Unstructured data is unfiltered information to which a fixed editing policy is not applied. It is often referred to as raw data. Common examples are internet logs, XML, JSON, text documents, images, videos and audio files. Unstructured data is searched and analyzed to extract useful facts. Up to 80% of enterprise data is unstructured. This means that it is the type of big data that is most visible to many people. The size of unstructured data requires scalable analytics to generate insights. Unstructured data is present in most, but not all, data lakes due to low storage costs.
In AI and machine learning projects, instead of processing raw data directly, it is necessary to make it more meaningful and processable. An important concept that comes into play at this point is Embedding.
İş analitiği, işletme verilerinin toplanması, analiz edilmesi ve anlamlı içgörüler elde edilmesi sürecidir. Temel amacı, şirketlerin stratejik ve operasyonel karar alma süreçlerini desteklemektir.
Regresyon, istatistiksel modelleme ve veri analizi süreçlerinde bağımlı bir değişken (sonuç) ile bir veya daha fazla bağımsız değişken (girdi) arasındaki ilişkiyi inceleyen bir tekniktir.
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