Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Data Analytics Modeling Certificate PDF full book. Access full book title Data Analytics Modeling Certificate by AICPA. Download full books in PDF and EPUB format.
Author: AICPA Publisher: Wiley ISBN: 9781119696650 Category : Business & Economics Languages : en Pages : 0
Book Description
The Data Analytics Modeling Certificate (14.0 CPE Credits) will expand your ability to work with structured and unstructured data to drive a successful analytics practice. To start, you will learn to define clear business outcomes for your analytics practice to ensure your efforts align with your organization's strategic direction and create value. Next, you will learn data profiling and data cleansing techniques to maintain data quality throughout the data life cycle. You'll practice ETL (extract, transform, load) techniques and work with different data models and analytics tools. Finally, you will learn how to institute sophisticated tools for managing an ongoing enterprise data practice, including tools for data warehousing, managing the data life cycle, and working with structured and unstructured data. This certificate is Part 3 of the Data Analyst Certificates Bundle – a comprehensive five-part program that provides training and practical guidance on the topic of data analytics. Note: It is recommended that you complete the Application of Data Analysis Essentials Certificate, or ensure you have equivalent knowledge and skills, before starting this certificate course. Learning Labs* This is an interactive learning program that includes bonus hands-on learning labs that will expose you to the tools needed to implement an analytics practice in a practical way and equip you to deploy those tools as needed within your organization. You will practice using various technologies for preparing, analyzing and managing datasets in the real world. *Time spent on learning labs does not award CPE and completing learning labs is not a requirement for earning the certificate. WHO WILL BENEFIT Accounting and finance professionals, especially those interested in learning and applying data analysis techniques to help their organizations make informed, data-driven business decisions. KEY TOPICS Defining value and tying analytics to value-driven business cases Understanding the characteristics of data and how they can be leveraged to gather insights from information Identifying project constructs for data analytics Identifying different types of data with which analysts will be expected to interact Profiling data for accurate analysis initiatives Understanding tool capabilities for working with data Cleansing data with appropriate tools to increases analytics accuracy Managing data quality and integrity Extracting, transforming, and loading data Implementing a data warehouse Managing the data life cycle Creating and using different types of data models Tools for working with both structured and unstructured data LEARNING OBJECTIVES Identify opportunities, processes, and necessary data for solving analytical problems. Apply data profiling and data cleansing techniques to available data. Use data preparation and enrichment tools. Use ETL (extract, transform, load) tools. Compare data warehousing techniques. Use data warehousing and data management tools. Align the outcomes of your data analytics practice with your organization's strategic direction and create value. Digital Badge: Your Professional Distinction Set yourself apart as a future-ready financial professional. Upon completion, you will be awarded with a certificate in the form of a digital badge. Digital badges allow you to distinguish yourself in the marketplace and show your commitment to quality. The badge can be posted to your social media profiles and linked to your resume or email signature, providing maximum visibility to your achievement. Credit Info CPE CREDITS: Online: 14.0 (CPE credit info) NASBA FIELD OF STUDY: Information Technology LEVEL: Intermediate PREREQUISITES: Recommended: Complete the Application of Data Analysis Essentials Certificate or ensure you have equivalent knowledge and skills. ADVANCE PREPARATION: None DELIVERY METHOD: QAS Self-Study COURSE ACRONYM: DALP-S3 Online Access Instructions A personal pin code is enclosed in the physical packaging that may be activated online upon receipt. Once activated, you will gain immediate online access to the product for one full year. System Requirements AICPA’s online CPE courses will operate in a variety of configurations, but only the configuration described below is supported by AICPA technicians. A stable and continuous internet connection is required. In order to record your completion of the online learning courses, please ensure you are connected to the internet at all times while taking the course. It is your responsibility to validate that CPE certificate(s) are available within your account after successfully completing the course and/or exam. Supported Operating Systems: Macintosh OS X 10.10 to present Windows 7 to present Supported Browsers: Apple Safari Google Chrome Microsoft Internet Explorer Mozilla Firefox Required Browser Plug-ins: Adobe Flash Adobe Acrobat Reader Technical Support: Please contact [email protected].
Author: AICPA Publisher: Wiley ISBN: 9781119696650 Category : Business & Economics Languages : en Pages : 0
Book Description
The Data Analytics Modeling Certificate (14.0 CPE Credits) will expand your ability to work with structured and unstructured data to drive a successful analytics practice. To start, you will learn to define clear business outcomes for your analytics practice to ensure your efforts align with your organization's strategic direction and create value. Next, you will learn data profiling and data cleansing techniques to maintain data quality throughout the data life cycle. You'll practice ETL (extract, transform, load) techniques and work with different data models and analytics tools. Finally, you will learn how to institute sophisticated tools for managing an ongoing enterprise data practice, including tools for data warehousing, managing the data life cycle, and working with structured and unstructured data. This certificate is Part 3 of the Data Analyst Certificates Bundle – a comprehensive five-part program that provides training and practical guidance on the topic of data analytics. Note: It is recommended that you complete the Application of Data Analysis Essentials Certificate, or ensure you have equivalent knowledge and skills, before starting this certificate course. Learning Labs* This is an interactive learning program that includes bonus hands-on learning labs that will expose you to the tools needed to implement an analytics practice in a practical way and equip you to deploy those tools as needed within your organization. You will practice using various technologies for preparing, analyzing and managing datasets in the real world. *Time spent on learning labs does not award CPE and completing learning labs is not a requirement for earning the certificate. WHO WILL BENEFIT Accounting and finance professionals, especially those interested in learning and applying data analysis techniques to help their organizations make informed, data-driven business decisions. KEY TOPICS Defining value and tying analytics to value-driven business cases Understanding the characteristics of data and how they can be leveraged to gather insights from information Identifying project constructs for data analytics Identifying different types of data with which analysts will be expected to interact Profiling data for accurate analysis initiatives Understanding tool capabilities for working with data Cleansing data with appropriate tools to increases analytics accuracy Managing data quality and integrity Extracting, transforming, and loading data Implementing a data warehouse Managing the data life cycle Creating and using different types of data models Tools for working with both structured and unstructured data LEARNING OBJECTIVES Identify opportunities, processes, and necessary data for solving analytical problems. Apply data profiling and data cleansing techniques to available data. Use data preparation and enrichment tools. Use ETL (extract, transform, load) tools. Compare data warehousing techniques. Use data warehousing and data management tools. Align the outcomes of your data analytics practice with your organization's strategic direction and create value. Digital Badge: Your Professional Distinction Set yourself apart as a future-ready financial professional. Upon completion, you will be awarded with a certificate in the form of a digital badge. Digital badges allow you to distinguish yourself in the marketplace and show your commitment to quality. The badge can be posted to your social media profiles and linked to your resume or email signature, providing maximum visibility to your achievement. Credit Info CPE CREDITS: Online: 14.0 (CPE credit info) NASBA FIELD OF STUDY: Information Technology LEVEL: Intermediate PREREQUISITES: Recommended: Complete the Application of Data Analysis Essentials Certificate or ensure you have equivalent knowledge and skills. ADVANCE PREPARATION: None DELIVERY METHOD: QAS Self-Study COURSE ACRONYM: DALP-S3 Online Access Instructions A personal pin code is enclosed in the physical packaging that may be activated online upon receipt. Once activated, you will gain immediate online access to the product for one full year. System Requirements AICPA’s online CPE courses will operate in a variety of configurations, but only the configuration described below is supported by AICPA technicians. A stable and continuous internet connection is required. In order to record your completion of the online learning courses, please ensure you are connected to the internet at all times while taking the course. It is your responsibility to validate that CPE certificate(s) are available within your account after successfully completing the course and/or exam. Supported Operating Systems: Macintosh OS X 10.10 to present Windows 7 to present Supported Browsers: Apple Safari Google Chrome Microsoft Internet Explorer Mozilla Firefox Required Browser Plug-ins: Adobe Flash Adobe Acrobat Reader Technical Support: Please contact [email protected].
Author: AICPA Publisher: Wiley ISBN: 9781119696674 Category : Business & Economics Languages : en Pages : 0
Book Description
The Forecasting and Predictive Analytics Certificate (15.0 CPE Credits) will teach you fundamental techniques used for predictive analytics: regression, classification, clustering, optimization, and simulation. Beginning with basic models for revealing and establishing relationships, you will learn to apply increasingly sophisticated modeling techniques for practical data analysis, as well as commonly encountered problems so you can determine the fit and usefulness for prediction of your models, and apply them to typical business problems. This certificate is Part 4 of the Data Analyst Certificates Bundle – a comprehensive five-part program that provides training and practical guidance on the topic of data analytics. As you develop your understanding of applied predictive analytics, you'll learn how to perform basic forecasting using time-based data to predict future values from a model. You will also learn how to model and calculate scenarios based on distance and space. You will get practice with classification, including naive Bayesian classification; create basic decision trees; and use various techniques for clustering and linear optimization to solve common business problems; as well as learn techniques for assessing the effectiveness of your solutions. Note: It is recommended that you complete the Data Analytics Modeling Certificate, or ensure you have equivalent knowledge and skills, before starting this certificate course. Learning Labs* This is an interactive learning program that includes bonus hands-on learning labs that will expose you to the tools needed to implement an analytics practice in a practical way and equip you to deploy those tools as needed within your organization. You will practice using various technologies for preparing, analyzing and managing datasets in the real world. *Time spent on learning labs does not award CPE and completing learning labs is not a requirement for earning the certificate. WHO WILL BENEFIT Accounting and finance professionals, especially those interested in learning and applying data analysis techniques to help their businesses make informed, data-driven business decisions. KEY TOPICS Predictive analytics techniques Forecasting with data models Finding relationships in data Bivariate and multivariate linear regression KNN classification Clustering Decision trees Training models LEARNING OBJECTIVES Identify the different techniques of predictive analytics: regression, classification, clustering, optimization, and simulation. Calculate varying types of regressions using R and Excel. Apply classification and clustering algorithms. Apply business process optimization to problems by identifying goals and constraints. Analyze the various probabilities of outcomes by applying Monte Carlo simulation. Calculate performance of predictive analytic algorithms. Digital Badge: Your Professional Distinction Set yourself apart as a future-ready financial professional. Upon completion, you will be awarded with a certificate in the form of a digital badge. Digital badges allow you to distinguish yourself in the marketplace and show your commitment to quality. The badge can be posted to your social media profiles and linked to your resume or email signature, providing maximum visibility to your achievement. Credit Info CPE CREDITS: Online: 15.0 (CPE credit info) NASBA FIELD OF STUDY: Statistics LEVEL: Intermediate PREREQUISITES: Recommended: Complete the Data Analytics Modeling Certificate or ensure you have equivalent knowledge and skills. ADVANCE PREPARATION: None DELIVERY METHOD: QAS Self-Study COURSE ACRONYM: DALP-S4 Online Access Instructions A personal pin code is enclosed in the physical packaging that may be activated online upon receipt. Once activated, you will gain immediate online access to the product for one full year. System Requirements AICPA’s online CPE courses will operate in a variety of configurations, but only the configuration described below is supported by AICPA technicians. A stable and continuous internet connection is required. In order to record your completion of the online learning courses, please ensure you are connected to the internet at all times while taking the course. It is your responsibility to validate that CPE certificate(s) are available within your account after successfully completing the course and/or exam. Supported Operating Systems: Macintosh OS X 10.10 to present Windows 7 to present Supported Browsers: Apple Safari Google Chrome Microsoft Internet Explorer Mozilla Firefox Required Browser Plug-ins: Adobe Flash Adobe Acrobat Reader Technical Support: Please contact [email protected].
Author: AICPA Publisher: Wiley ISBN: 9781119696636 Category : Business & Economics Languages : en Pages : 0
Book Description
The Data Analysis Fundamentals Certificate (10.0 CPE Credits) provides you with the knowledge on the different job roles involved in the analytics practice and the most commonly encountered technologies in today's data ecosystem. This certificate is Part 1 of the Data Analyst Certificates Bundle - a comprehensive five-part program that provides training and practical guidance on the topic of data analytics. The Data Analysis Fundamentals Certificate begins with a foundational understanding of the need of transformational assets within an organization and explains the importance of intelligent data management and corresponding analytics practice. This certificate program aims to provide you with the knowledge on the different job roles involved in the analytics practice and the most commonly encountered technologies in today's data ecosystem. It will cover concepts behind the most common types of data you will need to be prepared to analyze, as well as help you explore the factors impacting data practice. This certificate program will also explain why intelligent data management and a corresponding analytics practice is critical for the success of both the organization and the professional. WHO WILL BENEFIT Accounting and finance professionals, especially those interested in learning and applying data analysis techniques to help their organizations' make informed, data-driven business decisions. KEY TOPICS The business impacts and disruptive potential of organizational data Basic concepts behind different types of data and how they're used The job roles and duties associated with data analytics The life cycle of organizational data and how to manage it A vocabulary for evaluating and communicating in data practice Exposure to and demonstrations of tools used for managing and analyzing data Common obstacles and hurdles to effectively leveraging data in an organization How to tie data to business requirements and build business cases LEARNING OBJECTIVES Determine how the digital transformation and disruption landscape create a competitive advantage across the enterprise. Identify the organizational ecosystem needed for becoming a data-driven organization. Analyze the life cycle of data and its implications for data-driven decision making. Compare common problems and risks associated with becoming a data-driven business. Differentiate between data analysis tools. Identify requirements for data-driven projects. Digital Badge: Your Professional Distinction Set yourself apart as a future-ready financial professional. Upon completion, you will be awarded with a certificate in the form of a digital badge. Digital badges allow you to distinguish yourself in the marketplace and show your commitment to quality. The badge can be posted to your social media profiles and linked to your resume or email signature, providing maximum visibility to your achievement. Credit Info CPE CREDITS: Online: 10.0 (CPE credit info) NASBA FIELD OF STUDY: Specialized Knowledge LEVEL: Basic PREREQUISITES: None ADVANCE PREPARATION: None DELIVERY METHOD: QAS Self-Study COURSE ACRONYM: DALP-S1 Online Access Instructions A personal pin code is enclosed in the physical packaging that may be activated online upon receipt. Once activated, you will gain immediate online access to the product for one full year. System Requirements AICPA’s online CPE courses will operate in a variety of configurations, but only the configuration described below is supported by AICPA technicians. A stable and continuous internet connection is required. In order to record your completion of the online learning courses, please ensure you are connected to the internet at all times while taking the course. It is your responsibility to validate that CPE certificate(s) are available within your account after successfully completing the course and/or exam. Supported Operating Systems: Macintosh OS X 10.10 to present Windows 7 to present Supported Browsers: Apple Safari Google Chrome Microsoft Internet Explorer Mozilla Firefox Required Browser Plug-ins: Adobe Flash Adobe Acrobat Reader Technical Support: Please contact [email protected].
Author: Wayne Winston Publisher: Microsoft Press ISBN: 1509306080 Category : Computers Languages : en Pages : 1488
Book Description
Master business modeling and analysis techniques with Microsoft Excel 2019 and Office 365 and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide helps you use Excel to ask the right questions and get accurate, actionable answers. New coverage ranges from Power Query/Get & Transform to Office 365 Geography and Stock data types. Practice with more than 800 problems, many based on actual challenges faced by working analysts. Solve real business problems with Excel—and build your competitive advantage: Quickly transition from Excel basics to sophisticated analytics Use PowerQuery or Get & Transform to connect, combine, and refine data sources Leverage Office 365’s new Geography and Stock data types and six new functions Illuminate insights from geographic and temporal data with 3D Maps Summarize data with pivot tables, descriptive statistics, histograms, and Pareto charts Use Excel trend curves, multiple regression, and exponential smoothing Delve into key financial, statistical, and time functions Master all of Excel’s great charts Quickly create forecasts from historical time-based data Use Solver to optimize product mix, logistics, work schedules, and investments—and even rate sports teams Run Monte Carlo simulations on stock prices and bidding models Learn about basic probability and Bayes’ Theorem Use the Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook Automate repetitive analytics tasks by using macros
Author: Alberto Ferrari Publisher: Microsoft Press ISBN: 1509302816 Category : Business & Economics Languages : en Pages : 438
Book Description
Renowned DAX experts Alberto Ferrari and Marco Russo teach you how to design data models for maximum efficiency and effectiveness. How can you use Excel and Power BI to gain real insights into your information? As you examine your data, how do you write a formula that provides the numbers you need? The answers to both of these questions lie with the data model. This book introduces the basic techniques for shaping data models in Excel and Power BI. It’s meant for readers who are new to data modeling as well as for experienced data modelers looking for tips from the experts. If you want to use Power BI or Excel to analyze data, the many real-world examples in this book will help you look at your reports in a different way–like experienced data modelers do. As you’ll soon see, with the right data model, the correct answer is always a simple one! By reading this book, you will: • Gain an understanding of the basics of data modeling, including tables, relationships, and keys • Familiarize yourself with star schemas, snowflakes, and common modeling techniques • Learn the importance of granularity • Discover how to use multiple fact tables, like sales and purchases, in a complex data model • Manage calendar-related calculations by using date tables • Track historical attributes, like previous addresses of customers or manager assignments • Use snapshots to compute quantity on hand • Work with multiple currencies in the most efficient way • Analyze events that have durations, including overlapping durations • Learn what data model you need to answer your specific business questions About This Book • For Excel and Power BI users who want to exploit the full power of their favorite tools • For BI professionals seeking new ideas for modeling data
Author: National Academies of Sciences, Engineering, and Medicine Publisher: National Academies Press ISBN: 0309475597 Category : Education Languages : en Pages : 139
Book Description
Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.
Author: Rafael A. Irizarry Publisher: CRC Press ISBN: 1498775861 Category : Mathematics Languages : en Pages : 461
Book Description
This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.
Author: Arshad Khan Publisher: Khan Consulting & Publishing LLC ISBN: 0966086376 Category : Computers Languages : en Pages : 176
Book Description
Self-Service Analytics Simplified: How to Plan and Implement will introduce you to self-service analytics (SSA), which aims to make business users less dependent on IT for their reporting and analytics needs. This book, which teaches how to plan and implement an SSA project, will appeal to a broad range of users including senior executives, business and IT managers, project managers, data analysts, business analysts, developers, casual users, as well as IT professionals. The topics covered in Self-Service Analytics Simplified: How to Plan and Implement include an introduction to self-service analytics, relationship with BI, benefits for different types of users, readiness assessment, planning, data-related topics including metadata and data pipelining, architecture, tools, requirements, implementation, data governance, security, training, data and user onboarding, and barriers to adoption, as well as challenges, best practices, lessons, and tips.
Author: Thomas W. Miller Publisher: FT Press ISBN: 013389214X Category : Computers Languages : en Pages : 448
Book Description
Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more
Author: Eduardo Chavez Publisher: Packt Publishing Ltd ISBN: 1801079692 Category : Computers Languages : en Pages : 284
Book Description
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.
Author: AICPA
Author: AICPA
Author: AICPA
Author: AICPA
Author: Wayne Winston
Author: Alberto Ferrari
Author: National Academies of Sciences, Engineering, and Medicine
Author: Rafael A. Irizarry
Author: Arshad Khan
Author: Thomas W. Miller
Author: Eduardo Chavez