Learning by Doing Series

Financial Ratios Analysis in BI

Topic 21 — Deploy Financial Ratios BI Model to SQL Server. Move the validated CSV training model into a working SQL Server database with tables, data loads, fixes, validations, and reporting views.

Topic 21 — Deploy Financial Ratios BI Model to SQL Server

This topic documents the real deployment process used to move the Financial Ratios Analysis in BI training package from CSV files into SQL Server.

Python Scripts→CSV Files→SQL Server Tables→SQL Views→Power BI Ready

Production / Cybersecurity Warning

This exercise uses synthetic training data. Do not run database creation, table drops, truncates, bulk loads, or permission commands against production systems without formal authorization.

Before deploying any real financial or accounting model, validate backups, permissions, least-privilege access, change-control approval, sandbox testing, audit requirements, and organizational cybersecurity protocols.

Objective

Deploy the completed synthetic financial BI model into SQL Server, validate the loaded tables, fix CSV loading issues, create reporting views, and prepare the model for Power BI.

Database Created
FinancialRatiosBI
Deployment Result
18 tables loaded, 4 views created, financial ratio categories validated.

Business Scenario

The training package already created a complete set of CSV files using Python. The next step is to move those files into a relational database so the model can be queried, validated, reused, and connected to Power BI as a real SQL Server data source.

Step-by-Step Practice

Step 1 — Create the Database and Tables

We executed SQL_Create_Tables.sql in SQL Server Management Studio. This created FinancialRatiosBI and all base tables.

SQL - Validate created tables 
USE FinancialRatiosBI;
GO

SELECT 
    TABLE_SCHEMA,
    TABLE_NAME
FROM INFORMATION_SCHEMA.TABLES
WHERE TABLE_TYPE = 'BASE TABLE'
ORDER BY TABLE_NAME;
GO

Step 2 — Copy CSV Files to a SQL-Friendly Folder

SQL Server could not read directly from the user Documents path because the service account is different from the interactive Windows user.

PowerShell 
New-Item -ItemType Directory -Path "C:\SQLData" -Force

Copy-Item `
  -Path "." `
  -Destination "C:\SQLData\financial_ratios_bi_training" `
  -Recurse `
  -Force

icacls "C:\SQLData\financial_ratios_bi_training" /grant "Everyone:(OI)(CI)R" /T

Step 3 — Test a Single BULK INSERT

The first test confirmed SQL Server could read the file, but basic comma parsing split fields that contained commas inside text.

SQL - Initial test that exposed CSV quote issue 
USE FinancialRatiosBI;
GO

TRUNCATE TABLE dbo.Dim_Company;
GO

BULK INSERT dbo.Dim_Company
FROM 'C:\SQLData\financial_ratios_bi_training\Dim_Company.csv'
WITH (
    FIRSTROW = 2,
    FIELDTERMINATOR = ',',
    ROWTERMINATOR = '0x0a',
    TABLOCK,
    CODEPAGE = '65001'
);
GO

SELECT * FROM dbo.Dim_Company;
GO

Step 4 — Fix CSV Loading with FORMAT = CSV

FORMAT = 'CSV' and FIELDQUOTE = '"' fixed quoted text fields.

SQL - Correct single-table load 
USE FinancialRatiosBI;
GO

TRUNCATE TABLE dbo.Dim_Company;
GO

BULK INSERT dbo.Dim_Company
FROM 'C:\SQLData\financial_ratios_bi_training\Dim_Company.csv'
WITH (
    FORMAT = 'CSV',
    FIRSTROW = 2,
    FIELDQUOTE = '"',
    ROWTERMINATOR = '0x0a',
    TABLOCK,
    CODEPAGE = '65001'
);
GO

SELECT * FROM dbo.Dim_Company;
GO

Step 5 — Load All Tables

Most tables loaded successfully using the fixed CSV pattern.

SQL - Load all CSV files with FORMAT = CSV 
USE FinancialRatiosBI;
GO

/* Load All CSV Files - Fixed Version */

TRUNCATE TABLE dbo.Data_Quality_Issues;
TRUNCATE TABLE dbo.Data_Quality_Issues_Detail;
TRUNCATE TABLE dbo.Fact_Balance_Sheet;
TRUNCATE TABLE dbo.Fact_Cash_Flow;
TRUNCATE TABLE dbo.Fact_Cash_Flow_Ratios;
TRUNCATE TABLE dbo.Fact_Debt_Ratios;
TRUNCATE TABLE dbo.Fact_Employees;
TRUNCATE TABLE dbo.Fact_Income_Statement;
TRUNCATE TABLE dbo.Fact_Investment_Valuation_Ratios;
TRUNCATE TABLE dbo.Fact_Liquidity_Ratios;
TRUNCATE TABLE dbo.Fact_Market_Data;
TRUNCATE TABLE dbo.Fact_Operating_Performance_Ratios;
TRUNCATE TABLE dbo.Fact_Profitability_Ratios;
TRUNCATE TABLE dbo.Fact_Trial_Balance;
TRUNCATE TABLE dbo.Mapping_Financial_Statements;
TRUNCATE TABLE dbo.Dim_Account;
TRUNCATE TABLE dbo.Dim_Company;
TRUNCATE TABLE dbo.Dim_Period;
GO

-- Use this BULK INSERT pattern for every CSV table.
BULK INSERT dbo.Dim_Company
FROM 'C:\SQLData\financial_ratios_bi_training\Dim_Company.csv'
WITH (FORMAT = 'CSV', FIRSTROW = 2, FIELDQUOTE = '"', ROWTERMINATOR = '0x0a', TABLOCK, CODEPAGE = '65001');
GO

-- Repeat same pattern for Dim_Period, Dim_Account, Mapping, all Fact tables, and DQ tables.
-- In the live execution, most tables loaded successfully with this pattern.

Step 6 — Validate Row Counts

The row count query identified the few tables that still needed help.

SQL - Row count validation 
USE FinancialRatiosBI;
GO

SELECT 'Dim_Company' AS TableName, COUNT(*) AS [RowCount] FROM dbo.Dim_Company
UNION ALL SELECT 'Dim_Period', COUNT(*) FROM dbo.Dim_Period
UNION ALL SELECT 'Dim_Account', COUNT(*) FROM dbo.Dim_Account
UNION ALL SELECT 'Mapping_Financial_Statements', COUNT(*) FROM dbo.Mapping_Financial_Statements
UNION ALL SELECT 'Fact_Trial_Balance', COUNT(*) FROM dbo.Fact_Trial_Balance
UNION ALL SELECT 'Fact_Income_Statement', COUNT(*) FROM dbo.Fact_Income_Statement
UNION ALL SELECT 'Fact_Balance_Sheet', COUNT(*) FROM dbo.Fact_Balance_Sheet
UNION ALL SELECT 'Fact_Cash_Flow', COUNT(*) FROM dbo.Fact_Cash_Flow
UNION ALL SELECT 'Fact_Market_Data', COUNT(*) FROM dbo.Fact_Market_Data
UNION ALL SELECT 'Fact_Employees', COUNT(*) FROM dbo.Fact_Employees
UNION ALL SELECT 'Fact_Liquidity_Ratios', COUNT(*) FROM dbo.Fact_Liquidity_Ratios
UNION ALL SELECT 'Fact_Profitability_Ratios', COUNT(*) FROM dbo.Fact_Profitability_Ratios
UNION ALL SELECT 'Fact_Debt_Ratios', COUNT(*) FROM dbo.Fact_Debt_Ratios
UNION ALL SELECT 'Fact_Operating_Performance_Ratios', COUNT(*) FROM dbo.Fact_Operating_Performance_Ratios
UNION ALL SELECT 'Fact_Cash_Flow_Ratios', COUNT(*) FROM dbo.Fact_Cash_Flow_Ratios
UNION ALL SELECT 'Fact_Investment_Valuation_Ratios', COUNT(*) FROM dbo.Fact_Investment_Valuation_Ratios
UNION ALL SELECT 'Data_Quality_Issues', COUNT(*) FROM dbo.Data_Quality_Issues
UNION ALL SELECT 'Data_Quality_Issues_Detail', COUNT(*) FROM dbo.Data_Quality_Issues_Detail;
GO

Step 7 — Use Python + pyodbc for the Hard CSV Tables

Dim_Account and Fact_Profitability_Ratios were loaded with pandas and pyodbc.

PowerShell - Install packages and run loader 
py -m pip install pandas pyodbc
py load_failed_tables_to_sql.py
Python - load_failed_tables_to_sql.py 
from pathlib import Path
import pandas as pd
import pyodbc

base_path = Path(r"C:\SQLData\financial_ratios_bi_training")
server = r"JCDCOMPUTER"
database = "FinancialRatiosBI"

connection_string = (
    "DRIVER={ODBC Driver 17 for SQL Server};"
    f"SERVER={server};"
    f"DATABASE={database};"
    "Trusted_Connection=yes;"
)

conn = pyodbc.connect(connection_string)
cursor = conn.cursor()
cursor.fast_executemany = True

tables = {
    "Dim_Account": "Dim_Account.csv",
    "Fact_Profitability_Ratios": "Fact_Profitability_Ratios.csv"
}

for table_name, file_name in tables.items():
    file_path = base_path / file_name
    print(f"Loading {file_name} into dbo.{table_name}...")
    df = pd.read_csv(file_path, dtype=str).fillna("")
    df.columns = [col.strip().replace(" ", "_").replace("/", "_").replace("-", "_") for col in df.columns]
    cursor.execute(f"DELETE FROM dbo.{table_name};")
    conn.commit()
    columns = list(df.columns)
    column_list = ", ".join(f"[{col}]" for col in columns)
    placeholders = ", ".join("?" for _ in columns)
    insert_sql = f"INSERT INTO dbo.{table_name} ({column_list}) VALUES ({placeholders})"
    rows = [tuple(row) for row in df.itertuples(index=False, name=None)]
    cursor.executemany(insert_sql, rows)
    conn.commit()
    print(f"{table_name}: {len(df)} rows loaded successfully.")

cursor.close()
conn.close()
print("Failed tables loaded successfully.")

Step 8 — Confirm All Tables Loaded

SQL - Final row count validation 
USE FinancialRatiosBI;
GO

SELECT 'Dim_Company' AS TableName, COUNT(*) AS [RowCount] FROM dbo.Dim_Company
UNION ALL SELECT 'Dim_Period', COUNT(*) FROM dbo.Dim_Period
UNION ALL SELECT 'Dim_Account', COUNT(*) FROM dbo.Dim_Account
UNION ALL SELECT 'Mapping_Financial_Statements', COUNT(*) FROM dbo.Mapping_Financial_Statements
UNION ALL SELECT 'Fact_Trial_Balance', COUNT(*) FROM dbo.Fact_Trial_Balance
UNION ALL SELECT 'Fact_Income_Statement', COUNT(*) FROM dbo.Fact_Income_Statement
UNION ALL SELECT 'Fact_Balance_Sheet', COUNT(*) FROM dbo.Fact_Balance_Sheet
UNION ALL SELECT 'Fact_Cash_Flow', COUNT(*) FROM dbo.Fact_Cash_Flow
UNION ALL SELECT 'Fact_Market_Data', COUNT(*) FROM dbo.Fact_Market_Data
UNION ALL SELECT 'Fact_Employees', COUNT(*) FROM dbo.Fact_Employees
UNION ALL SELECT 'Fact_Liquidity_Ratios', COUNT(*) FROM dbo.Fact_Liquidity_Ratios
UNION ALL SELECT 'Fact_Profitability_Ratios', COUNT(*) FROM dbo.Fact_Profitability_Ratios
UNION ALL SELECT 'Fact_Debt_Ratios', COUNT(*) FROM dbo.Fact_Debt_Ratios
UNION ALL SELECT 'Fact_Operating_Performance_Ratios', COUNT(*) FROM dbo.Fact_Operating_Performance_Ratios
UNION ALL SELECT 'Fact_Cash_Flow_Ratios', COUNT(*) FROM dbo.Fact_Cash_Flow_Ratios
UNION ALL SELECT 'Fact_Investment_Valuation_Ratios', COUNT(*) FROM dbo.Fact_Investment_Valuation_Ratios
UNION ALL SELECT 'Data_Quality_Issues', COUNT(*) FROM dbo.Data_Quality_Issues
UNION ALL SELECT 'Data_Quality_Issues_Detail', COUNT(*) FROM dbo.Data_Quality_Issues_Detail;
GO

Step 9 — Create SQL Reporting Views

SQL_Financial_Views.sql created the reporting views.

SQL - Validate views and ratio categories 
USE FinancialRatiosBI;
GO

SELECT TABLE_SCHEMA, TABLE_NAME
FROM INFORMATION_SCHEMA.VIEWS
ORDER BY TABLE_NAME;
GO

SELECT TOP 20 *
FROM dbo.vw_All_Financial_Ratios;
GO

SELECT RatioCategory, COUNT(*) AS [RowCount], COUNT(DISTINCT RatioName) AS DistinctRatios
FROM dbo.vw_All_Financial_Ratios
GROUP BY RatioCategory
ORDER BY RatioCategory;
GO

Final SQL Server Deployment Result

The SQL Server deployment was completed successfully. The database contains 18 loaded tables and 4 reporting views.

Final Loaded Tables

Table NameRow Count
Dim_Company5
Dim_Period20
Dim_Account32
Mapping_Financial_Statements28
Fact_Trial_Balance2,800
Fact_Income_Statement1,500
Fact_Balance_Sheet2,400
Fact_Cash_Flow700
Fact_Market_Data100
Fact_Employees100
Fact_Liquidity_Ratios800
Fact_Profitability_Ratios1,100
Fact_Debt_Ratios1,000
Fact_Operating_Performance_Ratios900
Fact_Cash_Flow_Ratios1,200
Fact_Investment_Valuation_Ratios1,700
Data_Quality_Issues11
Data_Quality_Issues_Detail6,782

Created SQL Views

View NameStatus
vw_All_Financial_RatiosCreated successfully
vw_Executive_Financial_SummaryCreated successfully
vw_Financial_Health_InputsCreated successfully
vw_Latest_Period_RatiosCreated successfully

Validated Ratio Categories

Ratio CategoryRow CountDistinct Ratios
Cash Flow1,20012
Debt1,00010
Investment Valuation1,70017
Liquidity8008
Operating Performance9009
Profitability1,10011

Business Interpretation

This topic turns the course into a real database workflow. The model is no longer only a collection of CSV files. It is now a SQL Server financial mini data warehouse with tables, validated loads, reporting views, and Power BI readiness.

The key learning is that data deployment is not just a technical copy process. It requires permissions, path control, CSV parsing, type handling, validation, troubleshooting, and final business verification.

Final Result of Topic 21

Final architecture 
Python scripts → CSV files → SQL Server tables → SQL reporting views → Power BI-ready model

Next step: Connect Power BI Desktop to SQL Server using database FinancialRatiosBI and import the SQL views.

Topic 21 — Desplegar Financial Ratios BI Model en SQL Server

This topic documents the real deployment process used to move the Financial Ratios Analysis in BI training package from CSV files into SQL Server.

Python Scripts→CSV Files→SQL Server Tables→SQL Views→Power BI Ready

Advertencia de Producción / Ciberseguridad

This exercise uses synthetic training data. Do not run database creation, table drops, truncates, bulk loads, or permission commands against production systems without formal authorization.

Before deploying any real financial or accounting model, validate backups, permissions, least-privilege access, change-control approval, sandbox testing, audit requirements, and organizational cybersecurity protocols.

Objetivo

Deploy the completed synthetic financial BI model into SQL Server, validate the loaded tables, fix CSV loading issues, create reporting views, and prepare the model for Power BI.

Database Created
FinancialRatiosBI
Deployment Result
18 tables loaded, 4 views created, financial ratio categories validated.

Escenario de Negocio

The training package already created a complete set of CSV files using Python. The next step is to move those files into a relational database so the model can be queried, validated, reused, and connected to Power BI as a real SQL Server data source.

Práctica Paso a Paso

Step 1 — Create the Database and Tables

We executed SQL_Create_Tables.sql in SQL Server Management Studio. This created FinancialRatiosBI and all base tables.

SQL - Validate created tables 
USE FinancialRatiosBI;
GO

SELECT 
    TABLE_SCHEMA,
    TABLE_NAME
FROM INFORMATION_SCHEMA.TABLES
WHERE TABLE_TYPE = 'BASE TABLE'
ORDER BY TABLE_NAME;
GO

Step 2 — Copy CSV Files to a SQL-Friendly Folder

SQL Server could not read directly from the user Documents path because the service account is different from the interactive Windows user.

PowerShell 
New-Item -ItemType Directory -Path "C:\SQLData" -Force

Copy-Item `
  -Path "." `
  -Destination "C:\SQLData\financial_ratios_bi_training" `
  -Recurse `
  -Force

icacls "C:\SQLData\financial_ratios_bi_training" /grant "Everyone:(OI)(CI)R" /T

Step 3 — Test a Single BULK INSERT

The first test confirmed SQL Server could read the file, but basic comma parsing split fields that contained commas inside text.

SQL - Initial test that exposed CSV quote issue 
USE FinancialRatiosBI;
GO

TRUNCATE TABLE dbo.Dim_Company;
GO

BULK INSERT dbo.Dim_Company
FROM 'C:\SQLData\financial_ratios_bi_training\Dim_Company.csv'
WITH (
    FIRSTROW = 2,
    FIELDTERMINATOR = ',',
    ROWTERMINATOR = '0x0a',
    TABLOCK,
    CODEPAGE = '65001'
);
GO

SELECT * FROM dbo.Dim_Company;
GO

Step 4 — Fix CSV Loading with FORMAT = CSV

FORMAT = 'CSV' and FIELDQUOTE = '"' fixed quoted text fields.

SQL - Correct single-table load 
USE FinancialRatiosBI;
GO

TRUNCATE TABLE dbo.Dim_Company;
GO

BULK INSERT dbo.Dim_Company
FROM 'C:\SQLData\financial_ratios_bi_training\Dim_Company.csv'
WITH (
    FORMAT = 'CSV',
    FIRSTROW = 2,
    FIELDQUOTE = '"',
    ROWTERMINATOR = '0x0a',
    TABLOCK,
    CODEPAGE = '65001'
);
GO

SELECT * FROM dbo.Dim_Company;
GO

Step 5 — Load All Tables

Most tables loaded successfully using the fixed CSV pattern.

SQL - Load all CSV files with FORMAT = CSV 
USE FinancialRatiosBI;
GO

/* Load All CSV Files - Fixed Version */

TRUNCATE TABLE dbo.Data_Quality_Issues;
TRUNCATE TABLE dbo.Data_Quality_Issues_Detail;
TRUNCATE TABLE dbo.Fact_Balance_Sheet;
TRUNCATE TABLE dbo.Fact_Cash_Flow;
TRUNCATE TABLE dbo.Fact_Cash_Flow_Ratios;
TRUNCATE TABLE dbo.Fact_Debt_Ratios;
TRUNCATE TABLE dbo.Fact_Employees;
TRUNCATE TABLE dbo.Fact_Income_Statement;
TRUNCATE TABLE dbo.Fact_Investment_Valuation_Ratios;
TRUNCATE TABLE dbo.Fact_Liquidity_Ratios;
TRUNCATE TABLE dbo.Fact_Market_Data;
TRUNCATE TABLE dbo.Fact_Operating_Performance_Ratios;
TRUNCATE TABLE dbo.Fact_Profitability_Ratios;
TRUNCATE TABLE dbo.Fact_Trial_Balance;
TRUNCATE TABLE dbo.Mapping_Financial_Statements;
TRUNCATE TABLE dbo.Dim_Account;
TRUNCATE TABLE dbo.Dim_Company;
TRUNCATE TABLE dbo.Dim_Period;
GO

-- Use this BULK INSERT pattern for every CSV table.
BULK INSERT dbo.Dim_Company
FROM 'C:\SQLData\financial_ratios_bi_training\Dim_Company.csv'
WITH (FORMAT = 'CSV', FIRSTROW = 2, FIELDQUOTE = '"', ROWTERMINATOR = '0x0a', TABLOCK, CODEPAGE = '65001');
GO

-- Repeat same pattern for Dim_Period, Dim_Account, Mapping, all Fact tables, and DQ tables.
-- In the live execution, most tables loaded successfully with this pattern.

Step 6 — Validate Row Counts

The row count query identified the few tables that still needed help.

SQL - Row count validation 
USE FinancialRatiosBI;
GO

SELECT 'Dim_Company' AS TableName, COUNT(*) AS [RowCount] FROM dbo.Dim_Company
UNION ALL SELECT 'Dim_Period', COUNT(*) FROM dbo.Dim_Period
UNION ALL SELECT 'Dim_Account', COUNT(*) FROM dbo.Dim_Account
UNION ALL SELECT 'Mapping_Financial_Statements', COUNT(*) FROM dbo.Mapping_Financial_Statements
UNION ALL SELECT 'Fact_Trial_Balance', COUNT(*) FROM dbo.Fact_Trial_Balance
UNION ALL SELECT 'Fact_Income_Statement', COUNT(*) FROM dbo.Fact_Income_Statement
UNION ALL SELECT 'Fact_Balance_Sheet', COUNT(*) FROM dbo.Fact_Balance_Sheet
UNION ALL SELECT 'Fact_Cash_Flow', COUNT(*) FROM dbo.Fact_Cash_Flow
UNION ALL SELECT 'Fact_Market_Data', COUNT(*) FROM dbo.Fact_Market_Data
UNION ALL SELECT 'Fact_Employees', COUNT(*) FROM dbo.Fact_Employees
UNION ALL SELECT 'Fact_Liquidity_Ratios', COUNT(*) FROM dbo.Fact_Liquidity_Ratios
UNION ALL SELECT 'Fact_Profitability_Ratios', COUNT(*) FROM dbo.Fact_Profitability_Ratios
UNION ALL SELECT 'Fact_Debt_Ratios', COUNT(*) FROM dbo.Fact_Debt_Ratios
UNION ALL SELECT 'Fact_Operating_Performance_Ratios', COUNT(*) FROM dbo.Fact_Operating_Performance_Ratios
UNION ALL SELECT 'Fact_Cash_Flow_Ratios', COUNT(*) FROM dbo.Fact_Cash_Flow_Ratios
UNION ALL SELECT 'Fact_Investment_Valuation_Ratios', COUNT(*) FROM dbo.Fact_Investment_Valuation_Ratios
UNION ALL SELECT 'Data_Quality_Issues', COUNT(*) FROM dbo.Data_Quality_Issues
UNION ALL SELECT 'Data_Quality_Issues_Detail', COUNT(*) FROM dbo.Data_Quality_Issues_Detail;
GO

Step 7 — Use Python + pyodbc for the Hard CSV Tables

Dim_Account and Fact_Profitability_Ratios were loaded with pandas and pyodbc.

PowerShell - Install packages and run loader 
py -m pip install pandas pyodbc
py load_failed_tables_to_sql.py
Python - load_failed_tables_to_sql.py 
from pathlib import Path
import pandas as pd
import pyodbc

base_path = Path(r"C:\SQLData\financial_ratios_bi_training")
server = r"JCDCOMPUTER"
database = "FinancialRatiosBI"

connection_string = (
    "DRIVER={ODBC Driver 17 for SQL Server};"
    f"SERVER={server};"
    f"DATABASE={database};"
    "Trusted_Connection=yes;"
)

conn = pyodbc.connect(connection_string)
cursor = conn.cursor()
cursor.fast_executemany = True

tables = {
    "Dim_Account": "Dim_Account.csv",
    "Fact_Profitability_Ratios": "Fact_Profitability_Ratios.csv"
}

for table_name, file_name in tables.items():
    file_path = base_path / file_name
    print(f"Loading {file_name} into dbo.{table_name}...")
    df = pd.read_csv(file_path, dtype=str).fillna("")
    df.columns = [col.strip().replace(" ", "_").replace("/", "_").replace("-", "_") for col in df.columns]
    cursor.execute(f"DELETE FROM dbo.{table_name};")
    conn.commit()
    columns = list(df.columns)
    column_list = ", ".join(f"[{col}]" for col in columns)
    placeholders = ", ".join("?" for _ in columns)
    insert_sql = f"INSERT INTO dbo.{table_name} ({column_list}) VALUES ({placeholders})"
    rows = [tuple(row) for row in df.itertuples(index=False, name=None)]
    cursor.executemany(insert_sql, rows)
    conn.commit()
    print(f"{table_name}: {len(df)} rows loaded successfully.")

cursor.close()
conn.close()
print("Failed tables loaded successfully.")

Step 8 — Confirm All Tables Loaded

SQL - Final row count validation 
USE FinancialRatiosBI;
GO

SELECT 'Dim_Company' AS TableName, COUNT(*) AS [RowCount] FROM dbo.Dim_Company
UNION ALL SELECT 'Dim_Period', COUNT(*) FROM dbo.Dim_Period
UNION ALL SELECT 'Dim_Account', COUNT(*) FROM dbo.Dim_Account
UNION ALL SELECT 'Mapping_Financial_Statements', COUNT(*) FROM dbo.Mapping_Financial_Statements
UNION ALL SELECT 'Fact_Trial_Balance', COUNT(*) FROM dbo.Fact_Trial_Balance
UNION ALL SELECT 'Fact_Income_Statement', COUNT(*) FROM dbo.Fact_Income_Statement
UNION ALL SELECT 'Fact_Balance_Sheet', COUNT(*) FROM dbo.Fact_Balance_Sheet
UNION ALL SELECT 'Fact_Cash_Flow', COUNT(*) FROM dbo.Fact_Cash_Flow
UNION ALL SELECT 'Fact_Market_Data', COUNT(*) FROM dbo.Fact_Market_Data
UNION ALL SELECT 'Fact_Employees', COUNT(*) FROM dbo.Fact_Employees
UNION ALL SELECT 'Fact_Liquidity_Ratios', COUNT(*) FROM dbo.Fact_Liquidity_Ratios
UNION ALL SELECT 'Fact_Profitability_Ratios', COUNT(*) FROM dbo.Fact_Profitability_Ratios
UNION ALL SELECT 'Fact_Debt_Ratios', COUNT(*) FROM dbo.Fact_Debt_Ratios
UNION ALL SELECT 'Fact_Operating_Performance_Ratios', COUNT(*) FROM dbo.Fact_Operating_Performance_Ratios
UNION ALL SELECT 'Fact_Cash_Flow_Ratios', COUNT(*) FROM dbo.Fact_Cash_Flow_Ratios
UNION ALL SELECT 'Fact_Investment_Valuation_Ratios', COUNT(*) FROM dbo.Fact_Investment_Valuation_Ratios
UNION ALL SELECT 'Data_Quality_Issues', COUNT(*) FROM dbo.Data_Quality_Issues
UNION ALL SELECT 'Data_Quality_Issues_Detail', COUNT(*) FROM dbo.Data_Quality_Issues_Detail;
GO

Step 9 — Create SQL Reporting Views

SQL_Financial_Views.sql created the reporting views.

SQL - Validate views and ratio categories 
USE FinancialRatiosBI;
GO

SELECT TABLE_SCHEMA, TABLE_NAME
FROM INFORMATION_SCHEMA.VIEWS
ORDER BY TABLE_NAME;
GO

SELECT TOP 20 *
FROM dbo.vw_All_Financial_Ratios;
GO

SELECT RatioCategory, COUNT(*) AS [RowCount], COUNT(DISTINCT RatioName) AS DistinctRatios
FROM dbo.vw_All_Financial_Ratios
GROUP BY RatioCategory
ORDER BY RatioCategory;
GO

Resultado Final del Deploy en SQL Server

The SQL Server deployment was completed successfully. The database contains 18 loaded tables and 4 reporting views.

Tablas Cargadas

Table NameRow Count
Dim_Company5
Dim_Period20
Dim_Account32
Mapping_Financial_Statements28
Fact_Trial_Balance2,800
Fact_Income_Statement1,500
Fact_Balance_Sheet2,400
Fact_Cash_Flow700
Fact_Market_Data100
Fact_Employees100
Fact_Liquidity_Ratios800
Fact_Profitability_Ratios1,100
Fact_Debt_Ratios1,000
Fact_Operating_Performance_Ratios900
Fact_Cash_Flow_Ratios1,200
Fact_Investment_Valuation_Ratios1,700
Data_Quality_Issues11
Data_Quality_Issues_Detail6,782

Views SQL Creadas

View NameStatus
vw_All_Financial_RatiosCreated successfully
vw_Executive_Financial_SummaryCreated successfully
vw_Financial_Health_InputsCreated successfully
vw_Latest_Period_RatiosCreated successfully

Categorías de Ratios Validadas

Ratio CategoryRow CountDistinct Ratios
Cash Flow1,20012
Debt1,00010
Investment Valuation1,70017
Liquidity8008
Operating Performance9009
Profitability1,10011

Interpretación de Negocio

This topic turns the course into a real database workflow. The model is no longer only a collection of CSV files. It is now a SQL Server financial mini data warehouse with tables, validated loads, reporting views, and Power BI readiness.

The key learning is that data deployment is not just a technical copy process. It requires permissions, path control, CSV parsing, type handling, validation, troubleshooting, and final business verification.

Resultado Final del Topic 21

Final architecture 
Python scripts → CSV files → SQL Server tables → SQL reporting views → Power BI-ready model

Next step: Connect Power BI Desktop to SQL Server using database FinancialRatiosBI and import the SQL views.