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| business analytics project example: How to Start a Business Analyst Career Laura Brandenburg, 2015-01-02 You may be wondering if business analysis is the right career choice, debating if you have what it takes to be successful as a business analyst, or looking for tips to maximize your business analysis opportunities. With the average salary for a business analyst in the United States reaching above $90,000 per year, more talented, experienced professionals are pursuing business analysis careers than ever before. But the path is not clear cut. No degree will guarantee you will start in a business analyst role. What's more, few junior-level business analyst jobs exist. Yet every year professionals with experience in other occupations move directly into mid-level and even senior-level business analyst roles. My promise to you is that this book will help you find your best path forward into a business analyst career. More than that, you will know exactly what to do next to expand your business analysis opportunities. |
| business analytics project example: Business Analysis For Dummies Kupe Kupersmith, Paul Mulvey, Kate McGoey, 2013-07-01 Your go-to guide on business analysis Business analysis refers to the set of tasks and activities that help companies determine their objectives for meeting certain opportunities or addressing challenges and then help them define solutions to meet those objectives. Those engaged in business analysis are charged with identifying the activities that enable the company to define the business problem or opportunity, define what the solutions looks like, and define how it should behave in the end. As a BA, you lay out the plans for the process ahead. Business Analysis For Dummies is the go to reference on how to make the complex topic of business analysis easy to understand. Whether you are new or have experience with business analysis, this book gives you the tools, techniques, tips and tricks to set your project’s expectations and on the path to success. Offers guidance on how to make an impact in your organization by performing business analysis Shows you the tools and techniques to be an effective business analysis professional Provides a number of examples on how to perform business analysis regardless of your role If you're interested in learning about the tools and techniques used by successful business analysis professionals, Business Analysis For Dummies has you covered. |
| business analytics project example: Analytics Phil Simon, 2017-07-03 For years, organizations have struggled to make sense out of their data. IT projects designed to provide employees with dashboards, KPIs, and business-intelligence tools often take a year or more to reach the finish line...if they get there at all. This has always been a problem. Today, though, it's downright unacceptable. The world changes faster than ever. Speed has never been more important. By adhering to antiquated methods, firms lose the ability to see nascent trends—and act upon them until it's too late. But what if the process of turning raw data into meaningful insights didn't have to be so painful, time-consuming, and frustrating? What if there were a better way to do analytics? Fortunately, you're in luck... Analytics: The Agile Way is the eighth book from award-winning author and Arizona State University professor Phil Simon. Analytics: The Agile Way demonstrates how progressive organizations such as Google, Nextdoor, and others approach analytics in a fundamentally different way. They are applying the same Agile techniques that software developers have employed for years. They have replaced large batches in favor of smaller ones...and their results will astonish you. Through a series of case studies and examples, Analytics: The Agile Way demonstrates the benefits of this new analytics mind-set: superior access to information, quicker insights, and the ability to spot trends far ahead of your competitors. |
| business analytics project example: Practical Business Analytics Using SAS Shailendra Kadre, Venkat Reddy Konasani, 2015-02-07 Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios. The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big data experts—first show how SAS is used in business, and then how to get started programming in SAS by importing data and learning how to manipulate it. Besides illustrating SAS basic functions, you will see how each function can be used to get the information you need to improve business performance. Each chapter offers hands-on exercises drawn from real business situations. The book then provides an overview of statistics, as well as instruction on exploring data, preparing it for analysis, and testing hypotheses. You will learn how to use SAS to perform analytics and model using both basic and advanced techniques like multiple regression, logistic regression, and time series analysis, among other topics. The book concludes with a chapter on analyzing big data. Illustrations from banking and other industries make the principles and methods come to life. Readers will find just enough theory to understand the practical examples and case studies, which cover all industries. Written for a corporate IT and programming audience that wants to upgrade skills or enter the analytics field, this book includes: More than 200 examples and exercises, including code and datasets for practice. Relevant examples for all industries. Case studies that show how to use SAS analytics to identify opportunities, solve complicated problems, and chart a course. Practical Business Analytics Using SAS: A Hands-on Guide gives you the tools you need to gain insight into the data at your fingertips, predict business conditions for better planning, and make excellent decisions. Whether you are in retail, finance, healthcare, manufacturing, government, or any other industry, this book will help your organization increase revenue, drive down costs, improve marketing, and satisfy customers better than ever before. |
| business analytics project example: Implementing Analytics Nauman Sheikh, 2013-05-06 Implementing Analytics demystifies the concept, technology and application of analytics and breaks its implementation down to repeatable and manageable steps, making it possible for widespread adoption across all functions of an organization. Implementing Analytics simplifies and helps democratize a very specialized discipline to foster business efficiency and innovation without investing in multi-million dollar technology and manpower. A technology agnostic methodology that breaks down complex tasks like model design and tuning and emphasizes business decisions rather than the technology behind analytics. - Simplifies the understanding of analytics from a technical and functional perspective and shows a wide array of problems that can be tackled using existing technology - Provides a detailed step by step approach to identify opportunities, extract requirements, design variables and build and test models. It further explains the business decision strategies to use analytics models and provides an overview for governance and tuning - Helps formalize analytics projects from staffing, technology and implementation perspectives - Emphasizes machine learning and data mining over statistics and shows how the role of a Data Scientist can be broken down and still deliver the value by building a robust development process |
| business analytics project example: Data Analysis for Business, Economics, and Policy Gábor Békés, Gábor Kézdi, 2021-05-06 A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data. |
| business analytics project example: Business Analytics Jay Liebowitz, 2013-12-19 Together, Big Data, high-performance computing, and complex environments create unprecedented opportunities for organizations to generate game-changing insights that are based on hard data. Business Analytics: An Introduction explains how to use business analytics to sort through an ever-increasing amount of data and improve the decision-making cap |
| business analytics project example: An Introduction to Business Analytics Ger Koole, 2019 Business Analytics (BA) is about turning data into decisions. This book covers the full range of BA topics, including statistics, machine learning and optimization, in a way that makes them accessible to a broader audience. Decision makers will gain enough insight into the subject to have meaningful discussions with machine learning specialists, and those starting out as data scientists will benefit from an overview of the field and take their first steps as business analytics specialist. Through this book and the various exercises included, you will be equipped with an understanding of BA, while learning R, a popular tool for statistics and machine learning. |
| business analytics project example: Business analyst: a profession and a mindset Yulia Kosarenko, 2019-05-12 What does it mean to be a business analyst? What would you do every day? How will you bring value to your clients? And most importantly, what makes a business analyst exceptional? This book will answer your questions about this challenging career choice through the prism of the business analyst mindset — a concept developed by the author, and its twelve principles demonstrated through many case study examples. Business analyst: a profession and a mindset is a structurally rich read with over 90 figures, tables and models. It offers you more than just techniques and methodologies. It encourages you to understand people and their behaviour as the key to solving business problems. |
| business analytics project example: R for Business Analytics A Ohri, 2012-09-14 This book examines common tasks performed by business analysts and helps the reader navigate the wealth of information in R and its 4000 packages to create useful analytics applications. Includes interviews with corporate users of R, and easy-to-use examples. |
| business analytics project example: 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 analytics project example: Data Science for Business Foster Provost, Tom Fawcett, 2013-07-27 Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the data-analytic thinking necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates |
| business analytics project example: Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner Olivia Parr-Rud, 2014-10 This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. This beginnner's guide with clear, illustrated, step-by-step instructions will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence. -- |
| business analytics project example: Applied Business Analytics Nathaniel Lin, 2015 Now that you've collected the data and crunched the numbers, what do you do with all this information? How do you take the fruit of your analytics labor and apply it to business decision making? How do you actually apply the information gleaned from quants and tech teams? Applied Business Analytics will help you find optimal answers to these questions, and bridge the gap between analytics and execution in your organization. Nathaniel Lin explains why analytics value chains often break due to organizational and cultural issues, and offers in the trenches guidance for overcoming these obstacles. You'll learn why a special breed of analytics deciders is indispensable for any organization that seeks to compete on analytics; how to become one of those deciders; and how to identify, foster, support, empower, and reward others who join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at every level: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ -- and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer |
| business analytics project example: The PMI Guide to Business Analysis , 2017-12-22 The Standard for Business Analysis – First Edition is a new PMI foundational standard, developed as a basis for business analysis for portfolio, program, and project management. This standard illustrates how project management processes and business analysis processes are complementary activities, where the primary focus of project management processes is the project and the primary focus of business analysis processes is the product. This is a process-based standard, aligned with A Guide to the Project Management Body of Knowledge (PMBOK® Guide) – Sixth Edition, and to be used as a standard framework contributing to the business analysis body of knowledge. |
| business analytics project example: Aligning Business Strategies and Analytics Murugan Anandarajan, Teresa D. Harrison, 2018-09-27 This book examines issues related to the alignment of business strategies and analytics. Vast amounts of data are being generated, collected, stored, processed, analyzed, distributed and used at an ever-increasing rate by organizations. Simultaneously, managers must rapidly and thoroughly understand the factors driving their business. Business Analytics is an interactive process of analyzing and exploring enterprise data to find valuable insights that can be exploited for competitive advantage. However, to gain this advantage, organizations need to create a sophisticated analytical climate within which strategic decisions are made. As a result, there is a growing awareness that alignment among business strategies, business structures, and analytics are critical to effectively develop and deploy techniques to enhance an organization’s decision-making capability. In the past, the relevance and usefulness of academic research in the area of alignment is often questioned by practitioners, but this book seeks to bridge this gap. Aligning Business Strategies and Analytics: Bridging Between Theory and Practice is comprised of twelve chapters, divided into three sections. The book begins by introducing business analytics and the current gap between academic training and the needs within the business community. Chapters 2 - 5 examines how the use of cognitive computing improves financial advice, how technology is accelerating the growth of the financial advising industry, explores the application of advanced analytics to various facets of the industry and provides the context for analytics in practice. Chapters 6 - 9 offers real-world examples of how project management professionals tackle big-data challenges, explores the application of agile methodologies, discusses the operational benefits that can be gained by implementing real-time, and a case study on human capital analytics. Chapters 10 - 11 reviews the opportunities and potential shortfall and highlights how new media marketing and analytics fostered new insights. Finally the book concludes with a look at how data and analytics are playing a revolutionary role in strategy development in the chemical industry. |
| business analytics project example: Business Analytics with Management Science Models and Methods Arben Asllani, 2015 This book is about prescriptive analytics. It provides business practitioners and students with a selected set of management science and optimization techniques and discusses the fundamental concepts, methods, and models needed to understand and implement these techniques in the era of Big Data. A large number of management science models exist in the body of literature today. These models include optimization techniques or heuristics, static or dynamic programming, and deterministic or stochastic modeling. The topics selected in this book, mathematical programming and simulation modeling, are believed to be among the most popular management science tools, as they can be used to solve a majority of business optimization problems. Over the years, these techniques have become the weapon of choice for decision makers and practitioners when dealing with complex business systems. |
| business analytics project example: Business Intelligence Roadmap Larissa Terpeluk Moss, S. Atre, 2003 This software will enable the user to learn about business intelligence roadmap. |
| business analytics project example: Mining Your Own Business Jeff Deal, Gerhard Pilcher, 2016-09-19 Practical guide for organization leaders, top-level executives. Industry experts explain in clear, understandable English. What data mining and predictive analytics are |
| business analytics project example: Win with Advanced Business Analytics Jean-Paul Isson, Jesse Harriott, 2012-09-25 Plain English guidance for strategic business analytics and big data implementation In today's challenging economy, business analytics and big data have become more and more ubiquitous. While some businesses don't even know where to start, others are struggling to move from beyond basic reporting. In some instances management and executives do not see the value of analytics or have a clear understanding of business analytics vision mandate and benefits. Win with Advanced Analytics focuses on integrating multiple types of intelligence, such as web analytics, customer feedback, competitive intelligence, customer behavior, and industry intelligence into your business practice. Provides the essential concept and framework to implement business analytics Written clearly for a nontechnical audience Filled with case studies across a variety of industries Uniquely focuses on integrating multiple types of big data intelligence into your business Companies now operate on a global scale and are inundated with a large volume of data from multiple locations and sources: B2B data, B2C data, traffic data, transactional data, third party vendor data, macroeconomic data, etc. Packed with case studies from multiple countries across a variety of industries, Win with Advanced Analytics provides a comprehensive framework and applications of how to leverage business analytics/big data to outpace the competition. |
| business analytics project example: Data Analytics in Project Management Seweryn Spalek, J. Davidson Frame, Yanping Chen, Carl Pritchard, Alfonso Bucero, Werner Meyer, Ryan Legard, Michael Bragen, Klas Skogmar, Deanne Larson, Bert Brijs, 2019-01-01 Data Analytics in Project Management. Data analytics plays a crucial role in business analytics. Without a rigid approach to analyzing data, there is no way to glean insights from it. Business analytics ensures the expected value of change while that change is implemented by projects in the business environment. Due to the significant increase in the number of projects and the amount of data associated with them, it is crucial to understand the areas in which data analytics can be applied in project management. This book addresses data analytics in relation to key areas, approaches, and methods in project management. It examines: • Risk management • The role of the project management office (PMO) • Planning and resource management • Project portfolio management • Earned value method (EVM) • Big Data • Software support • Data mining • Decision-making • Agile project management Data analytics in project management is of increasing importance and extremely challenging. There is rapid multiplication of data volumes, and, at the same time, the structure of the data is more complex. Digging through exabytes and zettabytes of data is a technological challenge in and of itself. How project management creates value through data analytics is crucial. Data Analytics in Project Management addresses the most common issues of applying data analytics in project management. The book supports theory with numerous examples and case studies and is a resource for academics and practitioners alike. It is a thought-provoking examination of data analytics applications that is valuable for projects today and those in the future. |
| business analytics project example: Analytics and Knowledge Management Suliman Hawamdeh, Hsia-Ching Chang, 2018-08-06 The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms. |
| business analytics project example: Business Analysis and Leadership Penny Pullan, James Archer, 2013-09-03 21st century organizations, across all sectors and of all types, have to cope with an international marketplace where change is frequent and customer expectations continue to rise. The work of business analysis professionals is crucial if organizations are to succeed and grow. If change programmes are to be successful, stakeholder engagement and situation analysis are vital, and to achieve this, senior business people need to display competence in a range of areas, not least of which include the ability to challenge, lead and influence. Business Analysis and Leadership is for anyone involved in business analysis working in any organization worldwide, from financial services to charities, government to manufacturing. It takes the reader beyond standard textbooks full of techniques and tools, advising on how to lead and gain credibility throughout the organization. It will help you with the tricky role of working with people from the shop floor to board directors and give readers the confidence to challenge the easy way forward and point out what will really work in practice. This inspirational book consists of contributions from leading thinkers and practitioners in business analysis from around the world. Their case studies, practical advice and downloadable appendices will help the reader to develop leadership skills and become an outstanding catalyst for change. |
| business analytics project example: CBAP Certification Study Guide V3. 0 Richard Larson, Elizabeth Larson, 2015-06-01 |
| business analytics project example: 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 analytics project example: Business Analytics Rahul Saxena, Anand Srinivasan, 2012-12-05 This book provides a guide to businesses on how to use analytics to help drive from ideas to execution. Analytics used in this way provides “full lifecycle support” for business and helps during all stages of management decision-making and execution. The framework presented in the book enables the effective interplay of business, analytics, and information technology (business intelligence) both to leverage analytics for competitive advantage and to embed the use of business analytics into the business culture. It lays out an approach for analytics, describes the processes used, and provides guidance on how to scale analytics and how to develop analytics teams. It provides tools to improve analytics in a broad range of business situations, regardless of the level of maturity and the degree of executive sponsorship provided. As a guide for practitioners and managers, the book will benefit people who work in analytics teams, the managers and leaders who manage, use and sponsor analytics, and those who work with and support business analytics teams. |
| business analytics project example: The Modern Business Data Analyst Dominik Jung, 2024 This book illustrates and explains the key concepts of business data analytics from scratch, tackling the day-to-day challenges of a business data analyst. It provides you with all the professional tools you need to predict online shop sales, to conduct A/B tests on marketing campaigns, to generate automated reports with PowerPoint, to extract datasets from Wikipedia, and to create interactive analytics Web apps. Alongside these practical projects, this book provides hands-on coding exercises, case studies, the essential programming tools and the CRISP-DM framework which you'll need to kickstart your career in business data analytics. The different chapters prioritize practical understanding over mathematical theory, using realistic business data and challenges of the Junglivet Whisky Company to intuitively grasp key concepts and ideas. Designed for beginners and intermediates, this book guides you from business data analytics fundamentals to advanced techniques, covering a large number of different techniques and best-practices which you can immediately exploit in your daily work. The book does not assume that you have an academic degree or any experience with business data analytics or data science. All you need is an open mind, willingness to puzzle and think mathematically, and the willingness to write some R code. This book is your all-in-one resource to become proficient in business data analytics with R, equipped with practical skills for the real world. |
| business analytics project example: Statistical Modelling and Sports Business Analytics Vanessa Ratten, Ted Hayduk, 2020-05-11 This book introduces predictive analytics in sports and discusses the relationship between analytics and algorithms and statistics. It defines sports data to be used and explains why the unique nature of sports would make analytics useful. The book also explains why the proper use of predictive analytics includes knowing what they are incapable of doing as well as the role of predictive analytics in the bigger picture of sports entrepreneurship, innovation, and technology. The book looks at the mathematical foundations that enhance technical knowledge of predictive models and illustrates through practical, insightful cases that will help to empower readers to build and deploy their own analytic methodologies. This book targets readers who already have working knowledge of location, dispersion, and distribution statistics, bivariate relationships (scatter plots and correlation coefficients), and statistical significance testing and is a reliable, well-rounded reference for furthering their knowledge of predictive analytics in sports. |
| business analytics project example: Business Intelligence Strategy and Big Data Analytics Steve Williams, 2016-04-08 Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others. It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges. In recent years, terms like big data and big data analytics have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness. Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate. More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both. - Provides ideas for improving the business performance of one's company or business functions - Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies - Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans |
| business analytics project example: Getting Started with Business Analytics David Roi Hardoon, Galit Shmueli, 2013-03-26 Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts |
| business analytics project example: Information Technology for Management: Emerging Research and Applications Ewa Ziemba, 2019-02-27 This book constitutes extended selected papers from the 16th Conference on Advanced Information Technologies for Management, AITM 2018, and the 13th Conference on Information Systems Management, ISM 2018, held as part of the Federated Conference on Computer Science and Information Systems, FedCSIS, which took place in Poznan, Poland, in September 2018. The total of 9 full and 3 short papers presented in this volume were carefully reviewed and selected from a total of 43 submissions. The papers selected to be included in this book contribute to the understanding of relevant trends of current research on information technology for management in business and public organizations. They were organized in topical sections named: information technology and systems for knowledge management, and information technology and systems for business transformation. |
| business analytics project example: Mastering Microsoft Power BI Brett Powell, 2018-03-29 Design, create and manage robust Power BI solutions to gain meaningful business insights Key Features Master all the dashboarding and reporting features of Microsoft Power BI Combine data from multiple sources, create stunning visualizations and publish your reports across multiple platforms A comprehensive guide with real-world use cases and examples demonstrating how you can get the best out of Microsoft Power BI Book DescriptionThis book is intended for business intelligence professionals responsible for the design and development of Power BI content as well as managers, architects and administrators who oversee Power BI projects and deployments. The chapters flow from the planning of a Power BI project through the development and distribution of content to the administration of Power BI for an organization. BI developers will learn how to create sustainable and impactful Power BI datasets, reports, and dashboards. This includes connecting to data sources, shaping and enhancing source data, and developing an analytical data model. Additionally, top report and dashboard design practices are described using features such as Bookmarks and the Power KPI visual. BI managers will learn how Power BI’s tools work together such as with the On-premises data gateway and how content can be staged and securely distributed via Apps. Additionally, both the Power BI Report Server and Power BI Premium are reviewed. By the end of this book, you will be confident in creating effective charts, tables, reports or dashboards for any kind of data using the tools and techniques in Microsoft Power BI.What you will learn Build efficient data retrieval and transformation processes with the Power Query M Language Design scalable, user-friendly DirectQuery and Import Data Models Develop visually rich, immersive, and interactive reports and dashboards Maintain version control and stage deployments across development, test, and production environments Manage and monitor the Power BI Service and the On-premises data gateway Develop a fully on-premise solution with the Power BI Report Server Scale up a Power BI solution via Power BI Premium capacity and migration to Azure Analysis Services or SQL Server Analysis Services Who this book is for Business Intelligence professionals and existing Power BI users looking to master Power BI for all their data visualization and dashboarding needs will find this book to be useful. While understanding of the basic BI concepts is required, some exposure to Microsoft Power BI will be helpful. |
| business analytics project example: Principles and Applications of Business Intelligence Research Herschel, Richard T., 2012-12-31 This book provides the latest ideas and research on advancing the understanding and implementation of business intelligence within organizations--Provided by publisher. |
| business analytics project example: Business Analytics Mary Ellen Gordon, 2023-05-24 This new textbook focuses on how data and analytics can be used to help inform organisational decision-making across the business by complementing human judgement. Taking a highly practical approach, it covers major use cases for analytics across different business areas, including marketing analytics, HR analytics, operational analytics and financial analytics. This concise and readable book grounds discussion in the fundamentals of data, analytics and data visualisation, and in an understanding of the legal and ethical responsibilities that come with working with data. Key features include: • Analytics in Practice vignettes show how data and analytics have been applied in real organisations • Video interviews with industry professionals bring examples to life • A running case study and accompanying dataset allow you to apply what you have learnt Suitable for undergraduate and postgraduate students studying business analytics. Mary Ellen Gordon is Senior Professional Teaching Fellow/Senior Lecturer in the School of Information Systems at the Victoria University of Wellington, New Zealand. |
| business analytics project example: Profit Driven Business Analytics Wouter Verbeke, Bart Baesens, Cristian Bravo, 2017-10-09 Maximize profit and optimize decisions with advanced business analytics Profit-Driven Business Analytics provides actionable guidance on optimizing the use of data to add value and drive better business. Combining theoretical and technical insights into daily operations and long-term strategy, this book acts as a development manual for practitioners seeking to conceive, develop, and manage advanced analytical models. Detailed discussion delves into the wide range of analytical approaches and modeling techniques that can help maximize business payoff, and the author team draws upon their recent research to share deep insight about optimal strategy. Real-life case studies and examples illustrate these techniques at work, and provide clear guidance for implementation in your own organization. From step-by-step instruction on data handling, to analytical fine-tuning, to evaluating results, this guide provides invaluable guidance for practitioners seeking to reap the advantages of true business analytics. Despite widespread discussion surrounding the value of data in decision making, few businesses have adopted advanced analytic techniques in any meaningful way. This book shows you how to delve deeper into the data and discover what it can do for your business. Reinforce basic analytics to maximize profits Adopt the tools and techniques of successful integration Implement more advanced analytics with a value-centric approach Fine-tune analytical information to optimize business decisions Both data stored and streamed has been increasing at an exponential rate, and failing to use it to the fullest advantage equates to leaving money on the table. From bolstering current efforts to implementing a full-scale analytics initiative, the vast majority of businesses will see greater profit by applying advanced methods. Profit-Driven Business Analytics provides a practical guidebook and reference for adopting real business analytics techniques. |
| business analytics project example: Artificial Intelligence for Business Analytics Felix Weber, 2023-03-01 While methods of artificial intelligence (AI) were until a few years ago exclusively a topic of scientific discussions, today they are increasingly finding their way into products of everyday life. At the same time, the amount of data produced and available is growing due to increasing digitalization, the integration of digital measurement and control systems, and automatic exchange between devices (Internet of Things). In the future, the use of business intelligence (BI) and a look into the past will no longer be sufficient for most companies.Instead, business analytics, i.e., predictive and predictive analyses and automated decisions, will be needed to stay competitive in the future. The use of growing amounts of data is a significant challenge and one of the most important areas of data analysis is represented by artificial intelligence methods.This book provides a concise introduction to the essential aspects of using artificial intelligence methods for business analytics, presents machine learning and the most important algorithms in a comprehensible form using the business analytics technology framework, and shows application scenarios from various industries. In addition, it provides the Business Analytics Model for Artificial Intelligence, a reference procedure model for structuring BA and AI projects in the company. This book is a translation of the original German 1st edition Künstliche Intelligenz für Business Analytics by Felix Weber, published by Springer Fachmedien Wiesbaden GmbH, part of Springer Nature in 2020. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors. |
| business analytics project example: The Business Analysis Handbook Helen Winter, 2019-09-03 FINALIST: Business Book Awards 2020 - Specialist Book Category FINALIST: PMI UK National Project Awards 2019 - Project Management Literature Category The business analyst role can cover a wide range of responsibilities, including the elicitation and documenting of business requirements, upfront strategic work, design and implementation phases. Typical difficulties faced by analysts include stakeholders who disagree or don't know their requirements, handling estimates and project deadlines that conflict, and what to do if all the requirements are top priority. The Business Analysis Handbook offers practical solutions to these and other common problems which arise when uncovering requirements or conducting business analysis. Getting requirements right is difficult; this book offers guidance on delivering the right project results, avoiding extra cost and work, and increasing the benefits to the organization. The Business Analysis Handbook provides an understanding of the analyst role and the soft skills required, and outlines industry standard tools and techniques with guidelines on their use to suit the most appropriate situations. Covering numerous techniques such as Business Process Model and Notation (BPMN), use cases and user stories, this essential guide also includes standard templates to save time and ensure nothing important is missed. |
| business analytics project example: Python for Everybody Charles R. Severance, 2016-04-09 Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled Python for Informatics: Exploring Information.There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.pythonlearn.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course. |
| business analytics project example: Analytics for Business Success Hema Seshadri, Ph.D., 2023-04-15 Harness the power of analytics to revolutionize your business. Analytics is transforming the business landscape. All over the world, companies are using data to plan, invent, evolve, and gain critical insight into their customers, markets, and operations. The hype around analytics is well justified—but implementing an analytics initiative in practice is no easy task. Most analytics projects never make it to production. Even companies that manage to engineer a workable product prototype can stumble at the last hurdle and fail to realize the benefit of their analytics investment. In Analytics for Business Success: A Guide to Analytics Fitness,TM analytics expert Hema Seshadri diagnoses the challenges that can sabotage analytics product development and operationalization. With her accessible guide, learn how you can boost your company’s analytics fitness and make advanced analytics and AI work for you. |
| business analytics project example: Encyclopedia of Data Science and Machine Learning Wang, John, 2023-01-20 Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians. |
MSc Business Analytics dissertation projects - University of …
MSc Business Analytics – dissertation projects We are looking for projects for our Masters in Business Analytics. The Business Analytics MSc has been ranked 9th in the world in the latest …
Truly Intelligent Business - Example Data Strategy
Explain the components of a data strategy, specifically aspects which are relevant to . Set out the desired level of data capability required to meet strategic goals. Assess the current state of …
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Business Analytics now are leveraging the benefits of statistical methods and technologies to analyze their past data. This is used to uncover new insights to help them make a strategic …
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Project Public Summary MSc in Business Analytics, CEU 2020-2021 - 3rd phase is to make a sales ledger analysis based on the transformed data. The output of the analysis is the report …
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MIT Analytics Capstone Project Overview
This presentation will outline what is required to propose an analytics project for your organization to work with our MIT students and faculty. What is the MIT Master of Business Analytics …
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THE BUSINESS IMPACT OF ADVANCED ANALYTICS - Intel
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Associate Publisher: Amy Neidlinger Executive Editor: Jeanne Glasser Levine Operations Specialist: Jodi Kemper Cover Designer: Alan Clements Cover Image: Alan McHugh
Introduction to Business Data Analytics: Organizational View
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THE ANALYTICS EDGE: HOW TO TURN DATA INTO …
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the business ensures sound data quality and puts analytics into operation. The data management strategy spans the full analytics life cycle. Data is accessible and usable by multiple people – …
Building an Analytical Roadmap: A Real Life Exa…
To Meet Business Objectives: Translate business strategy into big data analytics strategy – answer: Which key …
MSc Business Analytics dissertation projects - Univ…
MSc Business Analytics – dissertation projects We are looking for projects for our Masters in Business Analytics. …
Truly Intelligent Business - Example Data Strategy
Explain the components of a data strategy, specifically aspects which are relevant to . Set out the desired level …
A MINI PROJECT REPORT ON - alameenedu.co.in
Business Analytics now are leveraging the benefits of statistical methods and technologies to analyze their past …
Master of Science in Business Analytics CAPST…
Project Public Summary MSc in Business Analytics, CEU 2020-2021 - 3rd phase is to make a sales ledger …
