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The research looks at the concepts associated with data warehousing. These include: cloud computing and big data analytics. By analyzing the growth of these technologies, it is possible to tell the trend in which data will take in the coming future. A lot of data is in use at the moment in very large packets and volumes. The technologies that are associated with data use are associated with data use are immense and greatly spread across all computing gadgets in use. Cell phones, microcomputers, and other computing gadgets all take advantage of data warehousing technology. The research presents a case for the proliferated use of big data technologies across the world. Data use, and data users are separated using the concept of 'abstraction.' As users continue to use big data analytics and warehousing more often, they are less aware of the dangers and concerns in the use and reliance of virtual computing facilities. The study seeks to establish the influence of current technologies on data warehousing and how they lead to the growth of data storage units across the globe. The survey on data warehousing trends is focused on software technologies that highly rely on the data warehousing facilities. Social media is acknowledged as one of the leading factors behind the growth of data warehousing facilities. This research seeks to establish the use of data in social media and other applications. The concept of data analytics is stressed as a key issue in data warehousing. Being that the data in warehouses is highly sophisticated and voluminous; the need for specialized software to undertake sorting and searching purposes is reviewed. The study seeks to establish that the use of big data is an important concept as well. This concept is evaluated and well explained. The concerns with data warehousing are also evaluated in an effort to realize more need to secure data. The research concludes with an appeal for user awareness on data warehouse capabilities. Users are expected to be more aware of the purpose and capability of data and in essence, use these facilities from a professional point of view; not as novices.

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An Intelligent Information Retrieval (IIR) is a machine learning system used by users to retrieve the massive volume of information available through internet. IIR offers personalization and efficiency in the current internet development allowing users to examine and acquire appropriate information. The paper will focus on the keyword searching issues of the current digital library system. The paper will analyze a model that solves the issue using metadata case-based and concept-based approach. The objective is to evaluate a set of categories and concepts in the domain field that demonstrates some relations between them to elaborate how poor quality of information retrieval in digital library system can be solved. The paper further argued that the already developed domain-specific ontology can be efficient for query advancement. Many researchers have used semantic retrieval technology using concepts to solve problems that lack semantics in traditional retrieval technology. Using concepts in ontology enhances search results