ISC 02 Data Management
     Remembering and Understanding: Identify data collection methods and techniques.

    In this section, the task is Remembering and Understanding: Identify data collection methods and techniques.

    Let's start with primary data collection methods. One common method is surveys and questionnaires, which involve the use of structured forms with a set of questions to gather data.

    Examples of this include online surveys distributed via email and paper questionnaires handed out at events. Another method is interviews, which involve conducting one-on-one or group discussions to gather in-depth information. This could be telephone interviews for market research or in-person interviews for academic research.

    Then there's observations. This method entails directly observing and recording behaviors or events as they occur. For instance, watching how shoppers navigate a store or observing interactions in a focus group. Experiments are also a primary data collection method. They involve controlled scenarios where variables are manipulated to study their effects, like clinical trials for a new drug or A/B testing for a website design.

    Moving on to secondary data collection methods, we have data mining. This involves extracting patterns from large datasets using algorithms and statistical methods. Examples include analyzing customer purchase histories to identify sales trends or reviewing website logs to understand user behavior.

    Another secondary method is database retrieval, which involves accessing stored data from databases. This can include retrieving historical sales data from a company's ERP system or accessing public data sets from government websites. Document review is also a secondary method, involving analyzing existing records and documents to extract data, such as reviewing archive to news articles or studying financial statements for historical trends.

    Lastly, we have automated data collection methods. Sensors and IoT devices are used to automatically collect data from environments. Examples include wearable fitness trackers measuring heart rate and steps or industrial sensors measuring temperature or pressure in machinery. Web scraping is another automated method, which involves extracting data from websites programmatically, like collecting product prices from e-commerce sites or extracting news headlines from media websites. Finally, there are application programming interfaces, or APIs, which are interfaces provided by platforms to programmatically access and retrieve data.

    Examples here include fetching tweets from Twitter's API or accessing weather data from a weather service API.

    Remembering and Understanding: Define the various types of data storage (e.g., data warehouse, data lake, data mart) and database schemas (e.g., star, snowflake).
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