Читать книгу Big Data - Seifedine Kadry - Страница 29

The data aggregation phase of the big data life cycle involves collecting the raw data, transmitting the data to the storage platform, and preprocessing them. Data acquisition in the big data world means acquiring the high‐volume data arriving at an ever‐increasing pace. The raw data thus collected is transmitted to a proper storage infrastructure to support processing and various analytical applications. Preprocessing involves data cleansing, data integration, data transformation, and data reduction to make the data reliable, error free, consistent, and accurate. The data gathered may have redundancies, which occupy the storage space and increase the storage cost and can be handled by data preprocessing. Also, much of the data gathered may not be related to the analysis objective, and hence it needs to be compressed while being preprocessed. Hence, efficient data preprocessing is indispensable for cost‐effective and efficient data storage. The preprocessed data are then transmitted for various purposes such as data modeling and data analytics.