Learn Informatica in 24 Hours


Book Description

This is a practical step by step hand-on guide to learn and master Informatica. Informatica is widely used ETL tool and provided end to end data integration and management solution. This book introduces Informatica in detail. It provides a detailed step by step installation tutorial of Informatica. It teaches various activities like data cleansing, data profiling, transforming and scheduling the workflows from source to target in simple steps, etc. Here is what you will learn – Chapter 1: Introduction to Informatica Chapter 2: Informatica Architecture Tutorial Chapter 3: How to Download & Install Informatica PowerCenter Chapter 4: How to Configure Client and Repository in Informatica Chapter 5: Source Analyzer and Target Designer in Informatica Chapter 6: Mappings in Informatica: Create, Components, Parameter, Variable Chapter 7: Workflow in Informatica: Create, Task, Parameter, Reusable, Manager Chapter 8: Workflow Monitor in Informatica: Task & Gantt Chart View Examples Chapter 9: Debugger in Informatica: Session, Breakpoint, Verbose Data & Mapping Chapter 10: Session Properties in Informatica Chapter 11: Introduction to Transformations in Informatica and Filter Transformation Chapter 12: Source Qualifier Transformation in Informatica with EXAMPLE Chapter 13: Aggregator Transformation in Informatica with Example Chapter 14: Router Transformation in Informatica with EXAMPLE Chapter 15: Joiner Transformation in Informatica with EXAMPLE Chapter 16: Rank Transformation in Informatica with EXAMPLE Chapter 17: Sequence Transformation in Informatica with EXAMPLE Chapter 18: Transaction Control Transformation in Informatica with EXAMPLE Chapter 19: Lookup Transformation in Informatica & Re-usable Transformation Example Chapter 20: Normalizer Transformation in Informatica with EXAMPLE Chapter 21: Performance Tuning in Informatica ★★★Download Today ~ Free to Read for Kindle Unlimited Subscribers!★★★




Business Intelligence Demystified


Book Description

Clear your doubts about Business Intelligence and start your new journey KEY FEATURES ● Includes successful methods and innovative ideas to achieve success with BI. ● Vendor-neutral, unbiased, and based on experience. ● Highlights practical challenges in BI journeys. ● Covers financial aspects along with technical aspects. ● Showcases multiple BI organization models and the structure of BI teams. DESCRIPTION The book demystifies misconceptions and misinformation about BI. It provides clarity to almost everything related to BI in a simplified and unbiased way. It covers topics right from the definition of BI, terms used in the BI definition, coinage of BI, details of the different main uses of BI, processes that support the main uses, side benefits, and the level of importance of BI, various types of BI based on various parameters, main phases in the BI journey and the challenges faced in each of the phases in the BI journey. It clarifies myths about self-service BI and real-time BI. The book covers the structure of a typical internal BI team, BI organizational models, and the main roles in BI. It also clarifies the doubts around roles in BI. It explores the different components that add to the cost of BI and explains how to calculate the total cost of the ownership of BI and ROI for BI. It covers several ideas, including unconventional ideas to achieve BI success and also learn about IBI. It explains the different types of BI architectures, commonly used technologies, tools, and concepts in BI and provides clarity about the boundary of BI w.r.t technologies, tools, and concepts. The book helps you lay a very strong foundation and provides the right perspective about BI. It enables you to start or restart your journey with BI. WHAT YOU WILL LEARN ● Builds a strong conceptual foundation in BI. ● Gives the right perspective and clarity on BI uses, challenges, and architectures. ● Enables you to make the right decisions on the BI structure, organization model, and budget. ● Explains which type of BI solution is required for your business. ● Applies successful BI ideas. WHO THIS BOOK IS FOR This book is a must-read for business managers, BI aspirants, CxOs, and all those who want to drive the business value with data-driven insights. TABLE OF CONTENTS 1. What is Business Intelligence? 2. Why do Businesses need BI? 3. Types of Business Intelligence 4. Challenges in Business Intelligence 5. Roles in Business Intelligence 6. Financials of Business Intelligence 7. Ideas for Success with BI 8. Introduction to IBI 9. BI Architectures 10. Demystify Tech, Tools, and Concepts in BI




Artificial Neural Networks in Food Processing


Book Description

Artificial Neural Networks (ANNs) is a powerful computational tool to mimic the learning process of the mammalian brain. This book gives a comprehensive overview of ANNs including an introduction to the topic, classifications of single neurons and neural networks, model predictive control and a review of ANNs used in food processing. Also, examples of ANNs in food processing applications such as pasteurization control are illustrated.




Information and Software Technologies


Book Description

This book constitutes the refereed proceedings of the 21th International Conference on Information and Software Technologies, ICIST 2015, held in Druskininkai, Lithuania, in October 2015. The 51 papers presented were carefully reviewed and selected from 125 submissions. The papers are organized in topical sections on information systems; business intelligence for information and software systems; software engineering; information technology applications.




Advances in Databases and Information Systems


Book Description

This book constitutes the thoroughly refereed proceedings of the 18th East European Conference on Advances in Databases and Information Systems, ADBIS 2014, held in Ohrid, Macedonia, in September 2014. The 26 revised full papers presented together with one invited talk were carefully selected and reviewed from 82 submissions. The papers are organized in topical sections on data models and query languages; data warehousing; query and data-flow optimization; information extraction and integration; spatial, temporal and streaming data; data mining and knowledge discovery; data organization and physical issues; and data and business processes.




Computational Intelligence for Technology Enhanced Learning


Book Description

E-Learning has become one of the most wide spread ways of distance teaching and learning. Technologies such as Web, Grid, and Mobile and Wireless networks are pushing teaching and learning communities to find new and intelligent ways of using these technologies to enhance teaching and learning activities. Indeed, these new technologies can play an important role in increasing the support to teachers and learners, to shorten the time to learning and teaching; yet, it is necessary to use intelligent techniques to take advantage of these new technologies to achieve the desired support to teachers and learners and enhance learners’ performance in distributed learning environments. The chapters of this volume bring advances in using intelligent techniques for technology enhanced learning as well as development of e-Learning applications based on such techniques and supported by technology. Such intelligent techniques include clustering and classification for personalization of learning, intelligent context-aware techniques, adaptive learning, data mining techniques and ontologies in e-Learning systems, among others. Academics, scientists, software developers, teachers and tutors and students interested in e-Learning will find this book useful for their academic, research and practice activity.




Deep Learning for Medical Applications with Unique Data


Book Description

Deep Learning for Medical Applications with Unique Data informs readers about the most recent deep learning-based medical applications in which only unique data gathered in real cases are used. The book provides examples of how deep learning can be used in different problem areas and frameworks in both clinical and research settings, including medical image analysis, medical image registration, time series analysis, medical data synthesis, drug discovery, and pre-processing operations. The volume discusses not only positive findings, but also negative ones obtained by deep learning techniques, including the use of newly developed deep learning techniques rarely reported in the existing literature. The book excludes research works with ready data sets and includes only unique data use to better understand the state of deep learning in real-world cases, along with the feedback and user experiences from physicians and medical staff for applied deep learning-based solutions. Other applications presented in the book include hybrid solutions with deep learning support, disease diagnosis with deep learning focusing on rare diseases and cancer, patient care and treatment, genomics research, as well as research on robotics and autonomous systems. - Introduces deep learning, demonstrating concepts for a wide variety of medical applications using unique data, excluding research with ready datasets - Encompasses a wide variety of biomedical applications, including unsupervised learning, natural language processing, pattern recognition, image and video processing and disease diagnosis - Provides a robust set of methods that will help readers appropriately and judiciously use the most suitable deep learning techniques for their applications




Information Modelling and Knowledge Bases XXVI


Book Description

Within the last three decades, information modelling and knowledge bases have become essential subjects, not only for academic communities related to information systems and computer science, but also for businesses where information technology is applied. This book presents the proceedings of EJC 2014, the 24th International Conference on Information Modelling and Knowledge Bases, held in Kiel, Germany, in June 2014. The main themes of the conference were: conceptual modelling, including modelling and specification languages, domain specific conceptual modelling, and validating and communicating conceptual models; knowledge and information modelling and discovery, including knowledge representation and knowledge management, advanced data mining and analysis methods, as well as information recognition and information modelling; linguistics modelling; cross-cultural communication and social computing; environmental modelling; and multimedia data modelling and systems, which includes modelling multimedia information and knowledge, content-based multimedia data management, content-based multimedia retrieval as well as privacy and context enhancing technologies. This book will be of interest to all those who wish to keep abreast of new developments in the field of information modelling and knowledge bases.




Enriching Teaching and Learning Environments With Contemporary Technologies


Book Description

Educational technologies have revolutionized the learning and teaching environments. Offline/online applications and social media have changed the conventional learning and teaching habits and competencies. In terms of learners, it has been empirically proven that the use of educational technologies in the classroom make learning easier and more enjoyable. On the other hand, it also poses threats to students such as cyberbullying and online addiction. While exploiting the opportunities of technological use in the classroom, educators must also remain vigilant and formulate ways to overcome the challenges and risks brought by technology. Enriching Teaching and Learning Environments With Contemporary Technologies is an essential research publication that aims to present exemplary practices of technology use and their management in pedagogical purposes in learning and teaching environments. The book also analyzes problems that may arise and develops policies on educational technologies and the exploitation of technology with pedagogical purposes as part of the discussion to solve these challenges. Featuring a wide range of topics such as augmented reality, mass media, and religious education, this book is ideal for educators who want to use technology in class, educational administrators who have responsibilities for developing policies on educational technologies and managing the use of them, and researchers who want to carry out a deep investigation into the subject. Additionally, educational software developers, academicians, instructional designers, curriculum developers, education professionals, and students will also benefit from the research contained within the book.




Industrial Applications of Machine Learning


Book Description

Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems. Features Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors Includes four case studies addressing real-world industrial problems solved with machine learning techniques A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka