Linked Data Management presents techniques for querying and managing Linked Data that is available on today's Web. The book shows how the abundance of Linked Data can serve as fertile ground for research and commercial applications. The text focuses on aspects of managing large-scale collections of Linked Data. It offers a detailed introduction to Linked Data and related standards, including the main principles distinguishing Linked Data from standard database technology. Chapters also describe how to generate links between datasets and explain the overall architecture of data integration systems based on Linked Data. A large part of the text is devoted to query processing in different setups. After presenting methods to publish relational data as Linked Data and efficient centralized processing, the book explores lookup-based, distributed, and parallel solutions. It then addresses advanced topics, such as reasoning, and discusses work related to read-write Linked Data for system interoperation. Despite the publication of many papers since Tim Berners-Lee developed the Linked Data principles in 2006, the field lacks a comprehensive, unified overview of the state of the art. Suitable for both researchers and practitioners, this book provides a thorough, consolidated account of the new data publishing and data integration paradigm. While the book covers query processing extensively, the Linked Data abstraction furnishes more than a mechanism for collecting, integrating, and querying data from the open Web-the Linked Data technology stack also allows for controlled, sophisticated applications deployed in an enterprise environment.

Blockchain is an emerging platform for developing decentralized applications and data storage, over and beyond its role as a platform for cryptocurrencies. This reference text provides a comprehensive discussion on blockchain technology from research and application perspective. Discusses different approaches for building distributed applications (DAPPS). Provides detailed listing and discussion of blockchain technology applications in solving real life problems. Covers proof of work (PoW) based blockchain consensus, and proof of stake (PoS) based blockchain consensus. Discusses blockchain algorithms including practical byzantine fault tolerance (PBFT) and simplified byzantine fault tolerance (SBFT). It comprehensively covers important topics including blockchain consensus algorithms, Ethereum, Hyperledger, blockchain scalability, smart contracts with solidity, ERC20 standards, building DApp with Golang, building DApp using Hyperledger, building PoCs with Hyperledger fabric, blockchain as a server, blockchain security and privacy. The text will serve as a useful text for senior undergraduate and graduate students in interdisciplinary areas including electronics and communications engineering, electrical engineering, computer science, and information technology.

In today's competitive business environment, most companies realize that the better they can manage their customer relationships, the more successful they will become. Customer Relationship Management (CRM) software systems are key tools for companies to manage the customer-facing processes of their businesses. However, many companies have resisted implementing this most critical customer-oriented application due in large part to the lack of a single-point resource on implementing a CRM system. This book attempts to fill that gap. Implementing SAP (R) CRM will help technologists and managers come to grips with the vision, concept, and technology of CRM. It begins by laying out the groundwork for understanding CRM. It explains the concept and context of CRM and the tangible business benefits of CRM adoption. Demonstrating a professional approach to the evaluation and selection of SAP, it details the critical success factors (CSFs), patterns, and anti-patterns of a successful SAP CRM implementation. CRM implementations can add significant benefit to the company's bottom line only if the company first transforms itself into a customer-centric and customer-responsive enterprise. This book explains what it means to be a customer-centric and responsive enterprise, and provides a framework for business operations based on customer relationships, rather than the traditional four Ps (product, positioning, price, promotion). It further spells out business process reengineering (BPR) strategies to configure internal business processes and operations with SAP CRM to improve customer-facing strategies, services, and relationships.

Big data has always been a major challenge in geoinformatics as geospatial data come in various types and formats, new geospatial data are acquired very fast, and geospatial databases are inherently very large. And while there have been advances in hardware and software for handling big data, they often fall short of handling geospatial big data efficiently and effectively. Big Data: Techniques and Technologies in Geoinformatics tackles these challenges head on, integrating coverage of techniques and technologies for storing, managing, and computing geospatial big data. Providing a perspective based on analysis of time, applications, and resources, this book familiarizes readers with geospatial applications that fall under the category of big data. It explores new trends in geospatial data collection, such as geo-crowdsourcing and advanced data collection technologies such as LiDAR point clouds. The book features a range of topics on big data techniques and technologies in geoinformatics including distributed computing, geospatial data analytics, social media, and volunteered geographic information. With chapters contributed by experts in geoinformatics and in domains such as computing and engineering, the book provides an understanding of the challenges and issues of big data in geoinformatics applications. The book is a single collection of current and emerging techniques, technologies, and tools that are needed to collect, analyze, manage, process, and visualize geospatial big data.

Visualization and Verbalization of Data shows how correspondence analysis and related techniques enable the display of data in graphical form, which results in the verbalization of the structures in data. Renowned researchers in the field trace the history of these techniques and cover their current applications. The first part of the book explains the historical origins of correspondence analysis and associated methods. The second part concentrates on the contributions made by the school of Jean-Paul Benzecri and related movements, such as social space and geometric data analysis. Although these topics are viewed from a French perspective, the book makes them understandable to an international audience. Throughout the text, well-known experts illustrate the use of the methods in practice. Examples include the spatial visualization of multivariate data, cluster analysis in computer science, the transformation of a textual data set into numerical data, the use of quantitative and qualitative variables in multiple factor analysis, different possibilities of recoding data prior to visualization, and the application of duality diagram theory to the analysis of a contingency table.

A Versatile Framework for Handling Subdivided Geometric Objects Combinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing gathers important ideas related to combinatorial maps and explains how the maps are applied in geometric modeling and image processing. It focuses on two subclasses of combinatorial maps: n-Gmaps and n-maps. Suitable for researchers and graduate students in geometric modeling, computational and discrete geometry, computer graphics, and image processing and analysis, the book presents the data structures, operations, and algorithms that are useful in handling subdivided geometric objects. It shows how to study data structures for the explicit representation of subdivided geometric objects and describes operations for handling the structures. The book also illustrates results of the design of data structures and operations.

Big Data: A Business and Legal Guide supplies a clear understanding of the interrelationships between Big Data, the new business insights it reveals, and the laws, regulations, and contracting practices that impact the use of the insights and the data. Providing business executives and lawyers (in-house and in private practice) with an accessible primer on Big Data and its business implications, this book will enable readers to quickly grasp the key issues and effectively implement the right solutions to collecting, licensing, handling, and using Big Data. The book brings together subject matter experts who examine a different area of law in each chapter and explain how these laws can affect the way your business or organization can use Big Data. These experts also supply recommendations as to the steps your organization can take to maximize Big Data opportunities without increasing risk and liability to your organization. Provides a new way of thinking about Big Data that will help readers address emerging issues Supplies real-world advice and practical ways to handle the issues Uses examples pulled from the news and cases to illustrate points Includes a non-technical Big Data primer that discusses the characteristics of Big Data and distinguishes it from traditional database models Taking a cross-disciplinary approach, the book will help executives, managers, and counsel better understand the interrelationships between Big Data, decisions based on Big Data, and the laws, regulations, and contracting practices that impact its use. After reading this book, you will be able to think more broadly about the best way to harness Big Data in your business and establish procedures to ensure that legal considerations are part of the decision.

'Big data' is now readily available to economic historians, thanks to the digitisation of primary sources, collaborative research linking different data sets, and the publication of databases on the internet. Key economic indicators, such as the consumer price index, can be tracked over long periods, and qualitative information, such as land use, can be converted to a quantitative form. In order to fully exploit these innovations it is necessary to use sophisticated statistical techniques to reveal the patterns hidden in datasets, and this book shows how this can be done. A distinguished group of economic historians have teamed up with younger researchers to pilot the application of new techniques to 'big data'. Topics addressed in this volume include prices and the standard of living, money supply, credit markets, land values and land use, transport, technological innovation, and business networks. The research spans the medieval, early modern and modern periods. Research methods include simultaneous equation systems, stochastic trends and discrete choice modelling. This book is essential reading for doctoral and post-doctoral researchers in business, economic and social history. The case studies will also appeal to historical geographers and applied econometricians.

This book focuses on the contribution of Information Technology (IT) and Information Technology Enabled Services (ITES) in shaping the current and future global economic scenario, with a special focus on Asia, and taking into account the three broad macroeconomic dimensions - growth, sustainability and governance mechanisms. The last two decades have witnessed a structural shift in the world economy due to the tremendous growth in gross domestic product share for the service sector; in fact, service has emerged as the dominant sector and the main driver of GDP growth. This is mainly attributable to the spectacular success of the IT sector in the new knowledge economy. Tradability, technology and transportability - the three T's - govern productivity growth in today's services. Growing Asian economies such as India, China and Vietnam, using their demographic advantages, have been reaping the benefits of this boom. The book's content focuses on recent debates and discussions concerning the issue of long-term sustainability and governance, especially in India, as these companies are facing continuous challenges in terms of international competition, salary inflation, health hazards, scarcity of talent, employee attrition, security concerns, global slowdown and many other technology-related issues. The book further highlights how the increased application of IT-based products and services is resulting in harsh inequalities concerning income distribution in many developing countries of Asia, mainly because of its labor shedding nature, and hence might be detrimental to sustainable development, if suitable policy measures are not implemented to counter these effects. The book provides a wealth of information for researchers, graduate students and political scientists alike, as well as thought-provoking insights for social scientists, policymakers and government officials. It also offers a valuable source of data for business and management professionals, and for members of Chambers of Commerce and Industry.

This book presents findings from the papers accepted at the Cyber Security Education Stream and Cyber Security Technology Stream of The National Cyber Summit's Research Track, reporting on the latest advances on topics ranging from software security to cyber attack detection and modelling to the use of machine learning in cyber security to legislation and policy to surveying of small businesses to cyber competition, and so on. Understanding the latest capabilities in cyber security ensures that users and organizations are best prepared for potential negative events. This book is of interest to cyber security researchers, educators, and practitioners, as well as students seeking to learn about cyber security.

The Complete Book of Data Anonymization: From Planning to Implementation supplies a 360-degree view of data privacy protection using data anonymization. It examines data anonymization from both a practitioner's and a program sponsor's perspective. Discussing analysis, planning, setup, and governance, it illustrates the entire process of adapting and implementing anonymization tools and programs. Part I of the book begins by explaining what data anonymization is. It describes how to scope a data anonymization program as well as the challenges involved when planning for this initiative at an enterprisewide level. Part II describes the different solution patterns and techniques available for data anonymization. It explains how to select a pattern and technique and provides a phased approach towards data anonymization for an application. A cutting-edge guide to data anonymization implementation, this book delves far beyond data anonymization techniques to supply you with the wide-ranging perspective required to ensure comprehensive protection against misuse of data.

An effective DBA is an efficient DBA. And if you work with SQL Server, dbatools is a lifesaver. With over 500 commands, this free and open source PowerShell module has the horsepower to automate just about every task you can imagine-and then some! Learn dbatools in a Month of Lunches teaches you techniques that will make you more effective-and efficient-than you ever thought possible. Learn dbatools in a Month of Lunches is a practical hands-on guide to automating SQL Server with PowerShell and the awesome dbatools module. You'll master techniques you can immediately put into practice, from daily duties like backups and restores right through to performing security audits. Stabilize and standardize your SQL server environment, and simplify your tasks by building automation, alerting, and reporting with this powerful tool. Each lesson delivers another skill that you can use to speed through your core tasks as a SQL Server DBA! About the Technology Want to automate tasks for thousands of SQL servers at once? Want to migrate an entire SQL server using just the command line? dbatools can do all that-and more. A free and open source PowerShell module, dbatools offers over 500 commands for automating SQL Server from the command line. Boasting advanced options unavailable in official tools, dbatools makes it easy to automate tasks including mass exports for simplified disaster recovery, tempdb configuration, and improving an instance's security posture.

For courses in Cryptography, Computer Security, and Network Security. Keep pace with the fast-moving field of cryptography and network security Stallings' Cryptography and Network Security: Principles and Practice introduces students to the compelling and evolving field of cryptography and network security. In an age of viruses and hackers, electronic eavesdropping, and electronic fraud on a global scale, security is paramount. The purpose of this book is to provide a practical survey of both the principles and practice of cryptography and network security. The first part of the book explores the basic issues to be addressed by a network security capability and provides a tutorial and survey of cryptography and network security technology. The latter part of the book deals with the practice of network security, covering practical applications that have been implemented and are in use to provide network security.

Take a deep dive into the architectural approach, best practices, and key considerations needed to comprehend, evaluate, and design an efficient, scalable, and sustainable Salesforce-based solution. This book takes a comprehensive look at the seven architectural domains that must be considered when architecting a Salesforce-based solution and equips you to develop the artifacts needed for an end-to-end enterprise architecture blueprint for Salesforce implementation and DevOps. This must-have handbook helps Salesforce professionals implement and manage Salesforce in their organization. You will learn Salesforce architecture: solution architecture, data architecture, security architecture, integration architecture, identity and access management architecture, and strategies that can be used for Salesforce-based mobile applications. In addition to the main architecture concepts, the book also offers industry best practices and the recommended framework for approaching, managing, delivering, and continuously improving a Salesforce solution using its Salesforce Development & Deployment Lifecycle. What You Will Learn Get a detailed overview of the Salesforce multi-tenant, metadata-driven architectural framework and the under-the-hood technology stack that supports Salesforce Know the seven architecture domains, their intricacies, and the considerations needed within each when designing a Salesforce solution Have an architectural mindset and the artifacts needed to architect an end-to-end enterprise-level implementation of Salesforce Be familiar with the most common Salesforce products, licenses, AppExchange products, and the key considerations of using out-of-the-box declarative capabilities vs custom programmatic capabilities of Salesforce Understand data architecture design considerations that include data modeling in Salesforce, identifying and mitigating large data volume concerns, and the key considerations for data migration and data archiving strategies Understand security architecture considerations related to securing data within Salesforce and the various approaches to allow or restrict sharing and visibility from within Salesforce Understand integration architecture considerations that provide an overview of the integration patterns and the integrations solutions that can be used with Salesforce to connect Salesforce with a remote system hosted on-premises, on the cloud, or by third-party solution providers Understand identity and access management architectural considerations across the 9 stages of an identity and access management lifecycle Be aware of the strategies available to design mobile solutions with Salesforce and the options available for Salesforce mobile architecture Employ the principles of the DevOps & Development Lifecycle needed for an ideal state Salesforce implementation Who This Book Is For Professionals interested in implementing, optimizing, and architecting Salesforce solutions enterprise-wide; Salesforce implementation (SI) partners needing a detailed playbook for architecting and delivering successful Salesforce solutions; Salesforce admins, developers, and architects looking for a one-stop educational resource to mastering the Salesforce architect domains or those pursuing the Salesforce architecture domain certification exams, including the Salesforce Certified Technical Architect (CTA) board exam

Data is the foundation of any current and future market transformation during this digital era. Companies are expected to adjust or to disappear. However, following assessments by Gartner and Forrester during the past two years, only a small fraction of all enterprises has adequately addressed the handling of data so far. Yet, more and more business leaders have become aware of the topic. They recognize the increasing relevance of data, and the need to act now. Those leaders will welcome this book as it guides them through the first steps in their journey towards a data-driven organisation. This book brings the topic of Data and its commercial usage to the attention of a broad range of business leaders. It encourages you to get engaged, by explaining in a non-technical way what data comprises, which opportunities wait to get discovered and, most importantly, how to prepare and launch the introduction of a Data Office in a company.

Today, online technologies are at the core of most fields of engineering and society as a whole . This book discusses the fundamentals, applications and lessons learned in the field of online and remote engineering, virtual instrumentation, and other related technologies like Cross Reality, Data Science & Big Data, Internet of Things & Industrial Internet of Things, Industry 4.0, Cyber Security, and M2M & Smart Objects. Since the first Remote Engineering and Virtual Instrumentation (REV) conference in 2004, the event has focused on the use of the Internet for engineering tasks, as well as the related opportunities and challenges. In a globally connected world, interest in online collaboration, teleworking, remote services, and other digital working environments is rapidly increasing. In this context, the REV conferences discuss fundamentals, applications and experiences in the field of Online and Remote Engineering as well as Virtual Instrumentation. Furthermore, the conferences focus on guidelines and new concepts for engineering education in higher and vocational education institutions, including emerging technologies in learning, MOOCs & MOOLs, and open resources. This book presents the proceedings of REV2020 on "Cross Reality and Data Science in Engineering" which was held as the 17th in series of annual events. It was organized in cooperation with the Engineering Education Transformations Institute and the Georgia Informatics Institutes for Research and Education and was held at the College of Engineering at the University of Georgia in Athens (GA), USA, from February 26 to 28, 2020.

This book provides a concise but comprehensive guide to the disciplines of database design, construction, implementation, and management. Based on the authors' professional experience in the software engineering and IT industries before making a career switch to academia, the text stresses sound database design as a necessary precursor to successful development and administration of database systems. The discipline of database systems design and management is discussed within the context of the bigger picture of software engineering. Students are led to understand from the outset of the text that a database is a critical component of a software infrastructure, and that proper database design and management is integral to the success of a software system. Additionally, students are led to appreciate the huge value of a properly designed database to the success of a business enterprise. The text was written for three target audiences. It is suited for undergraduate students of computer science and related disciplines who are pursuing a course in database systems, graduate students who are pursuing an introductory course to database, and practicing software engineers and information technology (IT) professionals who need a quick reference on database design. Database Systems: A Pragmatic Approach, 3rd Edition discusses concepts, principles, design, implementation, and management issues related to database systems. Each chapter is organized into brief, reader-friendly, conversational sections with itemization of salient points to be remembered. This pragmatic approach includes adequate treatment of database theory and practice based on strategies that have been tested, proven, and refined over several years. Features of the third edition include: Short paragraphs that express the salient aspects of each subject Bullet points itemizing important points for easy memorization Fully revised and updated diagrams and figures to illustrate concepts to enhance the student's understanding Real-world examples Original methodologies applicable to database design Step-by-step, student-friendly guidelines for solving generic database systems problems Opening chapter overviews and concluding chapter summaries Discussion of DBMS alternatives such as the Entity-Attributes-Value model, NoSQL databases, database-supporting frameworks, and other burgeoning database technologies A chapter with sample assignment questions and case studies This textbook may be used as a one-semester or two-semester course in database systems, augmented by a DBMS (preferably Oracle). After its usage, students will come away with a firm grasp of the design, development, implementation, and management of a database system.

A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today's often unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures. Service-Oriented Distributed Knowledge Discovery presents techniques, algorithms, and systems based on the service-oriented paradigm. Through detailed descriptions of real software systems, it shows how the techniques, models, and architectures can be implemented. The book covers key areas in data mining and service-oriented computing. It presents the concepts and principles of distributed knowledge discovery and service-oriented data mining. The authors illustrate how to design services for data analytics, describe real systems for implementing distributed knowledge discovery applications, and explore mobile data mining models. They also discuss the future role of service-oriented knowledge discovery in ubiquitous discovery processes and large-scale data analytics. Highlighting the latest achievements in the field, the book gives many examples of the state of the art in service-oriented knowledge discovery. Both novices and more seasoned researchers will learn useful concepts related to distributed data mining and service-oriented data analysis. Developers will also gain insight on how to successfully use service-oriented knowledge discovery in databases (KDD) frameworks.

At its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are naturally expressed as graphs. Graph-Powered Machine Learning introduces you to graph technology concepts, highlighting the role of graphs in machine learning and big data platforms. You'll get an in-depth look at techniques including data source modeling, algorithm design, link analysis, classification, and clustering. As you master the core concepts, you'll explore three end-to-end projects that illustrate architectures, best design practices, optimization approaches, and common pitfalls. Key Features * The lifecycle of a machine learning project * Three end-to-end applications * Graphs in big data platforms * Data source modeling * Natural language processing, recommendations, and relevant search * Optimization methods Readers comfortable with machine learning basics. About the technology By organizing and analyzing your data as graphs, your applications work more fluidly with graph-centric algorithms like nearest neighbor or page rank where it's important to quickly identify and exploit relevant relationships. Modern graph data stores, like Neo4j or Amazon Neptune, are readily available tools that support graph-powered machine learning. Alessandro Negro is a Chief Scientist at GraphAware. With extensive experience in software development, software architecture, and data management, he has been a speaker at many conferences, such as Java One, Oracle Open World, and Graph Connect. He holds a Ph.D. in Computer Science and has authored several publications on graph-based machine learning.

Discusses techniques and how to use them. Includes R and Python code

Exploiting the rich information found in electronic health records (EHRs) can facilitate better medical research and improve the quality of medical practice. Until now, a trivial amount of research has been published on the challenges of leveraging this information. Addressing these challenges, Information Discovery on Electronic Health Records explores the technology to unleash the data stored in EHRs.

Assembling a truly interdisciplinary team of experts, the book tackles medical privacy concerns, the lack of standardization for the representation of EHRs, missing or incorrect values, and the availability of multiple rich health ontologies. It looks at how to search the EHR collection given a user query and return relevant fragments from the EHRs. It also explains how to mine the EHR collection to extract interesting patterns, group entities to various classes, or decide whether an EHR satisfies a given property. Most of the book focuses on textual or numeric data of EHRs, where more searching and mining progress has occurred. A chapter on the processing of medical images is also included.

Maintaining a uniform style across chapters and minimizing technical jargon, this book presents the various ways to extract useful knowledge from EHRs. It skillfully discusses how EHR data can be effectively searched and mined.

Exploring fundamental research questions, Conceptual Structures in Practice takes you through the basic yet nontrivial task of establishing conceptual relations as the foundation for research in knowledge representation and knowledge mining. It includes contributions from leading researchers in both the conceptual graph and formal concept analysis (FCA) communities. This accessible, self-contained book begins by providing the formal background in FCA and conceptual graphs. It then describes various software tools for analysis and computation, including the ToscanaJ suite. Written by the original visionaries of the field, the next section discusses the history and future directions of conceptual structures. The final chapters explore prominent application areas in computer science, including text analysis, web semantics, and intelligent systems. An unprecedented, state-of-the-art overview from innovators in the field, this volume discusses how FCA and conceptual graphs can be used in many computer science areas. It serves as a benchmark of research on conceptual structures, inspiring further exploration in this discipline.

Maintaining compatibility among all affected network and application interfaces of modern enterprise systems can quickly become costly and overwhelming. This handbook presents the knowledge and practical experience of a global group of experts from varying disciplines to help you plan and implement enterprise integration projects that respond to business needs quickly and are seamless to business users. The Handbook of Enterprise Integration brings together the latest research and application results to provide infrastructure engineers, software engineers, software developers, system designers, and project managers with a clear and comprehensive understanding of systems integration technologies, architectures, applications, and project management techniques involved in enterprise system integration. The text includes coverage of mobile communications, standards for integrated manufacturing and e-commerce, RFID, Web-based systems, and complete service-oriented enterprise modeling and analysis. Practitioners will benefit from insights on managing virtual teams as well as techniques for introducing complex technology into businesses. Covering best practices in enterprise systems integration, the text highlights applications across various business enterprises to help you: Bring together existing systems for business processes improvement Design and implement systems that can be reconfigured quickly and easily in response to evolving operational needs Establish procedures for achieving smooth migrations from legacy systems-with minimal disruption to existing operations Complete with case studies, this book illustrates the current state of the art in the context of user requirements and integration and provides the up-to-date understanding required to manage today's complex and interconnected systems.

This collection of articles is the first attempt by academics and professional writers to delve into the world of content management systems. The knowledge economy's greatest asset and primary problem is information management: finding it, validating it, re-purposing it, keeping it current, and keeping it safe. In the last few years content management software has become as common as word-processing software was five years ago. But unlike word processors, which are designed for single authorization and local storage, content management systems are designed to accommodate large-scale information production, with many authors providing many different pieces of information kept in a web-accessible database, any piece of which might find its way into electronic documents that the author doesn't even know exist. These software systems are complex, to say the least, and their impact on the field of writing will be immense.

Focusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Mainly based on the authors' own research work, the book takes a practical approach to the subject. The first part of the book reviews data mining techniques, such as artificial neural networks and support vector machines, as well as data mining applications. The second section covers the design and implementation of data mining tools for intrusion detection. It examines various designs and performance results, along with the strengths and weaknesses of the approaches. The third part presents techniques to solve the WWW prediction problem. The final part describes models that the authors have developed for image classification. Showing step by step how data mining tools are developed, this hands-on guide discusses the performance results, limitations, and unique contributions of data mining systems. It provides essential information for technologists to decide on the tools to select for a particular application, for developers to focus on alternative designs if an approach is unsuitable, and for managers to choose whether to proceed with a data mining project.