How is Financial Data used?
Zippia reviewed thousands of resumes to understand how financial data is used in different jobs. Explore the list of common job responsibilities related to financial data below:
- Comply and report financial data and statistical, demographic reports in accordance with government and accrediting agency guidelines.
- Analyzed and reconciled program execution to various financial databases; recommended and implemented strategies to improve performance.
- Validated all financial entries and performed Account Allocations after review to correct inaccurate financial data.
- Reviewed/analyzed financial data, exercised judgment and discretion in conformance with established guidelines.
- Created and maintained financial databases, spreadsheets and generated financial reports as required.
- Report all financial data to company executives to support strategic decision-making.
Are Financial Data skills in demand?
Yes, financial data skills are in demand today. Currently, 18,773 job openings list financial data skills as a requirement. The job descriptions that most frequently include financial data skills are finance officer, budget accountant, and finance assistance advisor.
How hard is it to learn Financial Data?
Based on the average complexity level of the jobs that use financial data the most: finance officer, budget accountant, and finance assistance advisor. The complexity level of these jobs is challenging.
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What jobs can you get with Financial Data skills?
You can get a job as a finance officer, budget accountant, and finance assistance advisor with financial data skills. After analyzing resumes and job postings, we identified these as the most common job titles for candidates with financial data skills.
Finance Officer
Job description:
A finance officer is responsible for monitoring the financial department and the transactions of an organization. Finance officers analyze financial reports, update account statements, and oversee the budget allocation for business operations. They also resolve billing discrepancies and banking issues, assist in cash statement release, and manage payroll disputes. A finance officer conducts data and statistical analysis to evaluate the company's financial performance and stability and identifying opportunities to increase revenues and grow more profits.
- Real Estate
- Financial Data
- Origination
- Financial Procedures
- Financial Management
- Financial Analysis
Budget Accountant
- Financial Data
- Fixed Assets
- Journal Entries
- Reconciliations
- Budget Preparation
- Balance Sheet
Finance Assistance Advisor
- Customer Service
- Financial Assistance
- Financial Data
- Financial Aid Eligibility
- Financial Aid
- Client Service
General Accountant
Job description:
A general accountant is responsible for evaluating account statements, conducting data analysis with financial transactions, and generating reports on revenues, expenses, and sales forecasting. These accountants manage discrepancies on the company and clients' profiles, including bank reconciliations and processing of account receivables and payables. They also handle the release of invoices and petty cash, analyzing balance sheets, and updating accurate financial information on the database. A general accountant must have excellent analytical skills, as well as extensive knowledge of the accounting principles and disciplines.
- Financial Data
- Reconciliations
- Cash Handling
- Vendor Invoices
- General Ledger Accounts
- Account Reconciliations
Voucher Examiner
- Travel Vouchers
- Customer Service
- Financial Data
- Vendor Payments
- Veterans
- Process Claims
Loan Clerk
- Customer Service
- Loan Payments
- Financial Data
- Mortgage Loans
- Credit Reports
- General Ledger Accounts
Budget/Finance Analyst
Job description:
Budget/finance analysts are financial professionals who are responsible for allocating the financial resources of private companies, nonprofit organizations, and government agencies. These analysts are required to perform financial analysis and reporting to monitor the finances that are associated with business operations. They must monitor the execution of budgets within assigned offices to ensure that the organization's goals and objectives are achieved. Budget/finance analysts must also compile and evaluate accounting records to identify the necessary financial resources for the implementation of programs.
- Financial Data
- Financial Analysis
- Financial Management
- DOD
- Financial Performance
- Financial Resources
Business Office Coordinator
Job description:
A business office coordinator is responsible for performing administrative and clerical duties to support business operations and requirements. Business office coordinators manage appointments and travel arrangements, respond to e-mail and phone queries, greet visitors and direct them to the appropriate department or personnel, and submit reports. They also monitor the company's database, update account information, and restore files needed for business operations. A business office coordinator must have excellent communication and organizational skills, especially in performing duties under minimal supervision and strict deadlines.
- Data Entry
- Patients
- Financial Data
- Payroll Processing
- Human Resources
- Kronos
Forensic Accountant
Job description:
Working close together with law enforcement agencies, a forensic accountant specializes in investigating potential fraud and financial crimes. Their responsibilities typically include performing extensive research and analysis, gathering and analyzing various forms of financial data and storage, reviewing and validating documents, verifying information, and conducting internal and external financial audits. Most of the time, a forensic accountant presents research findings to lawyers and judges as evidence, which will require them to participate and testify in court proceedings.
- CPA
- Litigation
- Forensic Accounting
- Financial Data
- Fraud Investigations
- CFE
Budget Technician
- Financial Management
- Financial Data
- Financial Reports
- Status Updates
- Budget Reports
- Budget Analysis
Fiscal Analyst
Job description:
A fiscal analyst specializes in providing analytical services to help companies monitor and develop budgets and financial activities. Their responsibilities include gathering and analyzing financial data, conducting market research and analysis, arranging spreadsheets, updating databases, and producing regular budget reports and forecasts. To carry out their duties, they typically use special software and programs, coordinate with various departments, and have knowledge in court collections. Moreover, a fiscal analyst may assist staff, all while implementing the company's policies and regulations.
- Payroll
- Financial Data
- Management System
- GAAP
- Financial Statements
- Reconciliations
Accounts Receivable Clerk
Job description:
An Accounts Receivable Clerk specializes in processing payment records and bill statements of a company or organization. Among the duties include calculating total revenues and unpaid invoices, maintaining financial records and keeping a detailed and organized database, and verifying financial transactions and payment delinquencies. Furthermore, an Accounts Receivable Clerk must resolve and examine deductions, prepare invoices and necessary documentation, and review customer payment plans and history records and coordinate with the collections department should there be any issues.
- Customer Service
- Data Entry
- Collection Calls
- Financial Data
- Credit Card Payments
- Process Payments
Senior Finance Specialist
Job description:
A finance specialist sells products and services at a financial institution. Finance specialists meet with customers to have a better understanding of their respective needs. The specialists offer insight into the trends in the financial market. They provide a suggestion on optimization strategies. It is expected of them to share their insight into the potential models in the business. The necessary skills for this job include strong communication, management experience, financial management, and analytical thinking.
- Financial Statements
- Financial Data
- Financial Analysis
- Calculation
- Strong Analytical
- Financial Management
Finance Management Specialist
Job description:
A finance management specialist is in charge of overseeing and managing a company's financial activities, ensuring accuracy and smooth workflow. They typically coordinate with different departments to gather accurate data, manage budgets and schedules, prepare cost and budget reports, and assess existing procedures to identify areas needing improvement. They must also maintain extensive records, produce sales forecasts, and participate in creating financial goals and objectives. Furthermore, as a finance management specialist, it is essential to develop strategies to optimize financial operations, all while implementing the company's policies and regulations.
- Financial Resources
- Financial Reports
- Financial Data
- Budget Formulation
- Budget Execution
- Financial Management Systems
Senior Budget Analyst
Job description:
A senior budget analyst analyzes the finances of their company. They monitor their company's financial data to gain new insights to make a profit. They create budgets for departments, increase the efficiency of company systems, and prepare reports and financial statements.
- Financial Management
- PowerPoint
- Financial Analysis
- Budget Analysis
- Financial Data
- Financial Systems
Data Processor
Job description:
A data processor is responsible for encoding various information to the organization's database, originating from either manual or electronic communications. Data processors must be highly detail-oriented, especially on analyzing the completeness of data before uploading it to the system. In some cases, a data processor performs in-depth research to verify the authenticity of the information. A data processor should have excellent typing skills and knowledge with office software tools to create proper formatting and ensure accuracy for easy comprehension.
- Computer Database
- Data Processing
- Financial Data
- Data Entry
- Computer System
- QC
Accounting Systems Analyst
Job description:
The advanced systems engineer works to develop and upgrade systems used in a company or provided for customers and clients. System engineers regularly monitor all applications, software, and productivity systems used in the company and evaluate them. The advanced systems engineer's goal is to improve the programs used in the company continually. Working alongside the IT department, the engineer monitors all feedback and promptly provides suggestions, recommendations and, if necessary, orders upgrades in problematic areas in the system.
- Hyperion
- Process Improvement
- Financial Systems
- Financial Reports
- Financial Data
- System Issues
Director Of Accounting & Finance
Job description:
A director of accounting and finance is in charge of overseeing all financial activities and decisions in a company and supervising its workforce. Their responsibilities revolve around spearheading the development of financial plans and strategies, coordinating with analysts and consultants, gathering and analyzing financial data, and reporting all sales progress to executives through documents and presentations. They must also set goals and objectives, allocate budgets to different departments, prepare comprehensive sales forecasts, and lead employees while implementing the company's policies and regulations.
- CPA
- GAAP
- Internal Controls
- Financial Data
- Balance Sheet
- Financial Reports
How much can you earn with Financial Data skills?
You can earn up to $68,822 a year with financial data skills if you become a finance officer, the highest-paying job that requires financial data skills. Budget accountants can earn the second-highest salary among jobs that use Python, $59,192 a year.
| Job title | Average salary | Hourly rate |
|---|---|---|
| Finance Officer | $68,822 | $33 |
| Budget Accountant | $59,192 | $28 |
| Finance Assistance Advisor | $79,349 | $38 |
| General Accountant | $55,043 | $26 |
| Voucher Examiner | $45,925 | $22 |
Companies using Financial Data in 2025
The top companies that look for employees with financial data skills are Robert Half, U.S. Department of the Treasury, and Cherry Bekaert. In the millions of job postings we reviewed, these companies mention financial data skills most frequently.
| Rank | Company | % of all skills | Job openings |
|---|---|---|---|
| 1 | Robert Half | 44% | 8,367 |
| 2 | U.S. Department of the Treasury | 11% | 8 |
| 3 | Cherry Bekaert | 8% | 1,297 |
| 4 | Sunrun | 4% | 923 |
| 5 | Ryder System | 4% | 6,349 |
Departments using Financial Data
| Department | Average salary |
|---|---|
| Accounting | $66,082 |
5 courses for Financial Data skills
1. Practical Financial Data Analysis With Python Data Science
THIS IS YOUR COMPLETE GUIDE TO FINANCIAL DATA ANALYSIS IN PYTHON! This course is your complete guide to analyzing real-world financial data using Python. All the main aspects of analyzing financial data- statistics, data visualization, time series analysis and machine learning will be covered in depth. If you take this course, you can do away with taking other courses or buying books on Python-based data analysis. In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal. By becoming proficient in analysing financial data in Python, you can give your company a competitive edge and boost your career to the next level. LEARN FROM AN EXPERT DATA SCIENTIST WITH +5 YEARS OF EXPERIENCE: Hey, my name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment), graduate. I recently finished a PhD at Cambridge University. I have +5 years of experience in analyzing real-life data from different sources using data science-related techniques and I have produced many publications for international peer-reviewed journals. Over the course of my research, I realised almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic. So, unlike other instructors, I dig deep into the data science features of R and gives you a one-of-a-kind grounding in data science-related topics! You will go all the way from carrying out data reading & cleaning to finally implementing powerful statistical and machine learning algorithms for analyzing financial data. Among other things: You will be introduced to powerful Python-based packages for financial data analysis. You will be introduced to both the commonly used techniques, visualization methods and machine/deep learning techniques that can be implemented for financial data. & you will learn to apply these frameworks to real-life data including temporal stocks and financial data. NO PRIOR PYTHON OR STATISTICS/MACHINE LEARNING KNOWLEDGE IS REQUIRED! You'll start by absorbing the most valuable Python Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in Python. My course will help you implement the methods using REAL DATA obtained from different sources. Many courses use made-up data that does not empower students to implement Python-based data science in real-life. After taking this course, you'll easily use the common time-series and financial analysis packages in Python. You'll even understand the underlying concepts to understand what algorithms and methods are best suited for your data. We will work with real data and you will have access to all the code and data used in the course. JOIN MY COURSE NOW!...
2. Data-Driven Investing with Python Financial Data Science
Become a Data Driven Investor. Take the guesswork out of your investing forever. Leverage the power of Financial Data Science, Financial Analysis, Python, and Quantitative Finance to make robust investment decisions (and generate Alpha). Discover how to use rigorous statistical techniques on Python to guide your investment decisions (even if you don't know statistics or your math is weak). Say hello to the most comprehensive Data Driven Investing course on the internet. Featuring:# =============================# 2 PARTS, 8 SECTIONS TO MASTERY # =============================(plus, all future updates included!)Structured learning path, Designed for Distinction™ including:12.5 hours of engaging, practical, on-demand HD video lessonsReal-world applications throughout the course200+ quiz questions with impeccably detailed solutions to help you stay on track and retain your knowledgeAssignments that take you outside your comfort zone and empower you to apply everything you learnA Practice Test to hone in and gain confidence in the core evergreen fundamentalsPython code (built from scratch) to help you build a replicable system for investingMathematical proofs for the mathematically curiousAn instructor who's insanely passionate about Finance, Investing, Python, and Financial Data SciencePART I: INVESTMENT ANALYSIS FUNDAMENTALSStart by gaining a solid command of the core fundamentals that drive the entire investment analysis / financial analysis process. Explore Investment Security Relationships & Estimate ReturnsDiscover powerful relationships between Price, Risk, and ReturnsIntuitively explore the baseline fundamental law of Financial Analysis - The Law of One Price. Learn what Shorting a stock actually means and how it worksLearn how to calculate stock returns and portfolio returns from scratchWork with real-world data on Python and know exactly what your code does and why it worksEstimate Expected Returns of Financial SecuritiesExplore what expected returns are and how to estimate them starting with the simple meanDive deeper with state contingent expected returns that synthesize your opinions with the dataLearn how to calculate expected returns using Asset Pricing Models like the CAPM (Capital Asset Pricing Model)Discover Multi-Factor Asset Pricing Models including the Fama French 3 Factor Model, Carhart 4 (Momentum), and moreMaster the theoretical foundation and apply what you learn using real-world data on Python your own! Quantify Stock Risk and Estimate Portfolio RiskExamine the risk of a stock and learn how to quantify total risk from scratchApply your knowledge to any stock you want to explore and work withDiscover the 3 factors that influence portfolio risk (1 of which is more important than the other two combined)Explore how to estimate portfolio risk for 'simple' 2-asset portfoliosLearn how to measure portfolio risk of multiple stocks (including working with real-world data on Python!)Check your MasterySo. Much. Knowledge, Skills, and Experience. Are you up for the challenge? - Take the Test Towards MasteryIdentify areas you need to improve on and get better at in the context of Financial Analysis / Investment AnalysisSet yourself up for success in Financial Data Science / Quantitative Finance by ensuring you have a rigorous foundation in placePART II: DATA DRIVEN INVESTING FINANCIAL DATA SCIENCE / QUANTITATIVE FINANCESkyrocket your financial analysis / investment analysis skills to a whole new level by learning how to leverage Financial Data Science, Quantitative Finance and Python for your investing. Discover Data Driven Investing and Hypothesis DesignDiscover what data driven investing actually is, and what it entailsExplore the 5 Step Data Driven Investing process that's designed to help you take the guesswork out of your investment decision makingLearn how to develop investment ideas (including how/where to source them from)Explore the intricacies of research questions in the context of Financial Data Science / Data Driven InvestingTransform your investment ideas into testable hypotheses (even if you don't know what a testable hypothesis is)Source, Clean, and Explore Real-World DataExplore how and where you can source data to test and validate your own hypothesesMaster the backbone of financial data science - data cleaning - and avoid the GIGO trap (even if you don't know what GIGO is)Work with large datasets (arguably Big Data) with over 1 million observations using Python! Discover quick hacks to easily clean data on Python (and become aware of issues that are easy to miss)Learn while exploring meaningful questions on the impact of ESG in financial marketsConduct Exploratory Data AnalysisDiscover how to conduct one of the most common financial data science techniques - exploratory data analysis using PythonEvaluate intriguing relationships between returns and ESG (or another factor of your choice)Learn how to statistically test and validate hypotheses using 'simple' t-testsNever compromise on the mathematical integrity of the concepts - understand why equations work the way they doExplore how to update beliefs and avoid losing money by leveraging the power of financial data science, quantitative finance, and PythonDesign and Construct Investment PortfoliosExplore exactly what it takes to design and construct investment portfolios that are based on individual investment ideasLearn how to sort firms into buckets to help identify monotonic relationships (a vital analysis technique of financial data science)Leverage the power of Pandas in Python to conduct investment analysis like the Pros (Hedge Funds, Financial Data Scientists, Applied Researchers)Strengthen your financial data science skills by becoming aware of Python's surprising default settings (and what you can do to overcome them)Plot charts that drive meaningful insights for Quantitative Finance, including exploring portfolio performance over time using Matplotlib and SeabornStatistically Test and Validate HypothesesSay goodbye to guesswork, hope, and luck when it comes to making investment decisionsRigorously test and statistically validate your investment ideas by applying robust financial data science techniques on PythonAdd the use of sophisticated tools including simple t-stats and more 'complex' regressions to your suite of financial data science analyticsExplore what it really takes to search for and generate Alpha (to beat the market)Learn and apply tried and tested financial data science and quantitative finance techniques used by hedge funds, financial data scientists, and researchers on PythonDESIGNED FOR DISTINCTION™We've used the same tried and tested, proven to work teaching techniques that have helped our clients ace their professional exams (e. g., ACA, ACCA, CFA®, CIMA), get hired by the most renowned investment banks in the world, manage their own portfolios, take control of their finances, get past their fear of math and equations, and so much more. You're in good hands. Here's how we'll help you master incredibly powerful Financial Data Science & Financial Analysis techniques to become a robust data driven investor who leverages the power of Python... A Solid FoundationYou'll gain a solid foundation of the core fundamentals that drive the entire financial analysis / investment analysis process. These fundamentals are the essence of financial analysis done right. And they'll hold you in mighty good stead both when you start applying financial data science techniques in Part II of this course, but also long after you've completed this course. Top skills in quantitative finance - for the rest of your life. Practical WalkthroughsForget about watching videos where all the Python code is pre-written. We'll start from blank Python scripts on Jupyter Notebooks (like the real world). And we'll build all the Python code from scratch, one line at a time. That way you'll literally see how we conduct rigorous financial analysis / financial data science using data-driven investing as the core basis, one step at a time. Hundreds of Quiz Questions, Dozen Assignments, and Much MoreApply what you learn immediately with 200+ quiz questions, all with impeccably detailed solutions. Plus, over a dozen assignments that take you outside your comfort zone. There's also a Practice Test to help you truly hone your knowledge and skills. And boatloads of practical, hands-on walkthroughs where we apply financial data science / quantitative finance techniques in data driven investing environments on Python. Proofs & ResourcesMathematical proofs for the mathematically curious. And also because, what's a quantitative finance course without proofs?! Step-by-step mathematical proofs, workable and reusable Python code (in. ipynb Jupyter notebook and. py versions), variable cheat sheets - all included. Seriously. This is the only course you need to genuinely master Data Driven Investing, and apply Financial Data Science & Quantitative Finance techniques on Python without compromising on the theoretical integrity of concepts...
3. Data-Driven Investing with Excel ® Financial Data Science
Become a Data Driven Investor. Take the guesswork out of your investing forever. Leverage the power of Financial Data Science, Financial Analysis, and Quantitative Finance to make robust investment decisions (and generate Alpha). Discover how to use rigorous statistical techniques to guide your investment decisions (even if you don't know statistics or your math is weak). Say hello to the most comprehensive Data Driven Investing course on the internet. Featuring:# =============================# 2 PARTS, 8 SECTIONS TO MASTERY # =============================(plus, all future updates included!)Structured learning path, Designed for Distinction™ including:13 hours of engaging, practical, on-demand HD video lessonsReal-world applications throughout the course200+ quiz questions with impeccably detailed solutions to help you stay on track and retain your knowledgeAssignments that take you outside your comfort zone and empower you to apply everything you learnA Practice Test to hone in and gain confidence in the core evergreen fundamentalsExcel® spreadsheets/templates (built from scratch) to help you build a replicable system for investingMathematical proofs for the mathematically curiousAn instructor who's insanely passionate about Finance, Investing, and Financial Data SciencePART I: INVESTMENT ANALYSIS FUNDAMENTALSStart by gaining a solid command of the core fundamentals that drive the entire investment analysis / financial analysis process. Explore Investment Security Relationships & Estimate ReturnsDiscover powerful relationships between Price, Risk, and ReturnsIntuitively explore the baseline fundamental law of Financial Analysis - The Law of One Price. Learn what Shorting a stock actually means and how it worksLearn how to calculate stock returns and portfolio returns from scratchDownload and work with real-world data on Excel® for any stock(s) you want, anywhere in the worldEstimate Expected Returns of Financial SecuritiesExplore what expected returns are and how to estimate them starting with the simple meanDive deeper with state contingent expected returns that synthesise your opinions with the dataLearn how to calculate expected returns using Asset Pricing Models like the CAPM (Capital Asset Pricing Model)Discover Multi Factor Asset Pricing Models including the Fama French 3 Factor Model, Carhart 4 (Momentum), and more)Master the theoretical foundation and apply what you learn using real-world data on your own! Quantify Stock Risk and Estimate Portfolio RiskExamine the risk of a stock and learn how to quantify total risk from scratchApply your knowledge to any stock you want to explore and work withDiscover the 3 factors that influence portfolio risk (1 of which is more important than the other two combined)Explore how to estimate portfolio risk for 'simple' 2-asset portfoliosLearn how to measure portfolio risk of multiple stocks (including working with real-world data!)Check your MasterySo. Much. Knowledge, Skills, and Experience. Are you up for the challenge? - Take the Test Towards MasteryIdentify areas you need to improve on and get better at in the context of Financial Analysis / Investment AnalysisSet yourself up for success in Financial Data Science / Quantitative Finance by ensuring you have a rigorous foundation in placePART II: DATA DRIVEN INVESTING FINANCIAL DATA SCIENCE / QUANTITATIVE FINANCESkyrocket your financial analysis / investment analysis skills to a whole new level by learning how to leverage Financial Data Science and Quantitative Finance for your investing. Discover Data Driven Investing and Hypothesis DesignDiscover what data driven investing actually is, and what it entailsExplore the 5 Step Data Driven Investing process that's designed to help you take the guesswork out of your investment decision makingLearn how to develop investment ideas (including how/where to source them from)Explore the intricacies of research questions in the context of Financial Data Science / Data Driven InvestingTransform your investment ideas into testable hypotheses (even if you don't know what a testable hypothesis is)Collect, Clean, and Explore Real-World DataExplore how and where you can source data to test and validate your own hypothesesMaster the backbone of financial data science - data cleaning - and avoid the GIGO trap (even if you don't know what GIGO is)Work with large datasets (arguably Big Data) with over 1 million observations using Excel®! Discover quick hacks to easily extract large amounts of data semi-automatically on Google SheetsLearn while exploring meaningful questions on the impact of ESG in financial marketsConduct Exploratory Data AnalysisDiscover how to conduct one of the most common financial data science techniques - exploratory data analysis using Excel®! Evaluate intriguing relationships between returns and ESG (or another factor of your choice)Learn how to statistically test and validate hypotheses using 'simple' t-testsNever compromise on the mathematical integrity of the concepts - understand why equations work the way they doExplore how to update beliefs and avoid losing money by leveraging the power of financial data science and quantitative financeDesign and Construct Investment PortfoliosExplore exactly what it takes to design and construct investment portfolios that are based on individual investment ideasLearn how to sort firms into buckets to help identify monotonic relationships (a vital analysis technique of financial data science)Discover intricate hacks to speed up your workflow when working with large datasets on ExcelStrengthen your financial data science skills by becoming aware of Excel®'s bugs (and what you can do to overcome them)Plot charts that drive meaningful insights for Quantitative Finance, including exploring portfolio performance over timeStatistically Test and Validate HypothesesSay goodbye to guesswork, hope, and luck when it comes to making investment decisionsRigorously test and statistically validate your investment ideas by applying robust financial data science techniquesAdd the use of sophisticated tools including simple t-stats and more 'complex' regressions to your suite of financial data science analyticsExplore what it really takes to search for and generate Alpha (to beat the market)Learn and apply tried and tested financial data science and quantitative finance techniques used by hedge funds, financial data scientists, and researchersDESIGNED FOR DISTINCTION™We've used the same tried and tested, proven to work teaching techniques that have helped our clients ace their professional exams (e. g., ACA, ACCA, CFA®, CIMA), get hired by the most renowned investment banks in the world, manage their own portfolios, take control of their finances, get past their fear of math and equations, and so much more. You're in good hands. Here's how we'll help you master incredibly powerful Financial Data Science & Financial Analysis techniques to become a robust data driven investor... A Solid FoundationYou'll gain a solid foundation of the core fundamentals that drive the entire financial analysis / investment analysis process. These fundamentals are the essence of financial analysis done right. And they'll hold you in mighty good stead both when you start applying financial data science techniques in Part II of this course, but also long after you've completed this course. Top skills in quantitative finance - for the rest of your life. Practical WalkthroughsForget about watching videos where all the Excel® templates are pre-built. We'll start from blank Excel® spreadsheets (like the real world). And we'll build everything from scratch, one cell at a time. That way you'll literally see how we conduct rigorous financial analysis / financial data science using data-driven investing as the core basis, one step at a time. Hundreds of Quiz Questions, Dozen Assignments, and Much MoreApply what you learn immediately with 200+ quiz questions, all with impeccably detailed solutions. Plus, over a dozen assignments that take you outside your comfort zone. There's also a Practice Test to help you truly hone your knowledge and skills. And boatloads of practical, hands-on walkthroughs where we apply financial data science / quantitative finance techniques in data driven investing environments. Proofs & ResourcesMathematical proofs for the mathematically curious. And also because, what's a quantitative finance course without proofs?! Step-by-step mathematical proofs, workable and reusable Excel® spreadsheets, variable cheat sheets - all included. Seriously. This is the only course you need to genuinely master Data Driven Investing, and apply Financial Data Science & Quantitative Finance techniques without compromising on the theoretical integrity of concepts...
4. Building Financial Dashboard in Google Data Studio
Learn from a Financial business intelligence analyst for a Group of more than 10 companies. Create Powerful Interactive Financial Dashboards from Google Sheets Data from scratch. No VBA or SQL coding require, just drag and drop, copy and paste. Analyze Google Sheets in minutes using powerful visualizations. Learn powerful visualizations such as Time Series Charts, Scorecards, Pie Charts, Stacked Area Charts. Display comparisons to Previous Period, Previous Year, in one scorecard. Create Financial Year to Date Calculations. Create filters to easily create interactive dashboards, graphs and reports. Create date range selection to easily manage the display range in the charts . Share Reports and Updating Data. Create pages navigation to make a report look like running in a professional financial software. Learn how to Fix error. Free access to the report anytime, anywhere by signing in Google Account...
5. Excel Data Analytics in AML Financial Intelligence Analysis
I created this course as a quick start in using Excel for AML/CFT analysis and investigation for those analysts or investigators that are looking for an alternative tool that is more affordable and has a much simpler learning curve than the conventional vendor specific analytical tools used in AML/CFT analysis and investigations. The course is also designed to accommodate anyone who is interested in having an insight into AML/CFT financial intelligence analysis using excel data analytics or anyone who wants to have a quick start in learning how to apply excel data analytics in AML/CFT financial intelligence analysis...