Course Background:
At present, a new round of scientific and technological revolution and industrial transformation is developing in depth, and digital transformation has become the trend of the times. The "Outline of the 14th Five-Year Plan for National Economic and Social Development of the People's Republic of China and the Long-Range Objectives Through the Year 2035" proposes to accelerate digital development, build a digital economy, a digital society, and a digital society, create a good digital ecology, and build a digital China. **The "14th Five-Year Plan for the Development of the Digital Economy" issued by the People's Republic of China puts forward specific measures to continuously strengthen, optimize and expand China's digital economy. The digital age has put forward inevitable requirements for the digital transformation of accounting. Accelerating the digital transformation of accounting is, on the one hand, an inevitable choice to implement the national informatization development strategy, promote the deep integration of the digital economy and the real economy, and build a digital ChinaOn the other hand, it is of great significance to promote the expansion of accounting functions and improve the level of accounting work and accounting informatization in China.
Finance is an important aspect to measure the operating results of all enterprises, and financial digitalization has always been regarded as an important breakthrough in the digital transformation of enterprises. Therefore, finance is no longer limited to simple algorithms such as accounting subjects + double-entry accounting, but based on enterprise management and social and economic operation, mining, gathering and analyzing business-related data, helping enterprises to gain insight and build a new decision-making mechanism based on data + algorithms to achieve more efficient, scientific, accurate and timely decision-making. Therefore, digital finance is the fusion of data, rules, algorithms and computing power, and is the future of finance.
To this end, this courseUse data to make decisions and build intelligent financial analysis reports for enterprisesBased on financial and business analysis, with Power BI tools as a breakthrough, we will jump out of the traditional IT-oriented self-service business intelligence analysis to business-oriented self-service business intelligence analysis, create tool empowerment, and make data truly its own power, so as to realize its own value and financial value, and help enterprises maximize benefits. The innovative training mode of case practical teaching, in-class teacher guidance, after-class homework consolidation, and online and offline all-round tracking services is adopted throughout the process to ensure that each student can learn and use, improve their core competitiveness in the workplace, add points for personal development, and create opportunities for success.
Course Benefits:
Integration of industry and finance:Create valuable and value-adding financial analysis and statements to support management's decision-making.
Tool Empowerment:Focus on using the flow of information from financial and business activities to improve work efficiency and empower business development.
Quantitative Management:Use data to make decisions and get rid of the bad habit of borrowing experience and intuition to make judgments.
Self-service analytics:Instead of relying on IT personnel and professional analysis teams, self-service business intelligence analysis tools can be used to fully analyze and explore business data, obtain first-hand data analysis results, and assist business decision-making.
Build the system:Help enterprises establish a financial data standard system, promote financial data governance capacity building, and build an intelligent management accounting system, so that managers can see clearly, understand mistakes, improve decision-making, and promote action.
Talent development:Strengthen the cultivation of enterprise accounting information talents, the digital transformation of enterprises is inseparable from the support of high-level talents, and can also better serve the operation and management of enterprises.
Course Duration:2 days, 6 hours a day.
Course Target:
Head of Finance Department:I want to guide the transformation of the finance department, and the focus of my work is more to combine with business operations.
Financial AnalystA large amount of financial data processing needs to be carried out every day, and there is no suitable tool in the face of tedious Excel work.
Finance & AccountingUnwilling to "settle accounts" every day, I want to transform from accounting accounting to management accounting.
Course Method:Theoretical explanation + case teaching + teacher interaction + in-class counseling + student hands-on.
Teaching Software:Participants should bring their own laptops and install Office2016 and above versions and Power BI Desktop software in advance.
Course outline
Lecture 1: Data Thinking - Intelligent Data Analysis Thinking and Related Technologies
Analysis:The transformation and difference between traditional statistical data thinking and intelligent analysis data thinking.
Import:Standardized paradigm of business data classification thinking and financial report data.
1. Structured standards for financial data reports
1.Classification of financial data reports.
2.Application scenarios and conversion between 1D tables and 2D tables.
2. Automated thinking of financial data operation
1.Analysis of the causes of inefficient data processing.
2.How to reprocess the data introduced by the information system.
3.How to quickly process irregular data in batches.
4.How to realize the automation of analysis reports to achieve one-click refresh, so that you can do it once and for all.
Third, the financial data report template thinking
Think:What is a data report template.
1.Ideas for building report templates.
2.What skills are required to build report templates.
Fourth, common data analysis thinking
1.Discover the trend: ** of the idea.
2.Clarifying Relationships: Intersecting Ideas.
3.Validating conclusions: hypothetical ideas.
4.Judging good or bad: the idea of contrast.
5.The Return of All Things: The Idea of Grouping.
6.Look at the scale: the idea of average.
5. Introduction to the five most commonly used tools in daily data analysis
1.The nemesis of massive data - pivot tables.
2.A simple tool comes in handy – conditional formatting.
3.Data classification and statistical tools - classification and summary.
4.Make abstract data visual—charts.
5.Power BI, an interactive data visualization and analysis tool
Lecture 2: Skill Enhancement – Data Preparation in Business Analysis
1. Obtain analysis data - use Power Query to quickly obtain data in the information system
1.Get it from excel or other files.
2.Get it from the database.
3.Get it from the web in the cloud.
2. Cleaning and analysis data - data conversion and processing
1.Row and column management and screening of data.
2.Conversion of data formats.
3.Splitting, merging, and extracting data.
4.Remove duplicates and erroneous values.
5.Transpose and invert.
6.Perspective and reverse perspective.
7.Group by.
8.Columns are added.
9.Collation of dates and times.
3. Integration of data from different information systems - data combination and aggregation
1.Append the query.
2.Merge queries.
3.Merge the co-vaccination classes in the query.
File merging
1) Summarize a large number of worksheets from the workbook.
2) Summarize multiple workbooks from folders.
Lecture 3: Self-Service Analytics – Power BI Business Intelligence Tools Applications
Import:
1) Introduction to the Power BI series components.
2) Power BI Desktop with installation.
1.Query view in pbid: Get data and query editing.
2.Relationship view in pbid: Create data relationships (modeling) between tables of underlying business facts
3.Data view in pbid: Create columns and adjust the format of the type.
4.Report view in pbid: Create charts with visualizations and optimize formatting.
5.Visualizations in Pbid: Native visualizations in Power BI.
6.Power BI Work Master Process: A process framework for self-service business intelligence analytics.
Leverage Power BI tools to quickly visualize your data
1) Operation and formatting of table and matrix visualizations.
2) Key indicators: the operation method of card charts and KPI charts.
3) Use column charts and bar charts to compare and analyze operational data.
4) Use line charts and area charts to analyze the trend of operational data.
5) Use pie charts and donut charts to analyze the proportion of operational data.
6) Use scatter plots to analyze the correlation of operational data.
7) Use maps for regional analysis of operational data.
8) Use waterfall charts to analyze the influencing factors of operational data.
9) Visualization of personalized analysis methods.
10) Slicing, filtering and interactive analysis of visualization objects.
11) Methods and applications from macro analysis drilling to micro analysis.
Lecture 4: Data Modeling - Using business data and financial data in the process of business to establish an analysis model
Think:What is a business data model.
Import:There are two types of tables in the data model: fact tables and dimension tables.
1.Standards and norms for the Fact Sheet.
2.Thinking and method of creating dimension tables.
3.General business modeling thinking methods and model architecture.
4.Establish and manage data relationships in modeling.
5.Understand and create hierarchies in data models.
6.Ideas and methods for creating date tables in a data model.
Computed elements in the data model
1) Calculated Columns: Enhance the viewing angle.
2) Metrics: Quantitative analysis indicators.
3) Calculation table: an intermediate process to obtain the results.
Computing environment and computation in the data model
1) Filter the context.
2) Calculate the row context.
3) Context conversion.
DAX data analysis expressions are used to construct analysis indicators in the analysis model
1) Overview of DAX data analysis expressions and how to use them.
2) Calculation methods and ideas of financial indicators in the data model.
3) The construction of partial and overall comparative analysis indicators.
4) Analyze the ideas and methods of dynamic interaction of indicators.
Lecture 5: Intelligent Reporting - Create Intelligent Financial Analysis Reports
1. The application of time intelligence in financial analysis and accounting periods
Calculation of the previous period indicators for the accounting period
Year-on-year period, quarter-on-quarter, month-on-month.
Calculation of the cumulative indicators since the beginning of the period
Year-to-date, quarter-to-date, month-to-date.
Calculation of the current analysis indicators
Calculation of the last day of the current period, calculation of the day before the last day, calculation of the year and month of the current period, and calculation of the year-to-date date of the current period.
4.Cumulative calculations from the earliest date in history to the present.
5.Analyze using moving averages.
2. Visualization design of intelligent financial statements
Intelligent visual design of balance sheet
1) Create a dimension table of the balance sheet.
2) Establishment of basic metrics.
3) Improvement of the balance sheet matrix.
4) Ratio indicator calculation and dashboard visualization.
Intelligent visual design of income statement
1) Create a dimension table for the income statement.
2) Create a base measure.
3) Income statement template application.
4) Measurement and calculation of income statement items.
5) Customize the display format of positive and negative numbers.
6) Visualization design of income statement matrix.
7) Visual chart making.
Intelligent visual design of cash flow statement
1) Create a dimension table of the cash flow statement.
2) Establishment of cash flow statement measures.
3) Visualize the output.
4.Creation of visual dashboards for financial comprehensive indicators.
5.Create a DuPont Analytics visualization dashboard with financial analysis metrics.
3. Release and sharing of intelligent data visualization analysis reports
1.Ideas and methods for planning financial reporting pages in Power BI.
2.Use the themes in the view to play around with the color palette of your Power BI reports.
3.Insert buttons and shapes into the Power BI report page to complete the report page.
4.Make a report in the Power BI report page.
5.Leverage PowerBI intelligent storytelling to easily generate dynamic report summaries.
6.Save the report and publish it to the Power BI site.
7.Create dashboards, reports, and phone views in Power BI.
8.Publish a report or report share to the cloud.