This pricing is influenced by several factors, including the quantity of data sources, data volume, complexity, data processing methods (batch, real-time, or combination), security and compliance requirements, and the chosen deployment model.

There are three main types of big data:

Structured data: its tabular format, includes information such as customer demographics, financial transactions, and sales data. This data type lends itself well to organization and can be efficiently sorted and queried using Business Intelligence (BI) tools.

Unstructured data: Unstructured data, on the other hand, lacks a predefined organizational structure and requires advanced technologies such as AI, ML, natural language processing (NLP), and optical character recognition (OCR) for meaningful processing. Examples of unstructured data encompass text, images, videos, and audio recordings. For instance, a company can employ NLP to analyze customer social media posts and gauge sentiment towards its services.

Semi-structured data: data falls somewhere between the two previous data types. While its elements can be assigned to specific fields or tags, they are not always readily suitable for querying or analytics. An illustrative example of semi-structured data is an email, which consists of a subject line and a message body. In this case, the subject line and the message text can be assigned to their respective tagged fields and later processed using techniques commonly applied to unstructured data.

Cloud solutions offer numerous benefits, including cost savings, scalability, data security, and improved accessibility. They also enable remote work and enhance collaboration among your team members.

No business is too small or too large for cloud consulting. We work with businesses of all sizes, from startups to enterprises, to tailor solutions that fit their unique requirements.