Abstract
Traditional business intelligence (BI) and data warehouse (DW) solutions use structured data extensively. Database platforms such as Oracle, Informatica, and others had limited capabilities to handle and manage unstructured data such as text, media, video, and so forth, although they had a data type called CLOB and BLOB; which were used to store large amounts of text, and accessing data from these platforms was a problem. With the advent of multistructured (a.k.a. unstructured) data in the form of social media and audio/video, there has to be a change in the way data is ingested, preprocessed, validated, and/or cleansed and integrated or co-related with nontextual formats. This chapter deals with the following topics:
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© 2013 Nitin Sawant
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Sawant, N., Shah, H. (2013). Big Data Ingestion and Streaming Patterns . In: Big Data Application Architecture Q & A. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4302-6293-0_3
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DOI: https://doi.org/10.1007/978-1-4302-6293-0_3
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4302-6292-3
Online ISBN: 978-1-4302-6293-0
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