Towards Introducing User Preferences in OLAP Reporting Tool

This paper presents an OLAP reporting tool and an approach for determining and processing user OLAP preferences, which are useful for generating recommendations on potentially interesting reports. We discuss the metadata layers of the reporting tool including our proposed OLAP preferences metamodel, which supports various scenarios of formulating preferences of two different types: schema-specific and report-specific. The process of semantic metadata usage at the stage of formulating user preferences is also considered. The methods for processing schema-specific and report-specific OLAP preferences are outlined.

Modeling and querying facts with period timestamps in data warehouses

Abstract In this paper, we study various ways of representing and querying fact data that are time-stamped with a time period in a data warehouse. The main focus is on how to represent the time periods that are associated with the facts in order to support convenient and efficient aggregations over time. We propose three distinct logical models that represent time periods as sets of all time points in a period (instant model), as pairs of start and end time points of a period (period model), and as atomic units that are explicitly stored in a new period dimension (period∗ model). The period dimension is enriched with information about the days of each period, thereby combining the former tw…

Research Directions of OLAP Personalizaton

In this paper we have highlighted five existing approaches for introducing personalization in OLAP: preference constructors, dynamic personalization, visual OLAP, recommendations with user session analysis and recommendations with user profile analysis and have analyzed research papers within these directions. We have provided an evaluation in order to point out (i) personalization options, described in these approaches, and its applicability to OLAP schema elements, aggregate functions, OLAP operations, (ii) the type of constraints (hard, soft or other), used in each approach, (iii) the methods for obtaining user preferences and collecting user information. The goal of our paper is to syst…

Handling Evolving Data Warehouse Requirements

A data warehouse is a dynamic environment and its business requirements tend to evolve over time, therefore, it is necessary not only to handle changes in data warehouse data, but also to adjust a data warehouse schema in accordance with changes in requirements. In this paper, we propose an approach to propagate modified data warehouse requirements in data warehouse schemata. The approach supports versions of data warehouse schemata and employs the requirements formalization metamodel and multiversion data warehouse metamodel to identify necessary changes in a data warehouse.

Data Modelling for Dynamic Monitoring of Vital Signs: Challenges and Perspectives

The use-case described in this paper covers data acquisition and real-time analysis of the gathered medical data from wearable sensor system. Accumulated data is essential for monitoring vital signs and tracking the dynamics of the treatment process of disabled patients or patients undergoing the recovery after traumatic knee joint injury (e.g. post-operative rehabilitation). The main goal of employing the wearable sensor system is to conduct rehabilitation process more effectively and increase the rate of successful rehabilitation. The results of data analysis of patient’s vital signs and feedback allow a physiotherapist to adjust the rehabilitation scenario on the fly. In this paper, we f…

A Little Bird Told Me: Discovering KPIs from Twitter Data

The goal of our research and experiments is to find the definitions and values of key performance indicators (KPIs) in unstructured text. The direct access to opinions of customers served as a motivating factor for us to choose Twitter data for our experiments. For our case study, we have chosen the restaurant business domain. As in the other business domains, KPIs often serve as a solution for identification of current problems. Therefore, it is essential to learn which criteria are important to restaurant guests. The mission of our Proof-of-Concept KPI discovery tool presented in this paper is to facilitate the explorative analysis taking Twitter user posts as a data source. After process…

Performance Measurement Framework with Formal Indicator Definitions

Definition of appropriate measures of organization’s performance should be conducted in a systematic way. In this paper the performance measurement and indicators are discussed not only from the side of management models, but also from the point of view of measurement theories to find out appropriate definitions. In our work we propose a formal specification of indicators. The principles of indicator reformulation from free form indicators to formal requirements are formulated and applied in several examples from performance measures database. The formally defined indicators could be used in the proposed performance measurement framework that covers five-step indicator lifecycle.

Extending a Metamodel for Formalization of Data Warehouse Requirements

In performance measurement systems that are built on top of a data warehouse, the information requirements in natural language are different performance indicators that should be stored and analyzed. We use the requirement formalization metamodel to create a formal requirement repository out of information requirements in natural language. In the course of this research we tested the compatibility of the existing requirement formalization metamodel applying it to a set of over 150 requirements for the currently operating data warehouse project. As a result, we extended the formal specification of information requirements with some additional classes like themes, grouping, and requirement pr…

Can SQ and EQ Values and Their Difference Indicate Programming Aptitude to Reduce Dropout Rate?

A crucial problem that we are currently facing at the Faculty of Computing of the University of Latvia is that during the first study semester on average 30% of the first-year students drop out, whereas after the first year of studies the number of dropouts increases up to nearly 50%. Thus, our overall goal is to determine in advance applicants that most likely will not finish the first study year successfully. A hypothesis formulated in another research study was that programming aptitude could be predicted based on the results of two personality self-report questionnaires − Systemizing Quotient (SQ) and Empathy Quotient (EQ) − taken by students. The difference between the SQ and EQ scores…

New Trends in Databases and Information Systems: Contributions from ADBIS 2017 Workshops

In the last few years, research on database and information system technologies has been rapidly evolving thanks to the new paradigms of software and hardware adopted by modern scientific and more invasive applications. A huge and heterogeneous amount of data should be efficiently stored, managed, and analyzed exploiting proper technologies for such novel and more interesting data-driven applications. New and cutting-edge research challenges arise that have been attracting great attention from both academia and industry. The 21st European Conference on Advances in Databases and Information Systems (ADBIS 2017), held on September 24–27, 2017 in Nicosia, Cyprus includes four thematic workshop…

Information Requirements for Big Data Projects: A Review of State-of-the-Art Approaches

Big data technologies are rapidly gaining popularity and become widely used, thus, making the choice of developing methodologies including the approaches for requirements analysis more acute. There is a position that in the context of the Data Warehousing (DW), similar to other Decision Support Systems (DSS) technologies, defining information requirements (IR) can increase the chances of the project to be successful with its goals achieved. This way, it is important to examine this subject in the context of Big data due to the lack of research in the field of Big data requirements analysis. This paper gives an overview of the existing methods associated with Big data technologies and requir…

Gathering formalized information requirements of a data warehouse

An empirical study of recommendations in OLAP reporting tool

This paper presents the results of the experimental study that was performed in laboratory settings in the context of the OLAP reporting tool developed and put to operation at the University. The study was targeted to explore which of the modes for generating recommendations in the OLAP reporting tool has a deeper impact on users (i.e. produces more accurate recommendations). Each of the modes of the recommendation component – report structure, user activity, and semantic – employs a separate content-based method that takes advantage of OLAP schema metadata and aggregate functions. Gained data are assessed (i) quantitatively by means of the precision/recall and other metrics from the lo…

OLAP Personalization with User-Describing Profiles

In this paper we have highlighted five existing approaches for introducing personalization in OLAP: preference constructors, dynamic personalization, visual OLAP, recommendations with user session analysis and recommendations with user profile analysis and have analyzed research papers within these directions. We have pointed out applicability of personalization to OLAP schema elements in these approaches. The comparative analysis has been made in order to highlight a certain personalization approach. A new method has been proposed, which provides exhaustive description of interaction between user and data warehouse, using the concept of Zachman Framework [1, 2], according to which a set of…