160 research outputs found
Proceedings of the 17th International Workshop on Data Warehousing and OLAP, DOLAP 2014, Shanghai, China, November 3-7, 2014
No full textFrom Business Intelligence to Location Intelligence with the Lily Library
No full textLocation intelligence is a set of tools and techniques to integrate spatial features into BI platforms, aimed at better monitoring and interpreting business events related to the territory. In this demonstration we present Lily, a geo-enhanced library that relies on a spatial data warehouse to add real location intelligence capabilities to existing BI platforms. Lily provides end-users with a highly-interactive interface that seamlessly achieves a bidirectional integration between the BI and the geospatial worlds, so as to enable advanced analytical, prediction, and simulation features taking into account the spatial dimension. In particular we focus on the impact of Lily on the user experience with reference to three case studies in the domain of healthcare, telco, and school services respectively
Big Data Management: New Frontiers, New Paradigms
No full textThis special issue on “Big Data Management: New Frontiers, New Paradigms” of Information Systems presents a rigorous selection of the best papers of the 17th ACM International Workshop on Data Warehousing and OLAP (DOLAP 2014), held in conjunction with the 23rd ACM International Conference on Conference on Information and Knowledge Management (CIKM 2014), in Shanghai, China, during November 3–7, 2014
Optimizing ETL Processes in Data Warehouses
No full textExtraction-Transformation-Loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, their cleansing, customization and insertion into a data warehouse. Usually, these processes must be completed in a certain time window; thus, it is necessary to optimize their execution time. In this paper, we delve into the logical optimization of ETL processes, modeling it as a state-space search problem. We consider each ETL workflow as a state and fabricate the state space through a set of correct state transitions. Moreover, we provide algorithms towards the minimization of the execution cost of an ETL workflow. 1
Modeling and managing ETL Processes
No full textExtraction-Transformation-Loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, their cleansing, customization and insertion into a data warehouse. The design, development and deployment of ETL processes, which is currently, performed in an ad-hoc, in house fashion, needs modeling, design and methodological foundations. Unfortunately, the research community has a lot of work to do to confront this shortcoming. Our research explores a coherent framework for the conceptual, the logical, and the physical design of ETL processes. We delve into the modeling of ETL activities and provide a conceptual and a logical abstraction for the representation of these processes. Moreover, we focus on the optimization of the ETL processes, in order to minimize the execution time of an ETL process. 1
Logical Optimization of ETL Workflows
No full textExtraction-Transformation-Loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, their cleansing, customization and insertion into a data warehouse. Usually, these processes must be completed in a certain time window; thus, it is necessary to optimize their execution time. In this paper, we delve into the logical optimization of ETL processes, modeling it as a state-space search problem. We consider each ETL workflow as a state and fabricate the state space through a set of correct state transitions. Moreover, we provide algorithms towards the minimization of the execution cost of an ETL workflow. 1
Benchmarking Analytical Query Processing in Intel SGXv2
No full textTrusted Execution Environments (TEEs), such as Intel’s Software Guard Extensions (SGX), are increasingly being adopted to address trust and compliance issues in the public cloud. Intel SGX’s second generation (SGXv2) addresses many limitations of its predecessor (SGXv1), offering the potential for secure and efficient analytical cloud DBMSs. We assess this potential and conduct the first in-depth evaluation study of analytical query processing
algorithms inside SGXv2. Our study reveals that, unlike SGXv1, state-of-the-art algorithms like radix joins and SIMD-based scans are a good starting point for achieving high-performance query processing inside SGXv2. However, subtle hardware and software differences still influence code execution inside SGX enclaves and cause substantial overheads. We investigate these differences and propose new optimizations to bring the performance inside enclaves on par with native code execution outside enclaves
Corresponding author:
No full textAbstract. Extraction-Transformation-Loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, their cleansing, customization and insertion into a data warehouse. In this paper, we delve into the logical design of ETL scenarios and provide a generic and customizable framework in order to support the DW designer in his task. First, we present a metamodel particularly customized for the definition of ETL activities. We follow a workflow-like approach, where the output of a certain activity can either be stored persistently or passed to a subsequent activity. Also, we employ a declarative database programming language, LDL, to define the semantics of each activity. The metamodel is generic enough to capture any possible ETL activity. Nevertheless, in the pursuit of higher reusability and flexibility, we specialize the set of our generic metamodel constructs with a palette of frequently-used ETL activities, which we call templates. Moreover, in order to achieve a uniform extensibility mechanism for this library of built-ins, we have to deal with specific language issues. Therefore, we also discuss the mechanics of template instantiation to concrete activities. The design concepts that we introduce have been implemented in a tool
Data Warehouse Back-End Tools
No full textThe back-end tools of a data warehouse are pieces of software responsible for the extraction of data from several sources, their cleansing, customization, and insertion into a data warehouse. In general, these tools are known as Extract – Transformation – Load (ETL) tools and the process that describes the population of a data warehouse from its sources is called ETL process. In all the phases of an ETL process (extraction and transportation, transformation and cleaning, and loading), individual issues arise, and, along with the problems and constraints that concern the overall ETL process, make its lifecycle a very complex task. </jats:p
- …
