{
  "format": "dataset-manifest/1",
  "slug": "smart-home-energy-saver-app",
  "version": 2,
  "seed": "smart-home-energy-saver-app:1",
  "spec": {
    "format": "dataset/1",
    "slug": "smart-home-energy-saver-app",
    "name": "Home Energy Management Insights",
    "tagline": "User energy consumption patterns, appliance data, and electricity tariffs for sustainable home management.",
    "description": "Families optimize their electricity consumption with energy management solutions that track usage patterns and device performance. Households engage in monitoring their energy habits, responding to shifting electricity tariffs, and managing monthly bills. Their daily routines create fluctuations in energy demand, typically peaking in the evening as heating and lighting devices are heavily utilized. This synthetic dataset captures these dynamics by providing insights into how users interact with their energy consumption and the devices they use.\n\nThe dataset features four key tables: users, energy_usage, devices, and electricity_tariffs. Each user row represents an individual household, detailing their unique profile and energy management practices. The energy_usage table records the energy consumption patterns associated with each user, allowing developers to analyze trends over time. The devices table provides information on the different appliances and systems in use within each household, showcasing how they contribute to overall energy usage. Lastly, the electricity_tariffs table outlines the various pricing plans available to users, which can influence their consumption decisions.\n\nDevelopers can leverage this dataset to answer critical questions such as: How do specific devices impact overall energy consumption? What trends can be identified in energy usage related to different tariff plans? How do household routines influence peak usage times? By exploring these aspects, developers can practice their skills in data analysis, query writing, and data visualization, gaining a better understanding of energy management.\n\nThis is a synthetic dataset that simulates real-world interactions within home energy management systems, making it an excellent resource for those looking to hone their analytical skills in the energy domain.",
    "domain": "energy",
    "shape": "time-series",
    "useCases": [
      "analytics-demo",
      "bi-dashboards"
    ],
    "keywords": [
      "energy management",
      "sustainability",
      "smart homes",
      "consumption patterns",
      "electricity tariffs"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "users": {
        "description": "This table holds information about users of the energy management app. Each user has a unique identifier, along with personal details to understand their demographics.",
        "rows": 100,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each user."
          },
          "full_name": {
            "kind": "fullName",
            "description": "The full name of the user.",
            "nullable": true
          },
          "email": {
            "kind": "email",
            "from": "full_name",
            "description": "Email address of the user.",
            "nullable": true
          },
          "city": {
            "kind": "city",
            "description": "City where the user resides.",
            "nullable": true
          },
          "country": {
            "kind": "country",
            "from": "city",
            "description": "Country of residence.",
            "nullable": true
          }
        }
      },
      "energy_usage": {
        "description": "This table records energy consumption data for each user. It captures daily usage amounts along with timestamps to track patterns over time.",
        "rows": {
          "per": "users",
          "via": "user_id",
          "min": 3,
          "max": 15,
          "skew": "long-tail"
        },
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each energy usage record."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "References the user to whom this usage belongs."
          },
          "usage_kwh": {
            "kind": "decimal",
            "min": 0,
            "max": 100,
            "scale": 2,
            "description": "Energy usage in kilowatt-hours.",
            "distribution": "normal"
          },
          "timestamp": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Timestamp of when the usage was recorded.",
            "dayProfile": "waking"
          }
        }
      },
      "devices": {
        "description": "This table contains information about the devices used by each user in their households. Each device is linked to the user who owns it.",
        "rows": {
          "per": "users",
          "via": "user_id",
          "min": 1,
          "max": 5,
          "skew": "long-tail"
        },
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each device."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "References the user who owns this device."
          },
          "device_name": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Name of the device, such as 'Refrigerator' or 'Smart Thermostat'.",
            "pool": [
              "Refrigerator",
              "Smart",
              "Thermostat",
              "Washer",
              "Dryer",
              "Oven",
              "Microwave",
              "Dishwasher",
              "Air",
              "Conditioner",
              "Heater",
              "Fan",
              "Light",
              "Bulb",
              "Speaker",
              "Camera",
              "Sensor",
              "Controller",
              "Hub",
              "Switch",
              "Outlet",
              "Plug",
              "Monitor",
              "Tracker",
              "Charger",
              "Generator",
              "Battery",
              "Pool",
              "Pump",
              "Water-heater",
              "Smartwatch",
              "Scale",
              "Thermometer",
              "Humidifier",
              "Dehumidifier",
              "Air-purifier",
              "Vacuum",
              "Robot",
              "Blender",
              "Coffee",
              "Maker",
              "Toaster",
              "Electric",
              "Kettle",
              "Rice-cooker",
              "Slow-cooker",
              "Pressure-cooker"
            ]
          },
          "power_rating_watts": {
            "kind": "int",
            "min": 10,
            "max": 3000,
            "description": "The power rating of the device in watts.",
            "distribution": "long-tail"
          }
        }
      },
      "electricity_tariffs": {
        "description": "This table outlines the electricity tariffs applicable to each user. Tariffs can vary based on time of day or consumption levels.",
        "rows": 100,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each tariff record."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "References the user associated with this tariff."
          },
          "tariff_name": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Name of the electricity tariff plan.",
            "nullable": true,
            "pool": [
              "Standard",
              "Time-of-use",
              "Flat-rate",
              "Tiered",
              "Prepaid",
              "Green",
              "Dynamic",
              "Variable",
              "Fixed",
              "Renewable",
              "Discounted",
              "Peak",
              "Off-peak",
              "Critical",
              "Demand",
              "Seasonal",
              "Block",
              "Residential",
              "Commercial",
              "Industrial",
              "Time-varying",
              "Net-metering",
              "Feed-in",
              "Smart-grid",
              "Incentive",
              "Rate",
              "Utility",
              "Wholesale",
              "Community",
              "Solar",
              "Wind",
              "Biomass",
              "Hydro",
              "Geothermal",
              "Electric-vehicle",
              "Time-based",
              "Load-management",
              "Capacity",
              "Usage-based",
              "Billing",
              "Subscription",
              "Contract",
              "Plan"
            ]
          },
          "rate_per_kwh": {
            "kind": "decimal",
            "min": 0.05,
            "max": 0.3,
            "scale": 2,
            "description": "Cost of electricity per kilowatt-hour.",
            "distribution": "long-tail"
          },
          "effective_date": {
            "kind": "date",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Date when the tariff became effective.",
            "nullable": true,
            "trend": "seasonal"
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "timestamped",
      "monetary",
      "high-cardinality"
    ],
    "analysisQuestions": [
      "What are the peak energy consumption hours for users?",
      "How do different devices impact overall energy usage?",
      "What is the average cost of electricity for users based on their tariffs?",
      "Are there any noticeable trends in energy consumption over the months?",
      "How does the energy usage vary between different user demographics?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Users and Energy Usage",
        "sql": "SELECT u.full_name, e.usage_kwh FROM users u JOIN energy_usage e ON u.id = e.user_id",
        "dialect": "postgres"
      },
      {
        "title": "Average Energy Usage by User",
        "sql": "SELECT user_id, AVG(usage_kwh) AS avg_usage FROM energy_usage GROUP BY user_id",
        "dialect": "postgres"
      },
      {
        "title": "Total Usage Over Time",
        "sql": "SELECT DATE(timestamp) AS usage_date, SUM(usage_kwh) AS total_usage FROM energy_usage GROUP BY usage_date ORDER BY usage_date",
        "dialect": "postgres"
      },
      {
        "title": "Cost Calculation by Tariff",
        "sql": "SELECT u.full_name, SUM(e.usage_kwh * t.rate_per_kwh) AS total_cost FROM users u JOIN energy_usage e ON u.id = e.user_id JOIN electricity_tariffs t ON u.id = t.user_id GROUP BY u.full_name",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Homeowners Monitoring Energy Usage",
        "body": "Homeowners can utilize the data from this dataset to monitor their energy consumption patterns over time. By analyzing their daily usage, they can identify peak consumption hours and adjust their habits, such as running appliances during off-peak hours to save on electricity bills."
      },
      {
        "title": "Energy Management Application Development",
        "body": "Developers can use this dataset to create energy management applications that provide real-time insights to users. With a focus on sustainability, these applications can help users optimize their energy consumption and reduce their overall carbon footprint."
      },
      {
        "title": "Utility Companies Analyzing Tariff Impact",
        "body": "Utility companies can analyze the impact of different electricity tariffs on user consumption patterns. By understanding how tariffs affect usage, they can design better pricing models that encourage energy conservation and improve customer satisfaction."
      },
      {
        "title": "Researchers Studying Energy Efficiency",
        "body": "Researchers can leverage this dataset to study energy efficiency trends across different demographics. By examining the correlation between device usage and energy consumption, they can identify opportunities for promoting energy-efficient appliances and practices."
      }
    ]
  },
  "counts": {
    "users": 100,
    "devices": 231,
    "electricity_tariffs": 100,
    "energy_usage": 697
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