Natural gas storage-tank water heaters use almost 50 percent less energy, costing less to operate, than the electric variety. Typically, there are storage-tank water heaters that use either natural gas or electricity for their fuel. A pipe emerges from the top to deliver hot water to its destination, kitchen, bathroom, or other sinks. Their components are an insulated tank, typically holding 30-50 gallons of water, to heat and store the water until it’s needed. Storage tank water heaters are commonly found in most homes. How are “Traditional” Tank Storage Water Heaters Different? These types of water heaters were found to be 22 percent more energy efficient on average than the gas-fired storage-tank models in tests conducted by Consumer Reports. Tankless water heaters are usually powered with electricity or gas. Tankless water heaters, also known as on-demand water heaters, use high-powered burners to rapidly heat water as it runs through a heat exchanger and deliver it directly to your faucets or shower without storing it in a tank. We’ll examine the pros and cons of tankless and traditional water heaters so you can make an informed decision. We’ve put together this comparison of storage water heaters vs tankless water heaters to help homeowners and contractors decide on the type of water heater that’s best for you. That’s why when it’s time to equip your new home, or replace your old water heater it’s important to consider cost, efficiency, and longevity of your new water heater. For example, we could use a scale of 0 (totally unreliable) to 1 (totally reliable).Water heaters can be a costly investment for home owners that you’ll be living with for over a decade. How much will it cost us to obtain the data we need? How much benefit will applying the business objective give us? Ideally, we should be able to quantify the reliability by assigning a number to each variable. The choice of course will probably be a cost/benefit one. Second, we may decide to change the business objective so that the required variables are ones we already have. We may decide to launch a campaign to obtain key missing data, via customer surveys, online questionnaires, or by deriving it from other currently available data. If the data is not available or it's not reliable, we may choose one of several options. For example, we could have cases of VIP clients who are also insolvent. This may be because the customer tends to make up a value instead of entering the true one, because of an error during data entry, or created by an automated data process. Or the disposable income may be entered in 80 percent of the records but 40 percent of the time it doesn't tie in with the other socio-economic indicators we have about the customer. The ZIP code may be entered in 100 percent of the records but in 50 percent of the records it doesn't comply with the correct format. However, the disposable income and cell-phone usage variables may be incomplete because we don't currently collect that information or the customer is not willing to supply it.Īnother aspect of reliability is what is recorded in the data variable. The ZIP code, marital status, and homeowner data may also be easily obtainable based on product/service type. In our example, the information about the purchase of a product B could be readily available, as well as the time as customer. Other businesses, such as retail, rely on customer loyalty cards to obtain additional customer demographic information. Banks and insurance companies tend to have a large amount of demographic data, which the customer has to supply in order to contract for a financial product. Depending on our type of business, we may have more opportunities to obtain data about our customers. We do this by checking, for each variable, what percentage of the data records have a value. The initial list could include whether the customer purchased product B, disposable income, homeownership, marital status, how long they've been a customer, ZIP code, and cell phone use.įirst, we evaluate the reliability of the variables. For example, consider that we want to predict if a customer will buy product A based on a set of variables we think are related. Here's how to address this situation.īy David Nettleton, Contract Researcher, Web Research Group, Pompeu Fabra UniversityĪ data mart should be designed with specific business objectives in mind, and we should plan to obtain the data we need for those objectives. When evaluating variable data for a given business intelligence objective, we may observe that the relevant variables are not reliable or that the reliable ones are not relevant. Data Quality: Relevance versus Reliability
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