Design of a Multidimensional Model Using Object Oriented Features in UML

A data warehouse is a single repository of data which includes data generated from various operational systems. Conceptual modeling is an important concept in the successful design of a data warehouse. The Unified Modeling Language (UML) has become a standard for object modeling during analysis and design steps of software system development. The paper proposes an object oriented approach to model the process of data warehouse design. The hierarchies of each data element can be explicitly defined, thus highlighting the data granularity. We propose a UML multidimensional model using various data sources based on UML schemas. We present a conceptual-level integration framework on diverse UML data sources on which OLAP operations can be performed. Our integration framework takes into account the benefits of UML (its concepts, relationships and extended features) which is more close to the real world and can model even the complex problems easily and accurately. Two steps are involved in our integration framework. The first one is to convert UML schemas into UML class diagrams. The second is to build a multidimensional model from the UML class diagrams. The white-paper focuses on the transformations used in the second step. We describe how to represent a multidimensional model using a UML star or snowflake diagram with the help of a case study. To the best of our knowledge, we are the first people to represent a UML snowflake diagram that integrates heterogeneous UML data sources

Characteristics and Challenges of Big Data

In today’s digital-era, we are bowed down by the massive data that is generated at exponential rates. Technically, this massive data is referred to as Big Data. Simultaneously, the need to manage Big Data arises. Big Data, due to its high volume, velocity, veracity, value, variety, leads to various issues. In this paper, we talk about the various challenges faced because of the exorbitant amount of data. We not only face challenges in processing, but also in designing, analysing, storage, management, privacy and security issues

An approach to Design Object Oriented Data Warehouse

Data warehouses are repository of data from wide range of sources that provide analytical results for making significant business decisions. As data warehouse has to support different complex queries therefore the design technique should be different from the traditional ones. The best suited technique is object oriented data warehouse design technique which is collection of objects that interact with each other. That further enhances the decision making capability of Data Warehouse. In our paper we illustrate a technique for designing of a relational schema from an object model, represent in their UML form and then transformed it into data warehouse. We also draw the trace diagram that actually

Swarm Intelligence Based Data Mart Maintenance

Data mart is the concise and user specific version of data warehouse. It is basically a confined data warehouse for manipulator to access data of his interest. The data within data mart is used to make strategic decision which relies severely on the accurate repossession of details. Therefore it is essential to brush up the data mart periodically so that the end user gets updated and accurate information. To accomplish this purpose, an efficient and effective method is required for optimizing the process of maintenance. This paper presents an algorithm to maintain the data mart using ant colony optimization. This algorithm uses the concept of clustering and meta-heuristic techniques to maintain and search the element in the data mart. The paper discusses the proposed algorithm for protein data bank and shows the effectiveness of the algorithm to maintain the data mart. The searching time is the main issue of concern. The technique described in the paper reduces the search time effectively