The Indexing data structure is used to store and retrieves data in database. It is frequently being used to speed up access to particular data items. Creating an index is a very important part of databases. Tree is a best option to create indexing for database. Appropriate indexing techniques supports in reducing the space and time complexity of storage and retrieval data. Traditional index sequencing method is used to static database and homogeneous data. To retrieve heterogenous big data, conventional indexing techniques is not useful. For heterogenous big data, optimized decision-making indexing is required. If there is a requirement to create the index for string or character for searching, tree-based indexing is the best option.In this paper, alphabetic text and character-based indexing techniques have proposed for searching purpose. This proposed index technique is very useful for insertion and updating database quickly. The alphabetic text and character-based indexing serve the “Starts with” operations for autocomplete function. Text-based indexing will be more beneficial than hash-based index. Alphabetic text and Character based indexing means the indices for characters are simply the order of alphabets like ‘a’ -> 0, ‘c’ -> 2 and so on.  The proposed technique can be used to quickly get some important information of one of the fields or combination and proceed with Create, Read, Update and Delete operations.  Experimental results show that alphabetic text indexing is better then hash-based indexing for insertion, deletion and updating of database.

The development of artificial intelligence (AI) technology expands the boundary of business practice, inducing the emergence and application of business intelligence (BI) that has promoted the transformation of information techniques to optimize business decision and operation. Along with the Tunisian National Tourist office, we have conducted a real study for transforming one of some relational structures of their data base into Data cubes that will later form their new Data Warehouse.

This article aims to explore factors contributing to the failure and abandonment of information system project in Malaysia. Also, the researchers have analyzed the critical Measurement organizational value (MOV) for such project. We have conducted nearly 25 questionnaires with leader expert in government linked agencies in Malaysia to analyze their experience in such cases. These factors include poor project impetus, uninvolved management, unqualified people, inaccurate expectations, project mismanagement, strategy misalignment, poor participation, hostile culture, insufficient budget, conflating technical and managerial problems, previous project trauma and underestimated complexity The results suggest that failure and abandonment are provoked by combinations of factors relating to team member qualifications and experience, to the management and organization of the project system, as well as to strategic alignment and changes in the organization’s internal structure.