![]() ![]() An analysist can then query the data using BI tools to produce useful information from the data. Remove raw story tracker manual#Organizations can feed raw data into a database or a data warehouse (one of several kinds of data repositories - see image above), which can collect raw data from many sources for automatic or manual correlating and processing. Therefore, it may use data anonymization to remove PII from the raw data or data controls and implement data retention policies to limit the risk of data leaks. This may make an organization liable for storing or transmitting it. Raw data may contain personally identifiable information ( PII). There is generally not much value in holding onto raw data without a way to use it, but as the cost of storage decreases, organizations are finding more and more value in collecting raw data for additional processing - if not right away, then later. The primary value in data is after it has been processed and interpreted. Advanced systems may use raw data for alerting purposes or with machine learning to build models of the data and its behavior. More complicated systems such as business intelligence ( BI) programs may use raw data for financial trending or forecasting purposes. A spreadsheet such as Microsoft Excel or Google sheets allows users to format, organize and graph data to reveal simple trends and help summarize data. There are many ways to process raw data, ranging from simple to complex. ![]() Cleaning raw data may require parsing the data for easier ingestion into a computer, removing outliers or spurious results and, occasionally, reformatting or translating the data - a process sometimes called massaging or crunching the data. In many instances, users must clean raw data before it can be used. Applications and devices can save raw data in various formats, but the most common format for interchanging raw data between systems is as a comma separated values (CSV) file. Examples of raw data can be financial transactions from a point of sale ( POS) terminal, computer logs or even participant eye tracking data in a research project. How it is processed and stored depend on its source and intended use, though. One notable exception is the data lake, which is a storage repository that can hold massive volumes of raw data in its native format. Usually, organizations must process raw data for it to become information when putting it in a repository to become useful. Then the data is stored and analyzed over time to produce a predictive modeling algorithm to help make better heating and cooling decisions. It can then use this processed data to meet a predetermined desired temperature for turning on and off a heater or air conditioner.įurthermore, the system may feed this temperature reading and the current time into another climate control system as that system's raw data. The system takes this voltage level as raw data and turns it into a temperature reading. Its raw data source is a temperature probe - usually read as an analog voltage level. Additionally, the final data from one system may be used as raw data in another.įor example, imagine a simple home thermostat. Extra processing is required to turn it into useful information. Finally, all this processed data that came in through the eyes, ears and memory helps you make the informed decision to cross the street or not.Ĭomputers cannot intuitively process raw data like a human mind can, however, and raw data is generally not useful on its own. Meanwhile, the ears take in raw information in the form of vibrations in the air, which the brain translates into sounds that can be interpreted as the wind, voices or a car engine. The working memory can tell you if that car is sitting still, getting bigger as it comes toward you, or getting smaller as it drives away. Then the brain takes these flashes and resolves them into objects such as street signs and cars. The eyes capture raw data as flashes of light and dark. The human brain is incredibly good at taking in raw data, processing it and using it to make decisions.įor example, imagine you are trying to cross a busy road. ![]() Tremendous amounts of raw data surround us and are produced every day. ![]() Because of processing, raw data sometimes ends up in a database, which enables the data to become accessible for further processing and analysis in a number of different ways. Raw data that has undergone processing is sometimes referred to as cooked data.Īlthough raw data has the potential to become "information," it requires selective extraction, organization and sometimes analysis and formatting for presentation. A distinction is sometimes made between data and information to the effect that information is the end product of data processing. Raw data (sometimes called source data, atomic data or primary data) is data that has not been processed for use. ![]()
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