Enterprise DATA WAREHOUSE initiative is a high investment project. The adoption of DATA WAREHOUSE will be significantly different depending upon the level of readiness of an organization. Before IMPLEMENTATION of DATA WAREHOUSE system in a firm, it is necessary to evaluate the level of the readiness of firm. A successful DATA WAREHOUSE assessment model requires a deep understanding of opportunities, challenges and influential factors that a typical firm’s DATA WAREHOUSE (DW) may include. Actually, DATA WAREHOUSE system is one of Knowledge Management and Decision Support System tools. By this system, the distributed DATA throughout organizations could be collected, extracted and integrated and with knowledge discovery and DATA mining the latent DATA can be extracted and analyzed In this paper, after reviewing the relevant literature and a comparative analysis of assessment models for organizational readiness for IMPLEMENTATION of DATA WAREHOUSE system, a conceptual framework was designed and its validity was approved by test of hypothesis. Then, by using analytical hierarchical process technique and its expert choice software, criteria and sub-criteria of influential factors were assessed and weighted. The validity and effectiveness of the model including, six criteria and 23 sub-criteria with main influential  factors named Information needs, DATA structure , Organizational processes , Organizational factors ,Technical structure and Project management were approved by a field study and the relevant statistical analysis.

Currently, the significant growth of the number of users of online services and distributed systems generate a large amount of DATAbase information at the level of DATA WAREHOUSEs and big DATA. DATA WAREHOUSEs are large collections of business DATA that help organizations and businesses make more accurate and intelligent decisions. Big DATA is also a very large collection of DATA collected from multiple sources. These DATA can be the results of evaluating the performance of an organization or the interactions of its audience in social networks. Due to the increasing importance of big DATA functions and DATA WAREHOUSEs, the issue of maintaining DATA security is the biggest threat these systems face. Basically, dealing with the category of information security and security of internet networks, DATA WAREHOUSEs and services based on big DATA, requires special attention of the organization to the position of information security and all-round security of these systems, and this category should be considered at the macro level and from the perspective of benefits and benefits. it looked The existence of security weaknesses in these systems, the lack of proper training and justification of users regardless of their point of view regarding the position and importance of security, the absence of necessary instructions to prevent security defects, the absence of specific and codified policies in order to properly and timely deal with Security flaws will lead to issues that harm all users and the operational capabilities of these systems and actually expose the information infrastructure of organizations to serious damage and threats. In this article, we are going to research the security aspects of DATA WAREHOUSEs and big DATA and examine effective and logical solutions in this area.

Introduction: Design and IMPLEMENTATION of management information systems (MIS) and in particular for the public sector, is a challenging and time consuming task. The purpose of this paper is to propose a tentative model for implementing MIS in higher education domain. Methodology: The main methodology used in this work is the design science method. Research and development patterns and prototyping have been used in this methodology to create solutions and processes. Findings: This work presents an evolved tentative model for building and implementing MIS in the higher education domain. This model consists of suggestions for proper organization, designed processes for performing steps and required operations, and also solutions to potential challenges. Given the structural similarity of different universities, using our evolved experimental model can reduce costs and fasten the IMPLEMENTATION for similar systems in higher education domain.

Near-real time DATA WAREHOUSE gives the end users the essential information to achieve appropriate decisions. Whatever the DATA are fresher in it, the decision would have a better result either. To achieve a fresh and up-to-date DATA, the changes happened in the side of source must be added to the DATA WAREHOUSE with little delay. For this reason, they should be transformed in to the DATA WAREHOUSE format. One of the famous algorithms in this area is called X-HYBRIDJOIN. In this algorithm the DATA characteristics of real word have been used to speed up the join operation. This algorithm keeps some partitions, which have more uses, in the main memory. In the proposed algorithm in this paper, disk-based relation is joined with input DATA stream. The aim of such join is to enrich stream. The proposed algorithm uses clustered index for disk-based relation and join attribute. Moreover, it is assumed that the join attribute is exclusive throughout the relation. This algorithm has improved the mentioned algorithm in two stages. At the first stage, some records of source table which are frequently accessible are detected. Detection of such records is carried out during the algorithm IMPLEMENTATION. The mechanism is in the way that each record access is counted by a counter and if it becomes more than the determined threshold, then it is considered as the frequently used record and placed in the hash table. The hash table is used to keep the frequently used records in the main memory. When the stream is going to enter in to join area, it is searched in this table. At the second stage, the choice method of the partition which is going to load in the main memory has been changed. One dimensional array is used to choose the mentioned partition. This array helps to select a partition of source table with highest number of records for the join among all partitions of source table. Using this array in each iteration, always leads to choose the best partition loading in memory. To compare the usefulness of the suggested algorithm some experiments have been done. Experimental results show that the service rate acquired in suggested algorithm is more than the existing algorithms. Service rate is the number of joined records in a time unit. Increasing service rate causes the effectiveness of the algorithm.

Diseases management offers the benefits of lower disease occurrence, improved patient care, and lower healthcare costs. The key mechanism used to identify individuals at risk, stratify patients by risk level and track patients’ progress through the disease management is the DATA WAREHOUSE (DW).This review article describes operational systems, DW features and component and role of it in disease management programs.By DATA WAREHOUSE, healthcare organizations, clinicians and managers can reduce costs generated by process redesign, obtain right information in areas of patient care, budgeting, planning, research, process improvement, external reporting, benchmarking, trend analysis and marketing and make the right decision to prevent the progression or appearance of the illness, thus maintaining the health of the population.

Considering the use of information technology and the increase of software provided by software providers, it is important to select the appropriate software from the software provided. Therefore, organizations need to have the tools to be able to examine and compare all aspects of the software offered in the tenders to select the appropriate software that meets the needs of the organization. It can be said that choosing the appropriate software system is a multi-criteria decisionmaking problem. In this paper, using the literature of research and opinions of experts, the indexes of the selection of appropriate software system are specified, then an executive model is presented to select the appropriate software from the software provided in the tenders of the organizations. . In the design of this model, the hierarchical analysis process has been used. Also, to illustrate how the model is implemented, a case study is conducted on the selection of software for DATA storage.

Several techniques exist to select and materialize a proper set of DATA in a suitable structure that manage the queries submitted to the online analytical processing systems. These techniques are called view management techniques, which consist of three research areas: 1) view selection to materialize, 2) query processing and rewriting using the materialized views, and 3) maintaining materialized views. There are several parameters should be considered in order to find the most important algorithm for view management. As various researches have been done to propose view selection algorithms, we should select and modify the most suitable algorithm for view materialization based on the properties of the applications. In this paper, we investigate and find relevant parameters to view selection algorithms and classify them based on these parameters. We also present a system to evaluate algorithms and compare them with respect to the values of the evaluation parameters. Based on the results of these activities, we propose a roadmap that helps us choose the most efficient view selection algorithm concerning application types.