000 scenarios > count how many land in each bucket > that's your probability per bucket

How to build your own weather trading bot Every weather trader making money on Polymarket follows the same 7 steps. Free data. Simple formula. Repeat daily Traders making $20k-$180k all started here free APIs, basic math the crowd ignores, and patience Here's the playbook: Step 1: Pick 2-3 cities Don't try to trade everything. Start with NYC, Chicago, and one international city. Learn how the forecast behaves for those exact locations. Fewer cities = faster feedback loop Start copy-trading any trader even with $10 → Step 2: Pull free forecast data Open-Meteo API free, no API key, updates every 6 hours. NOAA official US government forecasts, 85-90% accurate at 1-2 days. Windy / Ventusky, visual model viewers to sanity-check your data These are the same data sources the top weather traders use. All free. All public Step 3: Turn forecasts into probabilities The market shows 8-12 temperature buckets (25°C, 26°C, 27°C). Your job: calculate the real probability for each bucket based on the forecast Simple method: > take the forecast daily max > assume ±1.5°C error range > simulate 50,000 scenarios > count how many land in each bucket > that's your probability per bucket

Alex

13,953 views • 5 months ago

How to make money on the weather using Polymarket I've been noticing more and more traders quietly printing on Polymarket's weather markets lately - and the category is exploding for a reason. Weather has always been super predictable for meteorologists (and us normals) right up to the day of. The whole point? You can earn easy, near-certain yield just knowing it'll rain in London tomorrow. I'm sharing a finished tutorial with you. Here is a small list of traders 1. gopfan2 ( - The absolute leader in weather. Earned over $2M in net profit by focusing on temperature and precipitation. Strategy - buy Yes below 15 cents, No above 45 cents, with risks of less than $1 per position. It dominates the NYC and London markets where the weather is predictable 2. enzocostapt81 ( is a weather-exclusive trader whose profile shows a complete wipeout in resolved positions-no active/open trades, current positions value $0.00, and all listed markets (resolved) at -100% P/L. The trader focused solely on daily/precise temperature predictions in major cities like New York City and London. 3. 0x594edb9112f526fa6a80b8f858a6379c8a2c1c11 ( 100% of active positions are weather/temperature markets across cities like Dallas, London, Seattle, Atlanta, NYC, and Toronto—focused on precise daily highs/thresholds/ranges. 4. meropi ( - Earned ~$30k on micro bets ($1-3) with multipliers up to 500x. Automated bets on temperature rise for 0.01 cents. Focus on speed to capture momentum in daily markets. One of the most stable in weather 5. 1pixel ( – $18.5k profit from $2.3k deposit, weather only (NYC and London) 6. erb80 ( Dominant focus-two massive Atlanta temperature range bets for Dec 17, with enormous share volume at ultra-low entries (0.1¢) turning into huge unrealized gains (+49,550% on the main one) 7. Hans323 ( - Earned $1.1M on one temperature trade in London. Started with $741 in January 2025 and increased to $87k net profit for the year 8. securebet ( - Turned $7 into $640 (+9244%) on a series of temperature bets in NYC and Seattle. 3077 predictions, top 0.04% by metrics. Focus on small bets ($3-20) with high growth on low quotes. High win rate thanks to NOAA data 9. automatedAItradingbot ( Micro/low-cost bets (0.4¢–15¢) on specific outcomes, especially weather thresholds in Seoul/London and fighter matchups.Explosive wins (300%+ on select weather 1,000–5,000% average ROI across successful weather specialists based on this traders Tools and Automation > ( - Built specifically for Polymarket weather traders. Offers real-time multi-model forecasts (GFS, ECMWF, etc.), temperature range dashboards, climate pattern guides per city/station, and settlement station details. Includes educational guides on seasonal biases and forecasting challenges—highly recommended for NYC/London/Atlanta markets. > ( — Free guide/resource hub for weather betting on Polymarket. Covers market overviews, settlement rules >Tropical Tidbits ( - US GFS and ECMWF Europe models for temperature, precipitation, hurricane forecasts. Updates every 6 hours. Ideal for comparing models if 3+ agree, the probability is high >Climate Reanalyzer ( - real-time maps of air/ocean temperature, precipitation anomalies. With historical context for calculating probabilities >Windy ( - interactive maps of wind, temperature, rain, snow. 10+ models, for local events NOAA Climate Data Online ( - 100+ years of historical location data NOAA Weather Prediction ? >Center ( - short forecasts for precipitation, anomalies. Climate Prediction Center ( - long-term ENSO, droughts >Open-Meteo ( - Completely free open-source weather API with no key required. Provides GFS, ECMWF-derived, and ensemble forecasts for temperature, precipitation, and more at hourly/sub-hourly resolution globally. Excellent for scripting quick checks on NYC/London highs or comparing multiple models. Direct API calls make it ideal for automation or batch probability calculations. >OpenWeatherMap ( = Free tier gives current conditions, 5-day/3-hour forecasts, and 16-day daily forecasts. Good for real-time verification and basic historical pulls (limited free). Use for cross-checking Polymarket ranges before resolution. >Visual Crossing Weather ( - Free tier includes historical data (50+ years), current conditions, hourly/sub-hourly forecasts, and alerts. Strong for querying specific cities >WeatherAPI. com ( - Free plan covers real-time, hourly, daily forecasts (up to 14 days), historical data (from 2010), and bulk requests. Reliable for urban stations and includes marine/pollen extras if needed. Quick Tips for Using These in Trading >>>Cross-verify 3+ models (e.g., GFS + ECMWF via Open-Meteo + Windy) → if 80%+ agree on a range/threshold, probability is often very high for "Yes" bets under 10-15¢. >>>Focus on major stations (e.g., Central Park for NYC, Heathrow for London) - check settlement rules on Polymarket pages. >>>ADD TO BOOKMARKS so you don't lose alpha information

Aleiah

77,397 views • 7 months ago

So much for the environmentalists in California - California already has roughly 321 days centers - At least 280 of those were built of expanded post-2022 - There are at least 54 more data centers currently planned in California - Combined all the current data centers use the equivalent of roughly 1,000,000 average US homes - The newly planned data centers will use the equivalent of 1 million more homes - They currently use about 50+ billion gallons of water per year, potentially rising to 120+ billion gallons by 2028 But yeah… drilling some oil and driving a gas car is the problem…. California Democrats are frauds. They don’t care about the environment or climate change

So much for the environmentalists in California - California already has roughly 321 days centers - At least 280 of those were built of expanded post-2022 - There are at least 54 more data centers currently planned in California - Combined all the current data centers use the equivalent of roughly 1,000,000 average US homes - The newly planned data centers will use the equivalent of 1 million more homes - They currently use about 50+ billion gallons of water per year, potentially rising to 120+ billion gallons by 2028 But yeah… drilling some oil and driving a gas car is the problem…. California Democrats are frauds. They don’t care about the environment or climate change

Wall Street Apes

122,403 views • 3 months ago

polymarket trader turned $126 into $1,400 betting on weather prediction he is an expert in this category, trades weather markets daily made over 1,300 predictions for the last month his PnL is over $19,000 maybe he uses weather models: GFS, ECMWF, Windy and other local stations yesterday he made a profit on weather forecast in Seoul (+1,111%; +597%) and Dallas (+213%) he makes dozens of bets daily, but on short-range markets (1-2 days ahead) where the accuracy of the models is higher he also trades temperatures in NYC, London, Chicago, Taipei check his profile here: you can copy him via PolyCop: (full guide below)

mahera

27,767 views • 5 months ago

What Postgres can’t do alone, it can tackle with DuckDB. The pg_duckdb extension shows how two databases can work hand in hand by querying analytical data with DuckDB and joining it with transactional data in Postgres. The extension embeds DuckDB directly into Postgres. DuckDB literally runs inside a Postgres process. How it works (see diagram): 1. An app sends a query to Postgres joining portfolio data (Postgres) with historical market data (lakehouse) 2. pg_duckdb detects lakehouse access and delegates execution to DuckDB 3. DuckDB pulls required market data from the lakehouse, queries Postgres tables, and performs the join 4. Postgres returns the final result to the app

What Postgres can’t do alone, it can tackle with DuckDB. The pg_duckdb extension shows how two databases can work hand in hand by querying analytical data with DuckDB and joining it with transactional data in Postgres. The extension embeds DuckDB directly into Postgres. DuckDB literally runs inside a Postgres process. How it works (see diagram): 1. An app sends a query to Postgres joining portfolio data (Postgres) with historical market data (lakehouse) 2. pg_duckdb detects lakehouse access and delegates execution to DuckDB 3. DuckDB pulls required market data from the lakehouse, queries Postgres tables, and performs the join 4. Postgres returns the final result to the app

Denis Magda

28,678 views • 7 months ago

Some trader withdrew all money from polymarket and came back a month later deposited $2,000 with a new strategy now sitting at $137,000 profit he switched to weather markets every day collects data from 5 APIs simultaneously: → Open-Meteo (GFS, ECMWF models) → OpenWeatherMap → WeatherAPI → Tomorrow(.)io → Visual Crossing if 4 out of 5 models agree on one forecast edge exists but the most interesting part - temporal arbitrage cities with best liquidity: NYC, London, Atlanta, Dallas i'm copying his trades using PolyCop started with $500 address: 0xcbbc5e035504421b084ad9248b660f6e9618b5d0

Some trader withdrew all money from polymarket and came back a month later deposited $2,000 with a new strategy now sitting at $137,000 profit he switched to weather markets every day collects data from 5 APIs simultaneously: → Open-Meteo (GFS, ECMWF models) → OpenWeatherMap → WeatherAPI → Tomorrow(.)io → Visual Crossing if 4 out of 5 models agree on one forecast edge exists but the most interesting part - temporal arbitrage cities with best liquidity: NYC, London, Atlanta, Dallas i'm copying his trades using PolyCop started with $500 address: 0xcbbc5e035504421b084ad9248b660f6e9618b5d0

Archive

19,899 views • 6 months ago

How to make money on the weather using Polymarket I've been noticing more and more traders quietly printing on Polymarket's weather markets lately - and the category is exploding for a reason. Weather has always been super predictable for meteorologists (and us normals) right up to the day of. The whole point? You can earn easy, near-certain yield just knowing it'll rain in London tomorrow. I'm sharing a finished tutorial with you. Here is a small list of traders 1. gopfan2 ( - The absolute leader in weather. Earned over $2M in net profit by focusing on temperature and precipitation. Strategy - buy Yes below 15 cents, No above 45 cents, with risks of less than $1 per position. It dominates the NYC and London markets where the weather is predictable 2. enzocostapt81 ( is a weather-exclusive trader whose profile shows a complete wipeout in resolved positions-no active/open trades, current positions value $0.00, and all listed markets (resolved) at -100% P/L. The trader focused solely on daily/precise temperature predictions in major cities like New York City and London. 3. 0x594edb9112f526fa6a80b8f858a6379c8a2c1c11 ( 100% of active positions are weather/temperature markets across cities like Dallas, London, Seattle, Atlanta, NYC, and Toronto-focused on precise daily highs/thresholds/ranges. 4. meropi ( - Earned ~$30k on micro bets ($1-3) with multipliers up to 500x. Automated bets on temperature rise for 0.01 cents. Focus on speed to capture momentum in daily markets. One of the most stable in weather 5. 1pixel ( - $18.5k profit from $2.3k deposit, weather only (NYC and London) 6. erb80 ( Dominant focus-two massive Atlanta temperature range bets for Dec 17, with enormous share volume at ultra-low entries (0.1¢) turning into huge unrealized gains (+49,550% on the main one) 7. Hans323 ( - Earned $1.1M on one temperature trade in London. Started with $741 in January 2025 and increased to $87k net profit for the year 8. securebet ( - Turned $7 into $640 (+9244%) on a series of temperature bets in NYC and Seattle. 3077 predictions, top 0.04% by metrics. Focus on small bets ($3-20) with high growth on low quotes. High win rate thanks to NOAA data 9. automatedAItradingbot ( Micro/low-cost bets (0.4¢–15¢) on specific outcomes, especially weather thresholds in Seoul/London and fighter matchups.Explosive wins (300%+ on select weather 1,000–5,000% average ROI across successful weather specialists based on this traders Tools and Automation > - Built specifically for Polymarket weather traders. Offers real-time multi-model forecasts (GFS, ECMWF, etc.), temperature range dashboards, climate pattern guides per city/station, and settlement station details. Includes educational guides on seasonal biases and forecasting challenges—highly recommended for NYC/London/Atlanta markets. > - Free guide/resource hub for weather betting on Polymarket. Covers market overviews, settlement rules > - US GFS and ECMWF Europe models for temperature, precipitation, hurricane forecasts. Updates every 6 hours. Ideal for comparing models if 3+ agree, the probability is high > - real-time maps of air/ocean temperature, precipitation anomalies. With historical context for calculating probabilities > - interactive maps of wind, temperature, rain, snow. 10+ models, for local events NOAA Climate Data Online - 100+ years of historical location data NOAA Weather Prediction > - short forecasts for precipitation, anomalies. Climate Prediction Center - long-term ENSO, droughts > - Completely free open-source weather API with no key required. Provides GFS, ECMWF-derived, and ensemble forecasts for temperature, precipitation, and more at hourly/sub-hourly resolution globally. Excellent for scripting quick checks on NYC/London highs or comparing multiple models. Direct API calls make it ideal for automation or batch probability calculations. > - Free tier gives current conditions, 5-day/3-hour forecasts, and 16-day daily forecasts. Good for real-time verification and basic historical pulls (limited free). Use for cross-checking Polymarket ranges before resolution. > - Free tier includes historical data (50+ years), current conditions, hourly/sub-hourly forecasts, and alerts. Strong for querying specific cities > - Free plan covers real-time, hourly, daily forecasts (up to 14 days), historical data (from 2010), and bulk requests. Reliable for urban stations and includes marine/pollen extras if needed. Quick Tips for Using These in Trading >>>Cross-verify 3+ models (e.g., GFS + ECMWF via Open-Meteo + Windy) → if 80%+ agree on a range/threshold, probability is often very high for "Yes" bets under 10-15¢. >>>Focus on major stations (e.g., Central Park for NYC, Heathrow for London) - check settlement rules on Polymarket pages. >>>ADD TO BOOKMARKS so you don't lose alpha information

Valentin

17,124 views • 3 months ago

This animation shows sea surface temperature differences compared to average conditions between January and mid-July 2026 using data from satellites, including NOAA’s geostationary and polar-orbiting satellites. Areas where temperatures are unusually high for an extended period of time indicate marine heatwave conditions. Understanding the duration, intensity, and spatial coverage of marine heatwaves is essential as they can significantly impact marine life that coastal communities and economies rely on.

This animation shows sea surface temperature differences compared to average conditions between January and mid-July 2026 using data from satellites, including NOAA’s geostationary and polar-orbiting satellites. Areas where temperatures are unusually high for an extended period of time indicate marine heatwave conditions. Understanding the duration, intensity, and spatial coverage of marine heatwaves is essential as they can significantly impact marine life that coastal communities and economies rely on.

NOAA Satellites

45,499 views • 1 month ago

🌊 El Niño in the tropical Pacific continues to strengthen According to NOAA/CPC, sea-surface temperatures off the coast of Peru and around the Galápagos Islands are more than 3°C above the long-term average. According to the WMO’s monthly Global Seasonal Climate Update, El Niño is expected to continue strengthening and develop into a strong event during August–October 2026. A positive Indian Ocean Dipole is also forecast. During this phase, the western tropical Indian Ocean is warmer than average, while the eastern part is cooler than average. The WMO warns that a strengthening El Niño increases the likelihood of heatwaves, drought, heavy rainfall, and other extreme weather events, with impacts varying by region. 🌡️ Above-normal temperatures: expected across most inhabited land areas of the world. 💧 Wetter-than-normal conditions: western North America, central South America, southern Europe, and North Africa. ☀️ Drier-than-normal conditions: Central America, northern South America, northern Europe, parts of central Africa, India, and southern and eastern Australia.

🌊 El Niño in the tropical Pacific continues to strengthen According to NOAA/CPC, sea-surface temperatures off the coast of Peru and around the Galápagos Islands are more than 3°C above the long-term average. According to the WMO’s monthly Global Seasonal Climate Update, El Niño is expected to continue strengthening and develop into a strong event during August–October 2026. A positive Indian Ocean Dipole is also forecast. During this phase, the western tropical Indian Ocean is warmer than average, while the eastern part is cooler than average. The WMO warns that a strengthening El Niño increases the likelihood of heatwaves, drought, heavy rainfall, and other extreme weather events, with impacts varying by region. 🌡️ Above-normal temperatures: expected across most inhabited land areas of the world. 💧 Wetter-than-normal conditions: western North America, central South America, southern Europe, and North Africa. ☀️ Drier-than-normal conditions: Central America, northern South America, northern Europe, parts of central Africa, India, and southern and eastern Australia.

Windy.com

38,889 views • 1 month ago

🚀 My New Book is Here: Data Strategy (3rd Edition) 🚀 I’m thrilled to share the release of my latest bestselling book, Data Strategy: How to Use Data and Artificial Intelligence to Transform Your Business. Every business today needs data to survive - but simply having data is not enough. What matters is how you use it. A well-designed data strategy is the key to unlocking value, driving insights, and giving your organisation the competitive edge it needs to thrive in the digital economy. From small organisations to global enterprises, I’ve seen first-hand how a data-driven approach can transform operations, improve decision-making, and unlock entirely new opportunities. That’s why I’ve poured my experience into this book — to help leaders and teams build strategies that don’t just talk about data, but actually deliver measurable impact. 🔍 In this third edition, I’ve expanded the book to reflect the latest developments in data and AI, including: ✅ Generative AI and its role in shaping business innovation. ✅ Synthetic data and how it can accelerate AI adoption. ✅ The potential of quantum computing and what it means for the future of data. ✅ Expanded guidance on cybersecurity, regulations, and ethics in a data-driven world. This isn’t just a theoretical framework - it’s a practical guide to collecting, managing, and using data effectively in order to drive growth, innovation, and long-term success. Whether you’re leading a start-up or a multinational, Data Strategy will equip you with the tools you need to stay ahead in a rapidly evolving landscape. 📖 Pre-order your copy today: 👉 Amazon - 👉 Kogan Page - I can’t wait to hear how this book helps you craft your own data-driven strategy and transform your business for the future.

🚀 My New Book is Here: Data Strategy (3rd Edition) 🚀 I’m thrilled to share the release of my latest bestselling book, Data Strategy: How to Use Data and Artificial Intelligence to Transform Your Business. Every business today needs data to survive - but simply having data is not enough. What matters is how you use it. A well-designed data strategy is the key to unlocking value, driving insights, and giving your organisation the competitive edge it needs to thrive in the digital economy. From small organisations to global enterprises, I’ve seen first-hand how a data-driven approach can transform operations, improve decision-making, and unlock entirely new opportunities. That’s why I’ve poured my experience into this book — to help leaders and teams build strategies that don’t just talk about data, but actually deliver measurable impact. 🔍 In this third edition, I’ve expanded the book to reflect the latest developments in data and AI, including: ✅ Generative AI and its role in shaping business innovation. ✅ Synthetic data and how it can accelerate AI adoption. ✅ The potential of quantum computing and what it means for the future of data. ✅ Expanded guidance on cybersecurity, regulations, and ethics in a data-driven world. This isn’t just a theoretical framework - it’s a practical guide to collecting, managing, and using data effectively in order to drive growth, innovation, and long-term success. Whether you’re leading a start-up or a multinational, Data Strategy will equip you with the tools you need to stay ahead in a rapidly evolving landscape. 📖 Pre-order your copy today: 👉 Amazon - 👉 Kogan Page - I can’t wait to hear how this book helps you craft your own data-driven strategy and transform your business for the future.

Bernard Marr

10,980 views • 1 year ago

Just like The Weather Channel. Al Gore couldn’t predict the weather if his life depended on it, yet somehow they handed him a Nobel Prize and treated him like a prophet. For decades they’ve been selling fear, making predictions that never seem to materialize, and demanding more power, more control, and more money every step of the way. The climate panic industry has become a billion-dollar business. Stop blindly accepting what you’re told. Question everything. Look at the track record. The people pushing the loudest narratives are often the same people who benefit from them. Al Gore is a FRAUD.

Just like The Weather Channel. Al Gore couldn’t predict the weather if his life depended on it, yet somehow they handed him a Nobel Prize and treated him like a prophet. For decades they’ve been selling fear, making predictions that never seem to materialize, and demanding more power, more control, and more money every step of the way. The climate panic industry has become a billion-dollar business. Stop blindly accepting what you’re told. Question everything. Look at the track record. The people pushing the loudest narratives are often the same people who benefit from them. Al Gore is a FRAUD.

Gunther Eagleman™

38,915 views • 2 months ago

Hurricanes and wildfire: #hawaii #maui #wildfire #LahainaFire The winds brought the power poles and transformers down, that sparked fires, communications went down, then 80MPH gusts fanned the flames across the landscape. A perfect storm… but why?! If you look at the National Interagency Fire Center’s Predictive Services, which we have been covering, they knew Hawaii would be ready for significant fire growth as far back at Spring. “El Niño will be the driving factor.” There was a La Niña/El Niño switch this spring… El Niño has developed in the equatorial Pacific Ocean, and rapid warming continues in much of the ENSO region, especially in the central Pacific with continued anomalous warmth off the coast of South America. Above normal sea surface temperatures are observed in all ENSO regions. Most forecast guidance depicts continued warming through summer, with El Niño conditions forecast to continue into winter. The Climate Prediction Center forecasts a greater than 95% chance of El Niño conditions continuing into winter, with a 56% chance of a strong El Niño developing this fall. Other teleconnection patterns, such as the Madden Julian Oscillation (MJO), Pacific Decadal Oscillation, and Pacific-North American Pattern may influence weather and climate during the outlook period, but El Niño will be the main driver…

Hurricanes and wildfire: #hawaii #maui #wildfire #LahainaFire The winds brought the power poles and transformers down, that sparked fires, communications went down, then 80MPH gusts fanned the flames across the landscape. A perfect storm… but why?! If you look at the National Interagency Fire Center’s Predictive Services, which we have been covering, they knew Hawaii would be ready for significant fire growth as far back at Spring. “El Niño will be the driving factor.” There was a La Niña/El Niño switch this spring… El Niño has developed in the equatorial Pacific Ocean, and rapid warming continues in much of the ENSO region, especially in the central Pacific with continued anomalous warmth off the coast of South America. Above normal sea surface temperatures are observed in all ENSO regions. Most forecast guidance depicts continued warming through summer, with El Niño conditions forecast to continue into winter. The Climate Prediction Center forecasts a greater than 95% chance of El Niño conditions continuing into winter, with a 56% chance of a strong El Niño developing this fall. Other teleconnection patterns, such as the Madden Julian Oscillation (MJO), Pacific Decadal Oscillation, and Pacific-North American Pattern may influence weather and climate during the outlook period, but El Niño will be the main driver…

The Hotshot Wake Up

3,699,416 views • 3 years ago