Big Data

    Types of Big Data Analytics Data

    With the gradual development of big data, there is more and more data, and data analysis is especially important.
    Updated:
    Types of Big Data Analytics Data

    With the gradual development of big data, more and more data, data analysis is particularly important, then, what types of data for big data analysis? Let's take a look!

    1. TRANSACTION DATA

    Big data platforms can access a larger time span, more massive structured transaction data, so that a wider range of transaction data types can be analyzed, including not only POS or e-commerce shopping data, but also behavioral transaction data, such as Web server records of Internet clickstream data logs.

    2. HUMAN-GENERATED DATA

    Unstructured data is widely available in emails, documents, images, audio, video, and data streams generated through blogs, wikis, and especially social media. These data provide a rich source of data for analysis using text analysis functions.

    3. MOBILE DATA

    Smartphones and tablets with Internet access are becoming more and more common. Apps on these mobile devices are capable of tracking and communicating a myriad of events, from transaction data within the app (e.g., a recorded event for a product search) to personal information or status reporting events (e.g., a change in location that reports a new geocode).

    4. MACHINE AND SENSOR DATA

    This includes data created or generated by functional devices, such as smart meters, smart temperature controllers, factory machines, and Internet-connected home appliances. These devices can be configured to communicate with other nodes in the interconnected network and can also automatically transmit data to a central server so that the data can be analyzed.

    Machine and sensor data are prime examples of what is generated from the emerging Internet of Things (IoT). Data from the IoT can be used to build analytical models, continuously monitor predictive behavior (e.g., identifying when sensor values indicate a problem), and provide prescribed instructions (e.g., alerting technicians to check equipment before something really goes wrong).

    The types of data for big data analytics are basically the four types above, and we can only better choose to make good use of data analytics tools if we understand the types of data.

    Related Articles