Ezio Lefons

Università degli Studi di Bari Aldo Moro | Università di Bari · Dipartimento di Informatica

Big Data warehouses are a new class of databases that largely use unstructured and volatile data for analytical purpose. Examples of this kind of data sources are those coming from the Web, such as social networks and blogs, or from sensor networks, where huge amounts of data may be available only for short intervals of time. In order to manage mas...

This article describes how the evaluation of modern data warehouses considers new solutions adopted for facing the radical changes caused by the necessity of reducing the storage volume, while increasing the velocity in multidimensional design and data elaboration, even in presence of unstructured data that are useful for providing qualitative info...

The data warehouse design methodologies require a novel approach in the Big Data context, because the methodologies have to provide solutions to face the issues related to the 5 Vs (Volume, Velocity, Variety, Veracity, and Value). So it is mandatory to support the designer through automatic techniques able to quickly produce a multidimensional sche...

Methodologies for data warehouse design are increasing more and more in last years, and each of them proposes a different point of view. Among all the methodologies present in literature, the promising ones are the hybrid methodologies—because they represent the only way to ensure a multidimensional schema to be both consistent with data sources an...

Decision making is an activity that addresses the problem of extracting knowledge and information from data stored in data warehouses, in order to improve the business processes of information systems. Usually, decision making is based on On-Line Analytical Processing, data mining, or approximate query processing. In the last case, answers to analy...

Traditional data warehouse design methodologies are based on two opposite approaches. The one is data oriented and aims to realize the data warehouse mainly through a reengineering process of the well-structured data sources solely, while minimizing the involvement of end users. The other is requirement oriented and aims to realize the data warehou...

Big Data Warehouses differ substantially from traditional data warehouses in that their schema should be based on novel logical models that allow more flexibility than that the relational model does. Furthermore, their design methodology also requires new principles, such as automation and agile techniques, in order to gain both a fast realization...

In the last years, data warehousing has got attention from Universities which are now adopting business intelligence solutions in order to analyze crucial aspects of the academic context. In this paper, we present the architecture of a Business Intelligence system for academic organizations. Then, we illustrate the design process of the data wareho...

The standard benchmark for Decision Support Systems is TPC-H, which is composed of a database, a workload, and a set of metrics for the performance evaluation. However, TPC-H does not include a methodology for the benchmark of Approximate Query Answering Systems, or the software tools used to obtain fast answers to analytical queries in the decisio...

Business Intelligence is an activity based on a set of processes and software tools. Its aim is to support the decisional making phase, by extracting information from synthetical data. As the success of such an activity depends on the effectiveness of several business processes and the correct integration of independent software tools, nowadays sta...

In the early stages of data warehouse design, the integration of several source databases must be addressed. Data-oriented and hybrid methodologies need to consider a global schema coming from the integration of source databases, in order to start the conceptual design. Since each database relies on its own conceptual schema, in the integration pro...

Traditional data warehouse design methodologies are based on two opposite approaches. The one is data oriented and aims to realize the data warehouse mainly through a reengineering process of the well-structured data sources solely, while minimizing the involvement of end users. The other is requirement oriented and aims to realize the data warehou...

In business intelligence systems, data warehouse metadata management and representation are getting more and more attention by vendors and designers. The standard language for the data warehouse metadata representation is the Common Warehouse Metamodel. However, business intelligence systems include also approximate query answering systems, since t...

Data warehousing is an activity that is getting more and more attention in several contexts. Also Universities are adopting data warehousing solutions for business intelligence purpose. In these contexts, there are specific aspects to be considered, such as the Didactics and the Research evaluation. Indeed, these are the main factors affecting the...

ContextData warehouse conceptual design is based on the metaphor of the cube, which can be derived from either requirement-driven or data-driven methodologies. Each methodology has its own advantages. The first allows designers to obtain a conceptual schema very close to the user needs but it may be not supported by the effective data availability....

The performance evaluation of the transaction processing in Database Management Systems used for Decision Support Systems is the aim of the current TPC-H standard. Decision Support Systems also include Approximate Query Answering Systems. However, the TPC-H does not define a methodology to evaluate these systems, nor does it provide useful metrics....

The main methodologies for the data warehouse design are based on two approaches which are opposite and alternative each other. The one, based on the data-driven approach, aims to produce a conceptual schema mainly through a reengineering process of the data sources, while minimizing the involvement of end users. The other is based on the requireme...

Business Intelligence is an activity that aims to extract information and knowledge from a central repository, the so-called data warehouse, in order to improve the business processes of an information system. Typical applications are based on reporting, on-line analytical processing, data mining, and approximate query processing. Business Intellig...

Approximate query processing is often based on analytical methodologies able to provide fast responses to queries. As a counterpart, the approximate answers are affected with a small quantity of error. Nowadays, these techniques are being exploited in data warehousing environments, because the queries devoted to extract information involve high-car...

The current lack of a standard methodology for data warehouse design has led to have many possible lifecycles. In some of them, the validation of the data warehouse conceptual schema is a specific process that precedes the translation of such a schema into a logical one. This activity must ensure that the data warehouse to be implemented effectivel...

The methodologies used in approximate query processing are able to provide fast responses to queries that require high computational time in the decision making process. However, the approximate answers are affected with a small quantity of error. For this reason, it is important to provide also an accuracy of the approximate value, that is, a conf...

Business Intelligence systems are based on traditional OLAP, data mining, and approximate query processing. Generally, these activities allow to extract information and knowledge from large volumes of data and to support decisional makers as concerns strategic choices to be taken in order to improve the business processes of the Information System....

Data Warehouses are databases used in Business Intelligence systems as a data source to develop analytical applications. These applications consist of multidimensional analyses of data and allow decisional makers to improve the business processes of the Information System. Since multidimensional analyses require to aggregate data on several attribu...

The dimensional fact model is a conceptual model that allows to design the multidimensional schema of a data warehouse. Its methodology is based on the (re)modelling of the schema of a relational database; such a schema is represented by a tree, and the (re)modelling consists of the traditional operations on graphs (as prune, graft, adding child, c...

The selectivity factor of relational operations is a critical parameter for determining the cost function of query processing. Good estimates of these parameters allow the optimizers to choose the least expensive path in the query execution. A method for estimating the join and projection selectivity factors based on the orthogonal polynomial serie...

Face-to-face teaching involves both theoretical and laboratory lessons. Here, we present an online course, developed by an open source software, in order to support traditional face-to-face lessons in the Databases field. The courseware is based on learning objects designed to support different teaching needs derived not only from the Computer Scie...

We present a system that provides an e-learning environment in the database and information system fields. The system has been designed to support different teaching needs deriving not only from the computer science degree, but also from others University degrees that require database skills. For this purpose, it has been developed a repository of...

The development of a Business Intelligence Application starts with the execution of OLAP queries to extract information from data stored in a Data Warehouse. The results of these queries, together with an opportune data representation, offer a deep synthesis of data and help business users to better discover hidden knowledge than using conventional...

Traditional users of data warehouses were banks, financial services, or chains of supermarkets. Instead, Institutional Organizations (e.g. Academies) in the past did not use the large amount of transactional data for strategic decision making. The optimal management of a University can now be considered as critical as the management of a big enterp...

A set of evaluation criteria is described and considered for comparing some popular OLAP systems that support Business Intelligence. These criteria involve critical aspects such as: information delivery, system and user administration, and OLAP queries. The measurement method is based on the functional complexity analysis. Experimental results have...

The paper examines some common platforms supporting Business Intelligence activities in order to state evaluation criteria for the system choice. The evaluation considers a software measurement method based on the analysis of the functional complexity of the platforms. The study has been performed on an academic warehouse that uses historical data...

In decision support activities, it is very important to provide the user with feasible strategies to answer complex queries, besides furnishing fast query response time. The alternative to the time-consuming scan of huge amounts of data in data warehouses is provided by the use of data reduction for data analysis and a suitable approximate query pr...

There are several benefits that can be reached by developing an academic data warehouse as providing a centralized source of information accessible across different academic units to quickly analyze problems and get satisfactory solutions, supplying the data necessary for developing the Institution's strategic plan, and enabling administrator to ma...

We introduce the use of Bitmap indices as very useful tools to represent analytical views of user's data. This approach differs from the conventional definition and use of bitmaps in that it allows us not only to index different domain attribute values, but also to pre-compute (any) legal relational algebra query expression from the user for analyt...

The use of bitmap indexes for representing analytical views of user's data is presented. This approach differs from the conventional definition and use of bitmap indexes in that they are defined not only to index different domain attribute values, but also for pre-computing any legal relational algebra query expression of the user for the analytic...

Bitmap indexing is a diffuse approach for processing efficiently complex queries in decision support activities. Besides this common use of bitmap structures, the use of bitmap indices to represent analytical views of user's data is presented here. In this approach, bitmaps can be created and utilized not only to index different domain attribute va...

A system that supports learning activities on data base management systems for the degree course in computer science is presented. After an accurate analysis of main open source tools, the system has been developed using ATutor, a freeware and multiplatform Learning Component Management System developed at the University of Toronto. The learning en...

The goal of the data warehousing approach is to supply directly relevant information to perform quickly and efficiently data analysis in decision support activities using OLAP and data mining tools. Thus, building data warehouse is a complex and expensive process involving careful design choices from source extraction and data integration phase to...

The Information Technology is an essential support in the decisional process to improve manager' phenomena knowledge, that is often approximate and ill-structured. Tools underlying decision support systems (as OLAP systems, data mining, and data warehouses) have a central role in enterprise information systems. In this paper, we present the design...

Analysts and decisional users utilize exploratory, complex, but iterative processes based on sequences of queries formulated against the data warehouse. Whereas the effectiveness of such an activity is related to analysis tools, its efficiency depends on the current quality of the stored data in the data warehouse. Here, we describe the case study...

The decisional analysis is a complex, iterative, and exploratory process based on a sequence of queries issued against the data warehouse. The efficiency of the decisional activity depends on the quality of the stored data in the data warehouse, while its effectiveness is related to the analysis tools. In this paper, we discuss both these aspects i...

The analysis, design, and implementation of the data warehouse system for the decisional process based on the Italian train booking data are presented. Trenitalia, the Italian main train service company, is the customer, and TSF (railway telesystems company) the IT solution provider. In particular, the feasibility requirements, functionality, techn...

In this paper, the matter of a successful data warehousing, with its analysis, design and implementation is dealt with. In particular, we present the data warehouse system for the decisional process based on our national train trasportation data owned by Trenitalia, the Italian main train service company and customer of the project. We discuss the...

In this paper, a method for estimating the size of relational query results is proposed. The approach is based on the estimates of the attribute distinct values. On the basis of our method, a set of parameters, the so-called Canonical Coefficients, can be derived from actual data; they allow us to approximate both the multivariate data distribution...

Most parameters which constitute the statistical profile are related to the record selectivity. To estimate record selectivity factors, the nonparametric are better than parametric methods in that they make no a priori assumptions concerning the data distribution and generally provide accurate results. Nonparametric methods are classified into the...

This article describes an attempt to use a theoretical model of human interaction called the elementary pragmatic model to determine which communication style leads from a normal subject's interactive pattern to a schizophrenic's and, conversely, from schizophrenia to normality. Results of this experimentation reveal a clear correspondence with the...

The architecture of the POLD relational system for distributed data analysis is presented. POLD was designed as the kernel of a decision support information system. The peculiarity of POLD consists in allowing the user to view and analyze the data information as couple 〈data, semantics〉, the semantics being a user's suitable classification of the d...

A theoretical frame for the description of the interactional behavior of human subject systems is presented. The subject's interactional pattern is defined by a quadruple of coordinates, each coordinate being the probability of transition between elementary states, defined in terms of initial subject states and input information (external stimuli)....

An original method of testing which can measure interactional patterns is presented. This method is based on a relational model, which describes the relational behaviour as a sequence of elementary interactions, in which a "single bit of information" is exchanged. The model and the testing method are applied to monitoring treatment of patients with...

In the commonly adopted data models (as ins entity-relationship data model 111, for example) an attribute is a mapping between an en- tity set or a relationship set and a value set. The intension of a mapping property is given im- plicitly or explicitly in the data models, but the extension can be generally represented by the set I), as in the rela...

In studying the problem of interaction between subjects, an approach which allows us to define in an unambiguous way the concepts of symmetrical, complementary and parallel interaction is proposed. This approach makes use of a point of view within which it is possible to develop a rational model based only on some fundamental elements of set theory...

This paper describes an interactive system to analyze large samples of collected data. The first application has been developed to ensure a significant improvement in the efficiency of data management in recent high energy physics experiments (Omega-project). However, the system is also suitable in all experiments treating large volumes of experime...

The work is concerned with a computer assisted laboratory for experimental analyses in the human interaction field, built up for the Psychiatric Clinic of Bari University, in collaboration with the Institute of Physics. Data acquisition, reduction, storage and retrieval, statistical analysis and simulation are supported by a programme chain, runnin...

An algebraic model for human interaction via information transmission is presented and discussed. Information transmission is schematized as the exchange of logical propositions among human subjects. As a first approach two interacting subjects are considered as being probabilistic automata described in terms of Boolean functions: in particular, a...

Decisional Portals are web-based systems furnishing summary information, statistical indicators, and graphical data reports in data warehousing environments. They are mainly used to monitor market evolu- tion and to control productivity of enterprise sectors. Fast response times and friendly user-interfaces are criti- cal requirements for decision-...

Both the approximate query process and decisional portals are emerging technologies in the decision support system environment. The former tool provides fast execution time for the analysis applications which require access to large amounts of data in the warehouse, by furnishing estimates of summary data with an approximation error acceptable for...

Counts of database unique values are crucial information in query optimization. Estimating the number of the distinct values occurs frequently in database queries, due to its importance in selecting query plans. We present a nonparametric method for estimating the database distincts, and, then, the number of distinct values. The method computes few...