A5090225150- Advanced Database Systems and Queries
- Data Management and Algorithms
- Cloud Computing and Resource Management
- Data Quality and Management
- Advanced Data Storage Technologies
- Data Stream Mining Techniques
- Teaching and Learning Programming
- Distributed and Parallel Computing Systems
- Educational Games and Gamification
- Advanced Malware Detection Techniques
- Smart Grid Security and Resilience
- Network Security and Intrusion Detection
- Big Data and Business Intelligence
- Online Learning and Analytics
University of Management and Technology
2019-2023
Government Sadiq College Women University
2017
Learning to program involves acquisition of various skills including problem solving, fundamental design techniques as well critical thinking. Generally, most the novice programmers struggle develop all these important skill. The research community has addressed in many different ways while involving improvisations curriculum, pedagogical methods, cognitive aspects, supporting tools, and designing assessments. This aims analyze synthesize existing literature aforementioned areas. Research...
Contribution: Recently, real-time data warehousing (DWH) and big streaming have become ubiquitous due to the fact that a number of business organizations are gearing up gain competitive advantage. The capability organizing in efficient manner reach decision empowers terms stream processing. A systematic literature review for processing systems is presented this paper which rigorously look at recent developments challenges can serve as guide implementation framework all shapes streams....
Data warehousing has been indispensable to enterprises for decades. However, infrequently updated data warehouse environment does not support quicker business decisions and faster recovery in case of transformation or load issue. Implementation real-time provides solution update problems enterprises. Efficient stream processing un-structured(NoSQL) structured(SQL) from various sources is required the successful implementation warehousing. We have done an analysis between un-structured...
As rapid decision making in business organizations gain popularity, the complexity and adaptability of extract, transform, load (ETL) process near real-time data warehousing has dramatically increased. The most important part warehouse is to feed new from different sources on near-real-time basis. However, this not format therefore, it needs be transformed into required by using transformation algorithms which essential ETL process. A semi-stream join algorithm implement transformation, for...
Near-real-time data warehousing is an emerging area of research in order to meet the high and up-to-date demands business organizations. This means customers transactions executed at source level need reflect into warehouse immediately that requires semi-stream join between a stream customer disk-based master data. For this purpose well-known algorithm called CACHEJOIN was presented literature. Due sequential execution both its phases, stream-probing phase disk-probing phase, cannot exploit...
Streaming data join is a critical process in the field of near-real-time warehousing. For this purpose, an adaptive semi-stream algorithm called CACHEJOIN (Cache Join) focusing non-uniform stream provided literature. However, cannot exploit memory and CPU resources optimally consequently it leaves its service rate suboptimal due to sequential execution both phases, stream-probing (SP) phase disk-probing (DP) phase. By integrating advantages CACHEJOIN, article presents two modifications for...
Heterogeneity is the key aspect of complex networks and smart devices for using it as nature live streams. The heterogeneous stream-disk join a significant research topic in real-time processing applications because can directly affect data analytics. Multiple issues, including stream loss, scalability, disk access cost, accuracy, should be considered during transformation. In this work we overcome these issues by introducing distributed architecture DHSDJArch which prevent loss well...
Streaming data join is a critical process in the field of near-real-time warehousing. For this purpose, an adaptive semi-stream algorithm called CACHEJOIN (Cache Join) focusing non-uniform stream provided literature. However, cannot exploit memory and CPU resources optimally consequently it leaves its service rate suboptimal due to sequential execution both phases, stream-probing (SP) phase disk-probing (DP) phase. By integrating advantages CACHEJOIN, paper we present two modifications it....