|
|
Books > Computing & IT > Computer software packages > Spreadsheet software
Discover timesaving features, accessibility and internal control
approaches, data integrity improvements, and spreadsheet automation
techniques by exploring Excel shortcuts and nuances in Microsoft
365, Excel versions till 2021 Key Features Get hands-on experience
by carrying out techniques in detailed example workbooks Reclaim
portions of your day by immediately implementing data integrity and
automation features Incorporate spreadsheet disaster recovery
techniques into your daily work Book DescriptionDavid Ringstrom
coined the phrase "Either you work Excel, or it works you!" after
observing how many users carry out tasks inefficiently. In this
book, you'll learn how to get more done with less effort. This book
will enable you to create resilient spreadsheets that are easy for
others to use as well, while incorporating spreadsheet disaster
preparedness techniques. The time-saving techniques covered in the
book include creating custom shortcuts and icons to streamline
repetitive tasks, as well as automating them with features such as
Tables and Custom Views. You'll see how Conditional Formatting
enables you to apply colors, Cell icons, and other formatting
on-demand as your data changes. You'll be empowered to protect the
integrity of spreadsheets and increase usability by implementing
internal controls, and understand how to solve problems with
What-If Analysis features. In addition, you'll master new features
and functions such as XLOOKUP, Dynamic Array functions, LET and
LAMBDA, and Power Query, while learning how to leverage shortcuts
and nuances in Excel. By the end of this book, you'll have a
broader awareness of how to avoid pitfalls in Excel. You'll be
empowered to work more effectively in Excel, having gained a deeper
understanding of the frustrating oddities that can arise daily in
Excel. What you will learn Explore hidden and overlooked features
that will save your time Implement disaster prevention and recovery
techniques Improve spreadsheet accessibility for all users Bolster
data integrity and spreadsheet resilience Craft code-free custom
worksheet functions with LAMBDA Create code-free report automation
with Power Query Integrate spreadsheet automation techniques with
ease Who this book is forThis book is for intermediate to advanced
excel users working in diverse roles such as business users,
accountants, project managers and business analysts among others.
The more time that you spend in excel the more time this book will
save you. You will be able to maximize your productivity by
learning spreadsheet interactivity, accessibility and automation.
This clear step-by-step explanation and detailed example workbook
will help you to try out new techniques firsthand and leverage them
for your business's advantage in no time.
Explore a variety of Excel features, functions, and productivity
tips for various aspects of financial modeling Key Features Explore
Excel's financial functions and pivot tables with this updated
second edition Build an integrated financial model with Excel for
Microsoft 365 from scratch Perform financial analysis with the help
of real-world use cases Book DescriptionFinancial modeling is a
core skill required by anyone who wants to build a career in
finance. Hands-On Financial Modeling with Excel for Microsoft 365
explores financial modeling terminologies with the help of Excel.
Starting with the key concepts of Excel, such as formulas and
functions, this updated second edition will help you to learn all
about referencing frameworks and other advanced components for
building financial models. As you proceed, you'll explore the
advantages of Power Query, learn how to prepare a 3-statement
model, inspect your financial projects, build assumptions, and
analyze historical data to develop data-driven models and
functional growth drivers. Next, you'll learn how to deal with
iterations and provide graphical representations of ratios, before
covering best practices for effective model testing. Later, you'll
discover how to build a model to extract a statement of
comprehensive income and financial position, and understand capital
budgeting with the help of end-to-end case studies. By the end of
this financial modeling Excel book, you'll have examined data from
various use cases and have developed the skills you need to build
financial models to extract the information required to make
informed business decisions. What you will learn Identify the
growth drivers derived from processing historical data in Excel Use
discounted cash flow (DCF) for efficient investment analysis
Prepare detailed asset and debt schedule models in Excel Calculate
profitability ratios using various profit parameters Obtain and
transform data using Power Query Dive into capital budgeting
techniques Apply a Monte Carlo simulation to derive key assumptions
for your financial model Build a financial model by projecting
balance sheets and profit and loss Who this book is forThis book is
for data professionals, analysts, traders, business owners, and
students who want to develop and implement in-demand financial
modeling skills in their finance, analysis, trading, and valuation
work. Even if you don't have any experience in data and statistics,
this book will help you get started with building financial models.
Working knowledge of Excel is a prerequisite.
The trusted series of workbooks by Philip H. Pollock III and Barry
C. Edwards continues with A Microsoft Excel (R)Companion to
Political Analysis. In this new guide, students dive headfirst into
actual political data working with the ubiquitous Excel software.
Students learn by doing with new guided examples, annotated
screenshots, step-by-step instructions, and exercises that reflect
current scholarly debates in varied subfields of political science,
including American politics, comparative politics, law and courts,
and international relations. Chapters cover all major topics in
political data analysis, from descriptive statistics through
logistic regression, all with worked examples and exercises in
Excel. No matter their professional goals, students can gain a leg
up for their future careers by developing a working knowledge of
statistics using Excel. By encouraging students to build on their
existing familiarity with the Excel program, instructors can
flatten the statistics learning curve and take some of the
intimidation out of the learning process. Gain lost time usually
spent troubleshooting software to provide students with a smooth
transition into political analysis.
You’re beyond the basics—so dive in and really put your spreadsheet skills to work! This supremely organized reference is packed with hundreds of timesaving solutions, troubleshooting tips, and workarounds. It’s all muscle and no fluff. Learn how the experts tackle Excel—and challenge yourself to new levels of mastery. Includes companion eBook and sample files.
Topics include:
•Customizing the Excel workspace
•Best practices for designing and managing worksheets
•Creating formulas and functions
•Performing statistical, what-if, and other data analysis
•Core to advanced charting techniques
•Using graphics and sparklines
•Managing databases and tables
•Automating Excel with macros and custom functions
•Collaborating in Excel online, in the cloud, and more
•Extending Excel
Designed as a project and case-oriented approach to learning Excel,
the emphasis of this book is on learning by doing. The book
presents a series of progressively reinforcing problem sets, which
allow the exploration of real-life business problems. First, the
background, theory, formulas, and calculations are discussed,
followed by the design of Excel spreadsheets, which support the
creation of effective spreadsheets for these applications. Finally,
the proper solution and other related aspects are discussed,
forming a cohesive set of practical application problems. Some of
the topics explored include amortization tables, weighted averages,
cash flows, payroll calculations, break even analysis, and
spreadsheet databases. Excel techniques include formulas and
functions, cell addressing, conditional and lookup functions,
graphs, sorting, and filtering. FEATURES Provides 30 projects,
several How-to Guides, and Application Types to learn Excel skills
using problems, applications, and case studies featuring practical
business problems Explores formulas and functions, financial
functions, cell addressing, conditional functions, lookup
functions, graphs, sorting, and filtering, amortization tables,
future values of an investment, weighted averages, cash flows,
payroll calculations, break even analysis, economic order quantity,
spreadsheet databases, and more Companion files with four Excel
video tutorials and images from the text. Instructor resources
available.
The prediction of the valuation of the "quality" of firm accounting
disclosure is an emerging economic problem that has not been
adequately analyzed in the relevant economic literature. While
there are a plethora of machine learning methods and algorithms
that have been implemented in recent years in the field of
economics that aim at creating predictive models for detecting
business failure, only a small amount of literature is provided
towards the prediction of the "actual" financial performance of the
business activity. Machine Learning Applications for Accounting
Disclosure and Fraud Detection is a crucial reference work that
uses machine learning techniques in accounting disclosure and
identifies methodological aspects revealing the deployment of
fraudulent behavior and fraud detection in the corporate
environment. The book applies machine learning models to identify
"quality" characteristics in corporate accounting disclosure,
proposing specific tools for detecting core business fraud
characteristics. Covering topics that include data mining; fraud
governance, detection, and prevention; and internal auditing, this
book is essential for accountants, auditors, managers, fraud
detection experts, forensic accountants, financial accountants, IT
specialists, corporate finance experts, business analysts,
academicians, researchers, and students.
|
|