{
  "format": "dataset-manifest/1",
  "slug": "interactive-home-energy-efficiency-and-savings-planner",
  "version": 2,
  "seed": "interactive-home-energy-efficiency-and-savings-planner:1",
  "spec": {
    "format": "dataset/1",
    "slug": "interactive-home-energy-efficiency-and-savings-planner",
    "name": "Home Energy Efficiency Insights",
    "tagline": "Homeowners' energy consumption patterns, appliances, solar installations, utility tariffs, and energy-saving tips data.",
    "description": "Homeowners engage in energy efficiency projects to optimize their energy consumption and increase savings. They analyze various facets of their energy usage, including choices of energy providers, the types of appliances used, and the impact of solar installations. This dataset illustrates how homeowners interact with different energy providers and the utility tariffs associated with their plans, helping them make informed decisions about their energy consumption and potential savings. \n\nThe dataset comprises several tables which illustrate different aspects of this energy efficiency journey. The 'homeowners' table holds information about individual homeowners and their energy consumption profiles. The 'energy_providers' table details the various energy providers available, outlining the services they offer and the utility tariffs they set. By joining the homeowners with the energy_providers table, one can assess how provider choice influences energy usage patterns. Meanwhile, the 'appliances' table contains data about the types of appliances used in homes, allowing users to explore how appliance efficiency correlates with energy consumption. The 'solar_installations' table sheds light on homeowners who have adopted solar energy solutions, providing insight into the growing trend of renewable energy adoption. The 'utility_tariffs' table provides crucial context about the costs associated with energy usage, while the 'energy_saving_tips' table offers practical advice homeowners can use to reduce their consumption. \n\nThis dataset answers questions around energy consumption habits, the financial impact of different energy providers, and the effectiveness of various energy-saving measures. It is particularly useful for practicing skills in data analysis, including querying relationships between different energy efficiency measures and modeling consumption patterns. It’s important to note that all of the data presented here is synthetic, designed to mimic real-world scenarios without compromising any personal information.",
    "domain": "energy",
    "shape": "time-series",
    "useCases": [
      "analytics-demo",
      "bi-dashboards"
    ],
    "keywords": [
      "energy consumption",
      "savings potential",
      "home efficiency",
      "solar installations",
      "utility tariffs",
      "energy providers"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "homeowners": {
        "description": "This table records data on individual homeowners, including their demographics and energy preferences. Each homeowner can have multiple appliance and energy usage records linked through foreign keys.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each homeowner."
          },
          "age": {
            "kind": "int",
            "min": 25,
            "max": 75,
            "description": "Age of the homeowner."
          },
          "location": {
            "kind": "city",
            "description": "City where the homeowner resides."
          },
          "energy_provider_id": {
            "kind": "fk",
            "ref": "energy_providers.id",
            "description": "Reference to the energy provider."
          }
        }
      },
      "energy_providers": {
        "description": "This table lists various energy providers available to homeowners, including their tariff plans and incentives offered. Homeowners are linked to energy providers to reflect their choices.",
        "rows": 50,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each energy provider."
          },
          "name": {
            "kind": "fullName",
            "description": "Name of the energy provider."
          },
          "tariff_plan": {
            "kind": "enum",
            "values": [
              "Standard",
              "Green",
              "Time-of-Use"
            ],
            "description": "Type of tariff plan offered by the provider.",
            "weights": [
              6,
              2,
              1
            ]
          },
          "rebate_incentives": {
            "kind": "decimal",
            "min": 0,
            "max": 1000,
            "scale": 2,
            "description": "Rebate incentives provided by the energy provider.",
            "distribution": "long-tail"
          }
        }
      },
      "appliances": {
        "description": "This table captures data on appliances used by homeowners, including their energy ratings and usage patterns. Each homeowner can have multiple appliances linked through foreign keys.",
        "rows": 600,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each appliance."
          },
          "homeowner_id": {
            "kind": "fk",
            "ref": "homeowners.id",
            "description": "Reference to the homeowner who owns the appliance."
          },
          "appliance_type": {
            "kind": "enum",
            "values": [
              "Refrigerator",
              "Washing Machine",
              "Heater",
              "Air Conditioner"
            ],
            "description": "Type of appliance.",
            "weights": [
              5,
              4,
              3,
              2
            ]
          },
          "energy_rating": {
            "kind": "enum",
            "values": [
              "A",
              "B",
              "C",
              "D"
            ],
            "description": "Energy efficiency rating of the appliance.",
            "weights": [
              7,
              5,
              3,
              1
            ]
          },
          "usage_hours_per_week": {
            "kind": "int",
            "min": 1,
            "max": 168,
            "description": "Average number of hours the appliance is used per week.",
            "distribution": "long-tail"
          }
        }
      },
      "solar_installations": {
        "description": "This table tracks solar installations at homeowners' properties, including installation dates and capacity. It allows analysis of solar adoption trends over time.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each solar installation."
          },
          "homeowner_id": {
            "kind": "fk",
            "ref": "homeowners.id",
            "description": "Reference to the homeowner who installed the solar system."
          },
          "installation_date": {
            "kind": "date",
            "from": "2015-01-01",
            "to": "2023-12-31",
            "description": "Date when the solar installation took place.",
            "trend": "growing"
          },
          "capacity_kw": {
            "kind": "decimal",
            "min": 1,
            "max": 10,
            "scale": 2,
            "description": "Capacity of the solar installation in kilowatts.",
            "distribution": "normal"
          }
        }
      },
      "utility_tariffs": {
        "description": "This table provides historical utility tariff data, including changes over time and their impact on homeowner choices. It links to the energy providers and can be analyzed for trends.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each utility tariff record."
          },
          "energy_provider_id": {
            "kind": "fk",
            "ref": "energy_providers.id",
            "description": "Reference to the energy provider for this tariff."
          },
          "effective_date": {
            "kind": "date",
            "from": "2015-01-01",
            "to": "2023-12-31",
            "description": "Date when the tariff became effective.",
            "trend": "seasonal"
          },
          "rate_per_kwh": {
            "kind": "decimal",
            "min": 0.05,
            "max": 0.5,
            "scale": 4,
            "description": "Rate charged per kilowatt-hour.",
            "distribution": "high"
          }
        }
      },
      "energy_saving_tips": {
        "description": "This table catalogs various energy-saving tips and their effectiveness ratings based on homeowner feedback. Each tip can be linked to the homeowner's overall energy savings.",
        "rows": 100,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each energy-saving tip."
          },
          "tip_description": {
            "kind": "sentence",
            "description": "Description of the energy-saving tip."
          },
          "effectiveness_rating": {
            "kind": "int",
            "min": 1,
            "max": 5,
            "description": "Effectiveness rating based on homeowner feedback.",
            "distribution": "high"
          },
          "adopted_by_homeowner_id": {
            "kind": "fk",
            "ref": "homeowners.id",
            "nullable": true,
            "description": "Reference to the homeowner who adopted the tip, if applicable."
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "timestamped",
      "categorical",
      "nullable",
      "high-cardinality"
    ],
    "analysisQuestions": [
      "What are the most common appliances used by homeowners, and how do their energy ratings vary?",
      "How has the adoption of solar installations changed over the past few years?",
      "What is the impact of different utility tariffs on homeowner energy consumption?",
      "Which energy-saving tips are considered the most effective by homeowners?",
      "How do energy provider choices correlate with rebates and savings?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Homeowners with Energy Providers",
        "sql": "SELECT homeowners.id, homeowners.age, energy_providers.name FROM homeowners JOIN energy_providers ON homeowners.energy_provider_id = energy_providers.id;",
        "dialect": "postgres"
      },
      {
        "title": "Count Appliances by Type per Homeowner",
        "sql": "SELECT homeowner_id, appliance_type, COUNT(*) FROM appliances GROUP BY homeowner_id, appliance_type;",
        "dialect": "postgres"
      },
      {
        "title": "Average Rate per KWh by Energy Provider",
        "sql": "SELECT energy_provider_id, AVG(rate_per_kwh) FROM utility_tariffs GROUP BY energy_provider_id;",
        "dialect": "postgres"
      },
      {
        "title": "Solar Installations Over Time",
        "sql": "SELECT EXTRACT(YEAR FROM installation_date) AS year, COUNT(*) FROM solar_installations GROUP BY year ORDER BY year;",
        "dialect": "postgres"
      },
      {
        "title": "Effectiveness of Energy-Saving Tips",
        "sql": "SELECT tip_description, AVG(effectiveness_rating) FROM energy_saving_tips GROUP BY tip_description;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Energy Analysts",
        "body": "Energy analysts can utilize this dataset to identify trends in energy consumption across different demographics. By examining appliance usage patterns and the effectiveness of energy-saving tips, they can provide insights to homeowners on how to reduce their energy bills. This analysis can also help energy providers tailor their offerings to better meet consumer needs."
      },
      {
        "title": "Home Energy Auditors",
        "body": "Home energy auditors can leverage this dataset to assess how different homeowners interact with energy efficiency measures. By understanding the common appliances in use and the impact of solar installations, auditors can recommend customized energy-saving strategies that align with the homeowner's lifestyle and preferences."
      },
      {
        "title": "Utility Companies",
        "body": "Utility companies can use this data to analyze the effectiveness of their tariff plans and rebate incentives. By understanding which plans are most popular and how they affect energy consumption, they can make informed decisions about future pricing strategies and incentive programs to encourage energy efficiency among their customers."
      },
      {
        "title": "Researchers",
        "body": "Researchers focusing on energy efficiency can use this dataset to study the factors influencing homeowner decisions regarding energy usage. They can analyze trends over time, such as the adoption of solar technology, and evaluate the efficacy of various energy-saving tips, thus contributing to the broader understanding of energy consumption behaviors."
      }
    ]
  },
  "counts": {
    "energy_providers": 50,
    "homeowners": 300,
    "appliances": 600,
    "energy_saving_tips": 100,
    "solar_installations": 150,
    "utility_tariffs": 200
  },
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