{
  "format": "dataset-manifest/1",
  "slug": "weather-forecast-and-alert-app",
  "version": 1,
  "seed": "weather-forecast-and-alert-app:1",
  "spec": {
    "format": "dataset/1",
    "slug": "weather-forecast-and-alert-app",
    "name": "Weather Insights Collection",
    "tagline": "Accurate weather forecasts and alerts for informed decision-making.",
    "description": "Weather forecasts inform individuals and organizations about impending climate conditions, guiding them in decision-making processes. This business operates with a focus on providing timely and precise weather reports through a network of IoT sensors strategically placed in various locations. Users benefit from customized alerts that reflect their geographical area and personal preferences, ensuring they receive relevant information to stay prepared for daily and severe weather events alike.\n\nThe primary table in this dataset, `weather_data`, contains detailed records of weather conditions captured by these sensors. Each row represents a unique entry of weather data linked to specific timestamps and locations. Attributes such as temperature, humidity, wind speed, and weather events are documented, allowing for a comprehensive view of the weather landscape at any given moment. This structured approach enables developers to explore various relationships within the data, such as trends over time and the correlation between different weather factors.\n\nPractitioners can utilize this dataset to answer crucial questions like: How do temperature fluctuations impact humidity levels? What are the patterns of extreme weather occurrences in specific regions? By analyzing this data, developers can hone their skills in data manipulation, visualization, and predictive analytics, particularly in the context of seasonal variations and climate change impacts. Additionally, the insights drawn from this data can assist organizations in improving their weather preparedness strategies.\n\nIt's important to note that this data is synthetic, designed to simulate real-world weather conditions while ensuring a safe and versatile environment for practicing data analysis techniques.",
    "domain": "iot",
    "shape": "time-series",
    "useCases": [
      "analytics-demo",
      "bi-dashboards"
    ],
    "keywords": [
      "weather",
      "forecasts",
      "alerts",
      "sensor data",
      "IoT",
      "time-series",
      "analytics",
      "climate",
      "extreme weather"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "weather_data": {
        "description": "Each row in this table represents daily weather metrics collected from various IoT monitoring stations. It includes common conditions alongside alerts for extreme weather events.",
        "rows": 365,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each record."
          },
          "date": {
            "kind": "date",
            "from": "2022-01-01",
            "to": "2022-12-31",
            "description": "The date of the recorded weather data.",
            "trend": "seasonal"
          },
          "temperature_c": {
            "kind": "decimal",
            "min": -30,
            "max": 50,
            "scale": 1,
            "description": "Average temperature for the day in degrees Celsius.",
            "nullable": true
          },
          "humidity_percentage": {
            "kind": "decimal",
            "min": 0,
            "max": 100,
            "scale": 1,
            "description": "Average humidity for the day as a percentage.",
            "nullable": true
          },
          "wind_speed_kmh": {
            "kind": "decimal",
            "min": 0,
            "max": 150,
            "scale": 1,
            "description": "Average wind speed for the day in kilometers per hour.",
            "nullable": true
          },
          "alert": {
            "kind": "enum",
            "values": [
              "none",
              "storm",
              "hurricane",
              "flood",
              "heatwave"
            ],
            "weights": [
              0.7,
              0.1,
              0.05,
              0.1,
              0.05
            ],
            "description": "Type of weather alert issued for the day."
          },
          "sensor_status": {
            "kind": "enum",
            "values": [
              "operational",
              "maintenance",
              "offline"
            ],
            "weights": [
              0.85,
              0.1,
              0.05
            ],
            "description": "Operational status of the weather monitoring sensor.",
            "nullable": true,
            "when": {
              "column": "alert",
              "in": [
                "storm",
                "hurricane",
                "flood",
                "heatwave"
              ]
            }
          }
        }
      }
    },
    "structure": "single-table",
    "traits": [
      "timestamped",
      "monetary",
      "categorical",
      "nullable"
    ],
    "analysisQuestions": [
      "What are the average temperature trends throughout the year?",
      "How often do extreme weather alerts occur, and during which months?",
      "What is the relationship between humidity levels and temperature?",
      "What percentage of the time are sensors operational versus under maintenance?"
    ],
    "suggestedQueries": [
      {
        "title": "Get all weather data for January 2022",
        "sql": "SELECT * FROM weather_data WHERE date BETWEEN '2022-01-01' AND '2022-01-31';",
        "dialect": "postgres"
      },
      {
        "title": "Count the number of extreme weather alerts issued",
        "sql": "SELECT alert, COUNT(*) FROM weather_data WHERE alert != 'none' GROUP BY alert;",
        "dialect": "postgres"
      },
      {
        "title": "Find average temperature on days with heatwave alerts",
        "sql": "SELECT AVG(temperature_c) FROM weather_data WHERE alert = 'heatwave';",
        "dialect": "postgres"
      },
      {
        "title": "Get daily wind speed over a specific date range",
        "sql": "SELECT date, wind_speed_kmh FROM weather_data WHERE date BETWEEN '2022-06-01' AND '2022-06-30' ORDER BY date;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Weather Application Development",
        "body": "Developers can utilize the Weather Insights Collection dataset to build and test applications aimed at providing users with real-time weather forecasts and alerts. By integrating this synthetic data, they can simulate various weather conditions and assess how their applications respond to different scenarios."
      },
      {
        "title": "Business Intelligence Analysis",
        "body": "Data analysts can leverage the dataset for creating business intelligence dashboards that visualize weather trends over time. By analyzing this data, they can provide insights to businesses about seasonal effects on operations and help them prepare for extreme weather events."
      },
      {
        "title": "Academic Research on Climate Patterns",
        "body": "Researchers studying climate patterns can use this dataset to model and analyze weather trends over an entire year. With access to detailed metrics such as temperature and humidity, they can derive conclusions on how climate change may be impacting local weather patterns."
      }
    ]
  },
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    "weather_data": 365
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  "stats": {
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        "temperature_c": {
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          "min": -29.9,
          "max": 49.9
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        "humidity_percentage": {
          "nulls": 48,
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          "min": 0.8,
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        "wind_speed_kmh": {
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        "alert": {
          "nulls": 0,
          "distinct": 5,
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          "max": "storm"
        },
        "sensor_status": {
          "nulls": 258,
          "distinct": 3,
          "min": "maintenance",
          "max": "operational"
        }
      }
    }
  },
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