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business intelligence software engineer: Business Intelligence Demystified Anoop Kumar V K, 2021-09-25 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 |
business intelligence software engineer: Business Analytics for Managers Gert Laursen, Jesper Thorlund, 2010-07-13 While business analytics sounds like a complex subject, this book provides a clear and non-intimidating overview of the topic. Following its advice will ensure that your organization knows the analytics it needs to succeed, and uses them in the service of key strategies and business processes. You too can go beyond reporting!—Thomas H. Davenport, President's Distinguished Professor of IT and Management, Babson College; coauthor, Analytics at Work: Smarter Decisions, Better Results Deliver the right decision support to the right people at the right time Filled with examples and forward-thinking guidance from renowned BA leaders Gert Laursen and Jesper Thorlund, Business Analytics for Managers offers powerful techniques for making increasingly advanced use of information in order to survive any market conditions. Take a look inside and find: Proven guidance on developing an information strategy Tips for supporting your company's ability to innovate in the future by using analytics Practical insights for planning and implementing BA How to use information as a strategic asset Why BA is the next stepping-stone for companies in the information age today Discussion on BA's ever-increasing role Improve your business's decision making. Align your business processes with your business's objectives. Drive your company into a prosperous future. Taking BA from buzzword to enormous value-maker, Business Analytics for Managers helps you do it all with workable solutions that will add tremendous value to your business. |
business intelligence software engineer: Agile Management for Software Engineering David J. Anderson, 2003-09-17 A breakthrough approach to managing agile software development, Agile methods might just be the alternative to outsourcing. However, agile development must scale in scope and discipline to be acceptable in the boardrooms of the Fortune 1000. In Agile Management for Software Engineering, David J. Anderson shows managers how to apply management science to gain the full business benefits of agility through application of the focused approach taught by Eli Goldratt in his Theory of Constraints. Whether you're using XP, Scrum, FDD, or another agile approach, you'll learn how to develop management discipline for all phases of the engineering process, implement realistic financial and production metrics, and focus on building software that delivers maximum customer value and outstanding business results.Coverage includes: Making the business case for agile methods: practical tools and disciplines How to choose an agile method for your next project Breakthrough application of Critical Chain Project Management and constraint-driven control of the flow of value Defines the four new roles for the agile manager in software projects—and competitive IT organizations Whether you're a development manager, project manager, team leader, or senior IT executive, this book will help you achieve all four of your most urgent challenges: lower cost, faster delivery, improved quality, and focused alignment with the business. |
business intelligence software engineer: Business Intelligence Guidebook Rick Sherman, 2014-11-04 Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors' tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, Big Data is belittled – projects flounder, are late and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers. After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget – turning the deluge of data into actionable information that fuels business knowledge. Finally, you'll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success. - Provides practical guidelines for building successful BI, DW and data integration solutions. - Explains underlying BI, DW and data integration design, architecture and processes in clear, accessible language. - Includes the complete project development lifecycle that can be applied at large enterprises as well as at small to medium-sized businesses - Describes best practices and pragmatic approaches so readers can put them into action. - Companion website includes templates and examples, further discussion of key topics, instructor materials, and references to trusted industry sources. |
business intelligence software engineer: Developing Business Intelligence Apps for SharePoint David Feldman, Jason Himmelstein, 2013-07-02 Create dynamic business intelligence (BI) solutions for SharePoint faster and with more capabilities than previously possible. With this book, you’ll learn the entire process—from high-level concepts to development and deployment—for building data-rich BI applications with Visual Studio LightSwitch, SQL Server 2012, and a host of related Microsoft technologies. You’ll learn practical techniques and patterns necessary to use all of these technologies together as you build an example application through the course of the book, step by step. Discover how to solve real problems, using BI solutions that will evolve to meet future needs. Learn the fundamentals of SharePoint, LightSwitch, and SQL Server 2012 Get a solid grounding in BI application basics and database design principles Use LightSwitch to build a help desk app, including data model design and SharePoint data integration Build a tabular cube with Microsoft’s Business Intelligence Semantic Model (BISM) Dive into the data visualization stack, including Excel and SQL Server Reporting Services Create reports with Excel Services, Report Builder, and PowerView Use tips and tricks for setting up your BI application development environment |
business intelligence software engineer: Business Intelligence David Loshin, 2012-10-17 This completely updated best seller is a must read for anyone who wants an understanding of business intelligence, business management disciplines, data warehousing, and how all of the pieces work together. |
business intelligence software engineer: Business Intelligence and Agile Methodologies for Knowledge-Based Organizations: Cross-Disciplinary Applications Rahman El Sheikh, Asim Abdel, 2011-09-30 Business intelligence applications are of vital importance as they help organizations manage, develop, and communicate intangible assets such as information and knowledge. Organizations that have undertaken business intelligence initiatives have benefited from increases in revenue, as well as significant cost savings.Business Intelligence and Agile Methodologies for Knowledge-Based Organizations: Cross-Disciplinary Applications highlights the marriage between business intelligence and knowledge management through the use of agile methodologies. Through its fifteen chapters, this book offers perspectives on the integration between process modeling, agile methodologies, business intelligence, knowledge management, and strategic management. |
business intelligence software engineer: Business Intelligence in Microsoft SharePoint 2013 Norm Warren, Mariano Neto, Stacia Misner, Ivan Sanders, Scott A. Helmers, 2013-05-15 Dive into the business intelligence features in SharePoint 2013—and use the right combination of tools to deliver compelling solutions. Take control of business intelligence (BI) with the tools offered by SharePoint 2013 and Microsoft SQL Server 2012. Led by a group of BI and SharePoint experts, you’ll get step-by-step instructions for understanding how to use these technologies best in specific BI scenarios—whether you’re a SharePoint administrator, SQL Server developer, or business analyst. Discover how to: Manage the entire BI lifecycle, from determining key performance indicators to building dashboards Use web-based Microsoft Excel services and publish workbooks on a SharePoint Server Mash up data from multiple sources and create Data Analysis Expressions (DAX) using PowerPivot Create data-driven diagrams that provide interactive processes and context with Microsoft Visio Services Use dashboards, scorecards, reports, and key performance indicators to monitor and analyze your business Use SharePoint to view BI reports side by side, no matter which tools were used to produced them |
business intelligence software engineer: Hands-On Business Intelligence with Qlik Sense Pablo Labbe, Clever Anjos, Kaushik Solanki, Jerry DiMaso, 2019-02-28 Create dynamic dashboards to bring interactive data visualization to your enterprise using Qlik Sense Key FeaturesImplement various Qlik Sense features to create interactive dashboardsAnalyze data easily and make business decisions faster using Qlik SensePerform self-service data analytics and geospatial analytics using an example-based approachBook Description Qlik Sense allows you to explore simple-to-complex data to reveal hidden insights and data relationships to make business-driven decisions. Hands-On Business Intelligence with Qlik Sense begins by helping you get to grips with underlying Qlik concepts and gives you an overview of all Qlik Sense’s features. You will learn advanced modeling techniques and learn how to analyze the data loaded using a variety of visualization objects. You’ll also be trained on how to share apps through Qlik Sense Enterprise and Qlik Sense Cloud and how to perform aggregation with AGGR. As you progress through the chapters, you’ll explore the stories feature to create data-driven presentations and update an existing story. This book will guide you through the GeoAnalytics feature with the geo-mapping object and GeoAnalytics connector. Furthermore, you’ll learn about the self-service analytics features and perform data forecasting using advanced analytics. Lastly, you’ll deploy Qlik Sense apps for mobile and tablet. By the end of this book, you will be well-equipped to run successful business intelligence applications using Qlik Sense's functionality, data modeling techniques, and visualization best practices. What you will learnDiscover how to load, reshape, and model data for analysisApply data visualization practices to create stunning dashboardsMake use of Python and R for advanced analyticsPerform geo-analysis to create visualizations using native objectsLearn how to work with AGGR and data storiesWho this book is for If you’re a data analyst, BI developer, or interested in business intelligence and want to gain practical experience of working on Qlik Sense, this book is for you. You’ll also find it useful if you want to explore Qlik Sense’s next-generation applications for self-service business intelligence. No prior experience of working with Qlik Sense is required. |
business intelligence software engineer: Become an Effective Software Engineering Manager James Stanier, 2020-06-09 Software startups make global headlines every day. As technology companies succeed and grow, so do their engineering departments. In your career, you'll may suddenly get the opportunity to lead teams: to become a manager. But this is often uncharted territory. How can you decide whether this career move is right for you? And if you do, what do you need to learn to succeed? Where do you start? How do you know that you're doing it right? What does it even mean? And isn't management a dirty word? This book will share the secrets you need to know to manage engineers successfully. Going from engineer to manager doesn't have to be intimidating. Engineers can be managers, and fantastic ones at that. Cast aside the rhetoric and focus on practical, hands-on techniques and tools. You'll become an effective and supportive team leader that your staff will look up to. Start with your transition to being a manager and see how that compares to being an engineer. Learn how to better organize information, feel productive, and delegate, but not micromanage. Discover how to manage your own boss, hire and fire, do performance and salary reviews, and build a great team. You'll also learn the psychology: how to ship while keeping staff happy, coach and mentor, deal with deadline pressure, handle sensitive information, and navigate workplace politics. Consider your whole department. How can you work with other teams to ensure best practice? How do you help form guilds and committees and communicate effectively? How can you create career tracks for individual contributors and managers? How can you support flexible and remote working? How can you improve diversity in the industry through your own actions? This book will show you how. Great managers can make the world a better place. Join us. |
business intelligence software engineer: Artificial Intelligence Methods For Software Engineering Meir Kalech, Rui Abreu, Mark Last, 2021-06-15 Software is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE).Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges.This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering.Related Link(s) |
business intelligence software engineer: Next-Generation Business Intelligence Software with Silverlight 3 Bart Czernicki, 2011-02-02 Business intelligence (BI) software is the code and tools that allow you to view different components of a business using a single visual platform, making comprehending mountains of data easier. Applications that include reports, analytics, statistics, and historical and predictive modeling are all examples of BI applications. Currently, we are in the second generation of BI software, called BI 2.0. This generation is focused on writing BI software that is predictive, adaptive, simple, and interactive. As computers and software have evolved, more data can be presented to end users with increasingly visually rich techniques. Rich Internet application (RIA) technologies such as Microsoft Silverlight can be used to transform traditional user interfaces filled with boring data into fully interactive analytical applications to deliver insight from large data sets quickly. Furthermore, RIAs include 3D spatial design capabilities that allow for interesting layouts of aggregated data beyond a simple list or grid. BI 2.0 implemented via RIA technology can truly bring out the power of BI and deliver it to an average user via the Web. Next-Generation Business Intelligence Software with Rich Internet Applications provides developers, designers, and architects a solid foundation of BI design and architecture concepts with Microsoft Silverlight. This book covers key BI design concepts and how they can be applied without requiring an existing BI infrastructure. The author, Bart Czernicki, will show you how to build small BI applications by example that are interactive, highly visual, statistical, predictive, and most importantly, intuitive to the user. BI isn't just for the executive branch of a Fortune 500 company; it is for the masses. Let Next-Generation Business Intelligence Software with Rich Internet Applications show you how to unlock the rich intelligence you already have. |
business intelligence software engineer: Build a Career in Data Science Emily Robinson, Jacqueline Nolis, 2020-03-24 Summary You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career. About the book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book. What's inside Creating a portfolio of data science projects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with professional data scientists About the reader For readers who want to begin or advance a data science career. About the author Emily Robinson is a data scientist at Warby Parker. Jacqueline Nolis is a data science consultant and mentor. Table of Contents: PART 1 - GETTING STARTED WITH DATA SCIENCE 1. What is data science? 2. Data science companies 3. Getting the skills 4. Building a portfolio PART 2 - FINDING YOUR DATA SCIENCE JOB 5. The search: Identifying the right job for you 6. The application: Résumés and cover letters 7. The interview: What to expect and how to handle it 8. The offer: Knowing what to accept PART 3 - SETTLING INTO DATA SCIENCE 9. The first months on the job 10. Making an effective analysis 11. Deploying a model into production 12. Working with stakeholders PART 4 - GROWING IN YOUR DATA SCIENCE ROLE 13. When your data science project fails 14. Joining the data science community 15. Leaving your job gracefully 16. Moving up the ladder |
business intelligence software engineer: Software Engineering: Artificial Intelligence, Compliance, and Security Brian D'Andrade, 2021-02-16 Information security is important in every aspect of daily life. This book examines four areas where risks are present: artificial intelligence (AI), the internet of things (IoT), government and malware. The authors channel their experience and research into an accessible body of knowledge for consideration by professionals.AI is introduced as a tool for healthcare, security and innovation. The advantages of using AI in new industries are highlighted in the context of recent developments in mechanical engineering, and a survey of AI software risks is presented focusing on well-publicized failures and US FDA regulatory guidelines.The risks associated with the billions of devices that form the IoT grow with the availability of such devices in consumer products, healthcare, energy infrastructure and transportation. The risks, software engineering risk mitigation methods and standards promoting a level of care for the manufacture of IoT devices are examined because of their importance for software developers.Strategic insights for software developers looking to do business with the US federal government are presented, considering threats to both public and private sectors as well as governmental priorities from recent executive and legislative branch actions.Finally, an analysis of malicious software that infects numerous computer systems each day and causes millions of dollars in damages every year is presented. Malicious software, or malware, is software designed with hostile intent, but the damage may be mitigated with static and dynamic analyses, which are processes for studying how malware operates and analyzing potential impacts. |
business intelligence software engineer: Agile Analytics Ken Collier, 2012 Using Agile methods, you can bring far greater innovation, value, and quality to any data warehousing (DW), business intelligence (BI), or analytics project. However, conventional Agile methods must be carefully adapted to address the unique characteristics of DW/BI projects. In Agile Analytics, Agile pioneer Ken Collier shows how to do just that. Collier introduces platform-agnostic Agile solutions for integrating infrastructures consisting of diverse operational, legacy, and specialty systems that mix commercial and custom code. Using working examples, he shows how to manage analytics development teams with widely diverse skill sets and how to support enormous and fast-growing data volumes. Collier's techniques offer optimal value whether your projects involve back-end data management, front-end business analysis, or both. Part I focuses on Agile project management techniques and delivery team coordination, introducing core practices that shape the way your Agile DW/BI project community can collaborate toward success Part II presents technical methods for enabling continuous delivery of business value at production-quality levels, including evolving superior designs; test-driven DW development; version control; and project automation Collier brings together proven solutions you can apply right now--whether you're an IT decision-maker, data warehouse professional, database administrator, business intelligence specialist, or database developer. With his help, you can mitigate project risk, improve business alignment, achieve better results--and have fun along the way. |
business intelligence software engineer: The Profit Impact of Business Intelligence Steve Williams, Nancy Williams, 2010-07-27 The Profit Impact of Business Intelligence presents an A-to-Z approach for getting the most business intelligence (BI) from a company's data assets or data warehouse. BI is not just a technology or methodology, it is a powerful new management approach that – when done right – can deliver knowledge, efficiency, better decisions, and profit to almost any organization that uses it. When BI first came on the scene, it promised a lot but often failed to deliver. The missing element was the business-centric focus explained in this book. It shows how you can achieve the promise of BI by connecting it to your organization's strategic goals, culture, and strengths while correcting your BI weaknesses. It provides a practical, process-oriented guide to achieve the full promise of BI; shows how world-class companies used BI to become leaders in their industries; helps senior business and IT executives understand the strategic impact of BI and how they can ensure a strong payoff from their BI investments; and identifies the most common mistakes organizations make in implementing BI. The book also includes a helpful glossary of BI terms; a BI readiness assessment for your organization; and Web links and extensive references for more information. - A practical, process-oriented book that will help organizations realize the promise of BI - Written by Nancy and Steve Williams, veteran consultants and instructors with hands-on, in the trenches experience in government and corporate business intelligence applications - Will help senior business and IT executives understand the strategic impact of BI and how they can help ensure a strong payoff on BI investments |
business intelligence software engineer: Business Intelligence: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2015-12-29 Data analysis is an important part of modern business administration, as efficient compilation of information allows managers and business leaders to make the best decisions for the financial solvency of their organizations. Understanding the use of analytics, reporting, and data mining in everyday business environments is imperative to the success of modern businesses. Business Intelligence: Concepts, Methodologies, Tools, and Applications presents a comprehensive examination of business data analytics along with case studies and practical applications for businesses in a variety of fields and corporate arenas. Focusing on topics and issues such as critical success factors, technology adaptation, agile development approaches, fuzzy logic tools, and best practices in business process management, this multivolume reference is of particular use to business analysts, investors, corporate managers, and entrepreneurs in a variety of prominent industries. |
business intelligence software engineer: Machine Learning and Information Processing Debabala Swain, Prasant Kumar Pattnaik, Tushar Athawale, 2021-04-02 This book includes selected papers from the 2nd International Conference on Machine Learning and Information Processing (ICMLIP 2020), held at Vardhaman College of Engineering, Jawaharlal Nehru Technological University (JNTU), Hyderabad, India, from November 28 to 29, 2020. It presents the latest developments and technical solutions in the areas of advanced computing and data sciences, covering machine learning, artificial intelligence, human–computer interaction, IoT, deep learning, image processing and pattern recognition, and signal and speech processing. |
business intelligence software engineer: AI-Enabled Analytics for Business Lawrence S. Maisel, Robert J. Zwerling, Jesper H. Sorensen, 2022-01-19 We are entering the era of digital transformation where human and artificial intelligence (AI) work hand in hand to achieve data driven performance. Today, more than ever, businesses are expected to possess the talent, tools, processes, and capabilities to enable their organizations to implement and utilize continuous analysis of past business performance and events to gain forward-looking insight to drive business decisions and actions. AI-Enabled Analytics in Business is your Roadmap to meet this essential business capability. To ensure we can plan for the future vs react to the future when it arrives, we need to develop and deploy a toolbox of tools, techniques, and effective processes to reveal forward-looking unbiased insights that help us understand significant patterns, relationships, and trends. This book promotes clarity to enable you to make better decisions from insights about the future. Learn how advanced analytics ensures that your people have the right information at the right time to gain critical insights and performance opportunities Empower better, smarter decision making by implementing AI-enabled analytics decision support tools Uncover patterns and insights in data, and discover facts about your business that will unlock greater performance Gain inspiration from practical examples and use cases showing how to move your business toward AI-Enabled decision making AI-Enabled Analytics in Business is a must-have practical resource for directors, officers, and executives across various functional disciplines who seek increased business performance and valuation. |
business intelligence software engineer: Business Intelligence and Analytics in Small and Medium Enterprises Pedro Novo Melo, Carolina Machado, 2019-11-26 Technological developments in recent years have been tremendous. This evolution is visible in companies through technological equipment, computerized procedures, and management practices associated with technologies. One of the management practices that is visible is related to business intelligence and analytics (BI&A). Concepts such as data warehousing, key performance indicators (KPIs), data mining, and dashboards are changing the business arena. This book aims to promote research related to these new trends that open up a new field of research in the small and medium enterprises (SMEs) area. Features Focuses on the more recent research findings occurring in the fields of BI&A Conveys how companies in the developed world are facing today's technological challenges Shares knowledge and insights on an international scale Provides different options and strategies to manage competitive organizations Addresses several dimensions of BI&A in favor of SMEs |
business intelligence software engineer: Fundamentals of Software Engineering Hitesh Mohapatra, Amiya Kumar Rath, 2020-01-14 Practical Handbook to understand the hidden language of computer hardware and software DESCRIPTION This book teaches the essentials of software engineering to anyone who wants to become an active and independent software engineer expert. It covers all the software engineering fundamentals without forgetting a few vital advanced topics such as software engineering with artificial intelligence, ontology, and data mining in software engineering. The primary goal of the book is to introduce a limited number of concepts and practices which will achieve the following two objectives: Teach students the skills needed to execute a smallish commercial project. Provide students with the necessary conceptual background for undertaking advanced studies in software engineering through courses or on their own. KEY FEATURES - This book contains real-time executed examples along with case studies. - Covers advanced technologies that are intersectional with software engineering. - Easy and simple language, crystal clear approach, and straight forward comprehensible presentation. - Understand what architecture design involves, and where it fits in the full software development life cycle. - Learning and optimizing the critical relationships between analysis and design. - Utilizing proven and reusable design primitives and adapting them to specific problems and contexts. WHAT WILL YOU LEARN This book includes only those concepts that we believe are foundational. As executing a software project requires skills in two dimensionsÑengineering and project managementÑthis book focuses on crucial tasks in these two dimensions and discuss the concepts and techniques that can be applied to execute these tasks effectively.Ê WHO THIS BOOK IS FOR The book is primarily intended to work as a beginnerÕs guide for Software Engineering in any undergraduate or postgraduate program. It is directed towards students who know the program but have not had formal exposure to software engineering. The book can also be used by teachers and trainers who are in a similar stateÑthey know some programming but want to be introduced to the systematic approach of software engineering. TABLE OF CONTENTS 1. Introductory Concepts of Software Engineering 2. Modelling Software Development Life Cycle 3. Software Requirement Analysis and Specification 4. Software Project Management Framework 5. Software Project Analysis and Design 6. Object-Oriented Analysis and Design 7. Designing Interfaces & Dialogues and Database Design 8. Coding and Debugging 9. Software Testing 10. System Implementation and Maintenance 11.Reliability 12.ÊSoftware Quality 13. CASE and Reuse 14. Recent Trends and Development in Software Engineering 15.ÊModel Questions with Answers |
business intelligence software engineer: Introduction to R for Business Intelligence Jay Gendron, 2016-08-26 Learn how to leverage the power of R for Business Intelligence About This Book Use this easy-to-follow guide to leverage the power of R analytics and make your business data more insightful. This highly practical guide teaches you how to develop dashboards that help you make informed decisions using R. Learn the A to Z of working with data for Business Intelligence with the help of this comprehensive guide. Who This Book Is For This book is for data analysts, business analysts, data science professionals or anyone who wants to learn analytic approaches to business problems. Basic familiarity with R is expected. What You Will Learn Extract, clean, and transform data Validate the quality of the data and variables in datasets Learn exploratory data analysis Build regression models Implement popular data-mining algorithms Visualize results using popular graphs Publish the results as a dashboard through Interactive Web Application frameworks In Detail Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance. In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards. After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence. Style and approach This book will take a step-by-step approach and instruct you in how you can achieve Business Intelligence from scratch using R. We will start with extracting data and then move towards exploring, analyzing, and visualizing it. Eventually, you will learn how to create insightful dashboards that help you make informed decisions—and all of this with the help of real-life examples. |
business intelligence software engineer: Silverlight 4 Business Intelligence Software Bart Czernicki, 2011-01-27 Business intelligence (BI) software allows you to view different components of a business using a single visual platform, which makes comprehending mountains of data easier. BI is everywhere. Applications that include reports, analytics, statistics, and historical and predictive modeling are all examples of business intelligence. Currently, we are in the second generation of business intelligence software—called BI 2.0—which is focused on writing business intelligence software that is predictive, adaptive, simple, and interactive. As computers and software have evolved, more data can be presented to end users with increasingly visually rich techniques. Rich Internet application (RIA) technologies such as Microsoft Silverlight can be used to transform traditional user-interfaces filled with boring data into fully interactive analytical applications that quickly deliver insight from large data sets. Furthermore, RIAs now include 3D spatial-design capabilities that move beyond a simple list or grid and allow for interesting layouts of aggregated data. BI 2.0 implemented via an RIA technology can truly bring out the power of business intelligence and deliver it to an average user on the Web. Silverlight 4 Business Intelligence Software provides developers, designers, and architects with a solid foundation in business intelligence design and architecture concepts for Microsoft Silverlight. This book covers key business intelligence design concepts and how they can be applied without an existing BI infrastructure. Author Bart Czernicki provides you with examples of how to build small BI applications that are interactive, highly visual, statistical, predictive—and most importantly—intuitive to the end-user. Business intelligence isn’t just for the executive branch of a Fortune 500 company—it is for the masses. Let Silverlight 4 Business Intelligence Software show you how to unlock the rich intelligence you already have. |
business intelligence software engineer: Organizational Integration of Enterprise Systems and Resources: Advancements and Applications Varajão, João Eduardo Quintela Alves de Sousa, 2012-06-30 The topic of Enterprise Information Systems (EIS) is having an increasingly relevant strategic impact on global business and the world economy, and organizations are undergoing hard investments in search of the rewarding benefits of efficiency and effectiveness that these ranges of solutions promise. Organizational Integration of Enterprise Systems and Resources: Advancements and Applications show that EIS are at the same time responsible for tremendous gains in some companies and tremendous losses in others. Therefore, their adoption should be carefully planned and managed. This title highlights new ways to identify opportunities and overtake trends and challenges of EIS selection, adoption, and exploitation as it is filled with models, solutions, tools, and case studies. The book provides researchers, scholars, and professionals with some of the most advanced research, solutions, and discussions of Enterprise Information Systems design, implementation, and management. |
business intelligence software engineer: Enterprise Software Architecture and Design Dominic Duggan, 2012-02-28 This book fills a gap between high-level overview texts that are often too general and low-level detail oriented technical handbooks that lose sight the big picture. This book discusses SOA from the low-level perspective of middleware, various XML-based technologies, and basic service design. It also examines broader implications of SOA, particularly where it intersects with business process management and process modeling. Concrete overviews will be provided of the methodologies in those fields, so that students will have a hands-on grasp of how they may be used in the context of SOA. |
business intelligence software engineer: Performance Dashboards Wayne W. Eckerson, 2005-10-27 Tips, techniques, and trends on how to use dashboard technology to optimize business performance Business performance management is a hot new management discipline that delivers tremendous value when supported by information technology. Through case studies and industry research, this book shows how leading companies are using performance dashboards to execute strategy, optimize business processes, and improve performance. Wayne W. Eckerson (Hingham, MA) is the Director of Research for The Data Warehousing Institute (TDWI), the leading association of business intelligence and data warehousing professionals worldwide that provide high-quality, in-depth education, training, and research. He is a columnist for SearchCIO.com, DM Review, Application Development Trends, the Business Intelligence Journal, and TDWI Case Studies & Solution. |
business intelligence software engineer: Oracle Business Intelligence Yuli Vailiev, 2010-10-12 A fast track guide to uncovering the analytical power of Oracle Business Intelligence: Analytic SQL, Oracle Discoverer, Oracle Reports, and Oracle Warehouse Builder with this book and eBook. |
business intelligence software engineer: Signal , 2012 |
business intelligence software engineer: Software Engineering Elvis Foster, Bradford Towle Jr., 2021-07-19 Software Engineering: A Methodical Approach (Second Edition) provides a comprehensive, but concise introduction to software engineering. It adopts a methodical approach to solving software engineering problems, proven over several years of teaching, with outstanding results. The book covers concepts, principles, design, construction, implementation, and management issues of software engineering. Each chapter is organized systematically into brief, reader-friendly sections, with itemization of the important points to be remembered. Diagrams and illustrations also sum up the salient points to enhance learning. Additionally, the book includes the author’s original methodologies that add clarity and creativity to the software engineering experience. New in the Second Edition are chapters on software engineering projects, management support systems, software engineering frameworks and patterns as a significant building block for the design and construction of contemporary software systems, and emerging software engineering frontiers. The text starts with an introduction of software engineering and the role of the software engineer. The following chapters examine in-depth software analysis, design, development, implementation, and management. Covering object-oriented methodologies and the principles of object-oriented information engineering, the book reinforces an object-oriented approach to the early phases of the software development life cycle. It covers various diagramming techniques and emphasizes object classification and object behavior. The text features comprehensive treatments of: Project management aids that are commonly used in software engineering An overview of the software design phase, including a discussion of the software design process, design strategies, architectural design, interface design, database design, and design and development standards User interface design Operations design Design considerations including system catalog, product documentation, user message management, design for real-time software, design for reuse, system security, and the agile effect Human resource management from a software engineering perspective Software economics Software implementation issues that range from operating environments to the marketing of software Software maintenance, legacy systems, and re-engineering This textbook can be used as a one-semester or two-semester course in software engineering, augmented with an appropriate CASE or RAD tool. It emphasizes a practical, methodical approach to software engineering, avoiding an overkill of theoretical calculations where possible. The primary objective is to help students gain a solid grasp of the activities in the software development life cycle to be confident about taking on new software engineering projects. |
business intelligence software engineer: Site Reliability Engineering Niall Richard Murphy, Betsy Beyer, Chris Jones, Jennifer Petoff, 2016-03-23 The overwhelming majority of a software system’s lifespan is spent in use, not in design or implementation. So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems? In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient—lessons directly applicable to your organization. This book is divided into four sections: Introduction—Learn what site reliability engineering is and why it differs from conventional IT industry practices Principles—Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE) Practices—Understand the theory and practice of an SRE’s day-to-day work: building and operating large distributed computing systems Management—Explore Google's best practices for training, communication, and meetings that your organization can use |
business intelligence software engineer: Business Intelligence Roadmap Larissa T. Moss, Shaku Atre, 2003-02-25 If you are looking for a complete treatment of business intelligence, then go no further than this book. Larissa T. Moss and Shaku Atre have covered all the bases in a cohesive and logical order, making it easy for the reader to follow their line of thought. From early design to ETL to physical database design, the book ties together all the components of business intelligence. --Bill Inmon, Inmon Enterprises This is the eBook version of the print title. The eBook edition contains the same content as the print edition. You will find instructions in the last few pages of your eBook that directs you to the media files. Business Intelligence Roadmap is a visual guide to developing an effective business intelligence (BI) decision-support application. This book outlines a methodology that takes into account the complexity of developing applications in an integrated BI environment. The authors walk readers through every step of the process--from strategic planning to the selection of new technologies and the evaluation of application releases. The book also serves as a single-source guide to the best practices of BI projects. Part I steers readers through the six stages of a BI project: justification, planning, business analysis, design, construction, and deployment. Each chapter describes one of sixteen development steps and the major activities, deliverables, roles, and responsibilities. All technical material is clearly expressed in tables, graphs, and diagrams. Part II provides five matrices that serve as references for the development process charted in Part I. Management tools, such as graphs illustrating the timing and coordination of activities, are included throughout the book. The authors conclude by crystallizing their many years of experience in a list of dos, don'ts, tips, and rules of thumb. Both the book and the methodology it describes are designed to adapt to the specific needs of individual stakeholders and organizations. The book directs business representatives, business sponsors, project managers, and technicians to the chapters that address their distinct responsibilities. The framework of the book allows organizations to begin at any step and enables projects to be scheduled and managed in a variety of ways. Business Intelligence Roadmap is a clear and comprehensive guide to negotiating the complexities inherent in the development of valuable business intelligence decision-support applications. |
business intelligence software engineer: Data Virtualization for Business Intelligence Systems Rick van der Lans, 2012-07-25 Data virtualization can help you accomplish your goals with more flexibility and agility. Learn what it is and how and why it should be used with Data Virtualization for Business Intelligence Systems. In this book, expert author Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects. You'll learn the difference is between this new form of data integration and older forms, such as ETL and replication, and gain a clear understanding of how data virtualization really works. Data Virtualization for Business Intelligence Systems outlines the advantages and disadvantages of data virtualization and illustrates how data virtualization should be applied in data warehouse environments. You'll come away with a comprehensive understanding of how data virtualization will make data warehouse environments more flexible and how it make developing operational BI applications easier. Van der Lans also describes the relationship between data virtualization and related topics, such as master data management, governance, and information management, so you come away with a big-picture understanding as well as all the practical know-how you need to virtualize your data. - First independent book on data virtualization that explains in a product-independent way how data virtualization technology works. - Illustrates concepts using examples developed with commercially available products. - Shows you how to solve common data integration challenges such as data quality, system interference, and overall performance by following practical guidelines on using data virtualization. - Apply data virtualization right away with three chapters full of practical implementation guidance. - Understand the big picture of data virtualization and its relationship with data governance and information management. |
business intelligence software engineer: Business Intelligence Career Master Plan Eduardo Chavez, Danny Moncada, 2023-08-31 Learn the foundations of business intelligence, sector trade-offs, organizational structures, and technology stacks while mastering coursework, certifications, and interview success strategies Purchase of the print or Kindle book includes a free PDF eBook Key Features Identify promising job opportunities and ideal entry point into BI Build, design, implement, and maintain BI systems successfully Ace your BI interview with author's expert guidance on certifications, trainings, and courses Book DescriptionNavigating the challenging path of a business intelligence career requires you to consider your expertise, interests, and skills. Business Intelligence Career Master Plan explores key skills like stacks, coursework, certifications, and interview advice, enabling you to make informed decisions about your BI journey. You’ll start by assessing the different roles in BI and matching your skills and career with the tech stack. You’ll then learn to build taxonomy and a data story using visualization types. Additionally, you’ll explore the fundamentals of programming, frontend development, backend development, software development lifecycle, and project management, giving you a broad view of the end-to-end BI process. With the help of the author’s expert advice, you’ll be able to identify what subjects and areas of study are crucial and would add significant value to your skill set. By the end of this book, you’ll be well-equipped to make an informed decision on which of the myriad paths to choose in your business intelligence journey based on your skill set and interests.What you will learn Understand BI roles, roadmap, and technology stack Accelerate your career and land your first job in the BI industry Build the taxonomy of various data sources for your organization Use the AdventureWorks database and PowerBI to build a robust data model Create compelling data stories using data visualization Automate, templatize, standardize, and monitor systems for productivity Who this book is for This book is for BI developers and business analysts who are passionate about data and are looking to advance their proficiency and career in business intelligence. While foundational knowledge of tools like Microsoft Excel is required, having a working knowledge of SQL, Python, Tableau, and major cloud providers such as AWS or GCP will be beneficial. |
business intelligence software engineer: Rethinking Productivity in Software Engineering Caitlin Sadowski, Thomas Zimmermann, 2019-05-07 Get the most out of this foundational reference and improve the productivity of your software teams. This open access book collects the wisdom of the 2017 Dagstuhl seminar on productivity in software engineering, a meeting of community leaders, who came together with the goal of rethinking traditional definitions and measures of productivity. The results of their work, Rethinking Productivity in Software Engineering, includes chapters covering definitions and core concepts related to productivity, guidelines for measuring productivity in specific contexts, best practices and pitfalls, and theories and open questions on productivity. You'll benefit from the many short chapters, each offering a focused discussion on one aspect of productivity in software engineering. Readers in many fields and industries will benefit from their collected work. Developers wanting to improve their personal productivity, will learn effective strategies for overcoming common issues that interfere with progress. Organizations thinking about building internal programs for measuring productivity of programmers and teams will learn best practices from industry and researchers in measuring productivity. And researchers can leverage the conceptual frameworks and rich body of literature in the book to effectively pursue new research directions. What You'll LearnReview the definitions and dimensions of software productivity See how time management is having the opposite of the intended effect Develop valuable dashboards Understand the impact of sensors on productivity Avoid software development waste Work with human-centered methods to measure productivity Look at the intersection of neuroscience and productivity Manage interruptions and context-switching Who Book Is For Industry developers and those responsible for seminar-style courses that include a segment on software developer productivity. Chapters are written for a generalist audience, without excessive use of technical terminology. |
business intelligence software engineer: Big Data: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2016-04-20 The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics. |
business intelligence software engineer: InfoWorld , 2004-10-11 InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects. |
business intelligence software engineer: Co-locating Transactional and Data Warehouse Workloads on System z Mike Ebbers, Dino Tonelli, Jason Arnold, Patric Becker, Yuan-Chi Chang, Willie Favero, Shantan Kethireddy, Nin Lei, Shirley Lin, Ron Lounsbury, Susan Widing Lynch, Cristian Molaro, Deepak Rangarao, Michael Schapira, IBM Redbooks, 2010-12-03 As business cycles speed up, many customers gain significant competitive advantage from quicker and more accurate business decision-making by using real data. For many customers, choosing the path to co-locate their transactional and analytical workloads on System z® better leverages their existing investment in hardware, software, and skills. We created a project to address a number of best practice questions on how to manage these newer, analytical type workloads, especially when co-located with traditional transactional workloads. The goal of this IBM® Redbooks® publication is to provide technical guidance and performance trade-offs associated with resource management and potentially DB2® data-sharing in a variety of mixed transactional / data warehouse System z topologies. The term co-location used here and in the rest of the book is specifically defined as the practice of housing both transactional (OLTP) and data warehouse (analytical) workloads within the same System z configuration. We also assumed that key portions of the transactional and data warehouse databases would reside on DB2 for z/OS®. The databases may or may not reside in a DB2 data-sharing environment; we discuss those pros and cons in this book. The intended audience includes DB2 data warehouse architects and practitioners who are facing choices in resource management and system topologies in the data warehouse arena. This specifically includes Business Intelligence (BI) administrators, DB2 database administrators (DBAs) and z/OS performance administrators / systems programmers. In addition, decision makers and architects can utilize this book to assist in making platform and database topology decisions. The book is divided into four parts. Part I, Introducing the co-location project covers the System z value proposition and why one should consider System z as the central platform for their data warehousing / business analytics needs. Some topics are risk avoidance via data consolidation, continuous availability, simplified disaster recovery, IBM Smart Analytics Optimizer, reduced network bandwidth requirements, and the unique virtualization and resource management capabilities of System z LPAR, z/VM® and WLM. Part I also provides some of the common System z co-location topologies along with an explanation of the general pros and cons of each. This would be useful input for an architect to understand where a customer is today and where they might consider moving to. Part II, Project environment covers the environment, products, workloads, workload drivers, and data models implemented for this study. The environment consisted of a logically partitioned z10TM 32way, running z/VM, Linux®, and z/OS operating system instances. On those instances we ran products such as z/OS DB2 V9, IBM Cognos® Business Intelligence Version 8.4 for Linux on System z, InfoSphereTM Warehouse for System z, InfoSphere Change Data Capture, z/OS WebSphere® V7, Tivoli® Omegamon for DB2 Performance expert. Utilizing these products we created transactional (OLTP), data warehouse query, and data warehouse refresh workloads. All the workloads were based on an existing web-based transactional Bookstore workload, that's currently utilized for internal testing within the System p® and z labs. While some IBM Cognos BI and ISWz product usage and experiences information is covered in this book, we do not go into the depth typically found in IBM Redbooks publications, since there's another book focused specifically on that |
business intelligence software engineer: Network World , 2002-12-02 For more than 20 years, Network World has been the premier provider of information, intelligence and insight for network and IT executives responsible for the digital nervous systems of large organizations. Readers are responsible for designing, implementing and managing the voice, data and video systems their companies use to support everything from business critical applications to employee collaboration and electronic commerce. |
business intelligence software engineer: InfoWorld , 2002-12-02 InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects. |
business intelligence software engineer: Internet-enabled Business Intelligence William A. Giovinazzo, 2003 William Giovinazzo gives experienced database professionals practical guidance for every aspect of planning and deploying Web-based data warehouses -- and leveraging them for competitive advantage. Unlike previous books, The Web-Enabled Data Warehouse covers all the enabling technologies and analysis approaches you need to know about -- from XML to CRM, Java to customer profiling. Giovinazzo begins by introducing the compelling advantages of integrating business intelligence and data warehouses with Web technology. He reviews the business and technical contexts in which the Web-enabled data warehouse will operate; shows how to build and optimize data warehouse infrastructure, and presents in-depth coverage of key enabling technologies -- including Java, XML and XSL, LDAP directories, and WAP wireless development environments. In the book's final section, Giovinazzo introduces and explains powerful new analysis techniques that can dramatically improve your understanding of customers -- and shows how to integrate data warehouses with CRM and other enterprise systems so you can act on your knowledge far more quickly and efficiently. For every experienced database professional seeking to understand or deploy Web-based data warehouses. |
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….