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Pizza Sales SQL Queries.docx
Pizza Sales SQL Queries.docx
README.md
README.md

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Pizza-Shop-Sales-Analysis-SQL-Power-BI

This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.

Key Features

  • SQL queries and SSIS packages to extract and transform data from SQL Server database.
  • Power Query in Power BI to connect to SQL Server and load data.
  • Compare results from SQL SSIS vs Power Query.
  • Power BI reports and dashboards to visualize sales trends and customer insights.
  • Insights into best selling pizzas, toppings, customer preferences and more.

Built Using

  • SQL Server - As the database to store sales data.
  • SQL Server Integration Services (SSIS) - To extract and transform data.
  • Power BI - Power Query to connect to SQL and Power BI reports for analysis.

SQL Server SSIS Queries File Contains SQL Queries and results screenshots:

Pizza Sales SQL Queries.docx

Benefits

  • Compare ETL techniques using SQL SSIS vs Power Query.
  • Understand performance and limitations of each approach.
  • Gain insights into pizza sales trends, customer preferences and more.
  • Optimize menu, ingredients and marketing based on analysis.

This dashboard in Power BI shows an overview of total sales, top pizzas sold and sales by Pizza type. Screenshot 2024-02-03 165956Screenshot 2024-02-03 170157Screenshot 2024-02-03 170045Screenshot 2024-02-03 170024

Analysis provides insights to:

  • Improve menu options
  • Optimize ingredient stocking
  • Target marketing and promotions

Comparing SQL SSIS vs Power Query helps determine:

  • Which ETL technique is faster
  • Which is easier to maintain
  • Any limitations of each approach

Power BI Sales Analytics File :

Pizza Sales Analytics.pbix

Hope this helps! Let me know if you have any other questions.

About

This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.

Topics

capstone-projectdata-analysisdata-visualizationpizzastoreportfoliopower-bipredictive-analyticssales-analysissales-dashboardsales-forecastingsales-trendssqlsql-analysissqlserverssisssms

Resources

Readme
Activity

Stars

2 stars

Watchers

1 watching

Forks

1 fork
Report repository

Releases

Packages

Contributors

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Repository files navigation
Pizza-Shop-Sales-Analysis-SQL-Power-BI
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Key Features
  • SQL queries and SSIS packages to extract and transform data from SQL Server database.
  • Power Query in Power BI to connect to SQL Server and load data.
  • Compare results from SQL SSIS vs Power Query.
  • Power BI reports and dashboards to visualize sales trends and customer insights.
  • Insights into best selling pizzas, toppings, customer preferences and more.
Built Using
  • SQL Server - As the database to store sales data.
  • SQL Server Integration Services (SSIS) - To extract and transform data.
  • Power BI - Power Query to connect to SQL and Power BI reports for analysis.
SQL Server SSIS Queries File Contains SQL Queries and results screenshots:
Pizza Sales SQL Queries.docx
Benefits
  • Compare ETL techniques using SQL SSIS vs Power Query.
  • Understand performance and limitations of each approach.
  • Gain insights into pizza sales trends, customer preferences and more.
  • Optimize menu, ingredients and marketing based on analysis.
This dashboard in Power BI shows an overview of total sales, top pizzas sold and sales by Pizza type.
Screenshot 2024-02-03 165956Screenshot 2024-02-03 170157Screenshot 2024-02-03 170045Screenshot 2024-02-03 170024
Analysis provides insights to:
  • Improve menu options
  • Optimize ingredient stocking
  • Target marketing and promotions
Comparing SQL SSIS vs Power Query helps determine:
  • Which ETL technique is faster
  • Which is easier to maintain
  • Any limitations of each approach
Power BI Sales Analytics File :
Pizza Sales Analytics.pbix
Hope this helps! Let me know if you have any other questions.
About
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Topics
capstone-projectdata-analysisdata-visualizationpizzastoreportfoliopower-bipredictive-analyticssales-analysissales-dashboardsales-forecastingsales-trendssqlsql-analysissqlserverssisssms
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Repository files navigation
Pizza-Shop-Sales-Analysis-SQL-Power-BI
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Key Features
  • SQL queries and SSIS packages to extract and transform data from SQL Server database.
  • Power Query in Power BI to connect to SQL Server and load data.
  • Compare results from SQL SSIS vs Power Query.
  • Power BI reports and dashboards to visualize sales trends and customer insights.
  • Insights into best selling pizzas, toppings, customer preferences and more.
Built Using
  • SQL Server - As the database to store sales data.
  • SQL Server Integration Services (SSIS) - To extract and transform data.
  • Power BI - Power Query to connect to SQL and Power BI reports for analysis.
SQL Server SSIS Queries File Contains SQL Queries and results screenshots:
Pizza Sales SQL Queries.docx
Benefits
  • Compare ETL techniques using SQL SSIS vs Power Query.
  • Understand performance and limitations of each approach.
  • Gain insights into pizza sales trends, customer preferences and more.
  • Optimize menu, ingredients and marketing based on analysis.
This dashboard in Power BI shows an overview of total sales, top pizzas sold and sales by Pizza type.
Screenshot 2024-02-03 165956Screenshot 2024-02-03 170157Screenshot 2024-02-03 170045Screenshot 2024-02-03 170024
Analysis provides insights to:
  • Improve menu options
  • Optimize ingredient stocking
  • Target marketing and promotions
Comparing SQL SSIS vs Power Query helps determine:
  • Which ETL technique is faster
  • Which is easier to maintain
  • Any limitations of each approach
Power BI Sales Analytics File :
Pizza Sales Analytics.pbix
Hope this helps! Let me know if you have any other questions.
About
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Topics
capstone-projectdata-analysisdata-visualizationpizzastoreportfoliopower-bipredictive-analyticssales-analysissales-dashboardsales-forecastingsales-trendssqlsql-analysissqlserverssisssms
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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README.md
README.md
Repository files navigation
Pizza-Shop-Sales-Analysis-SQL-Power-BI
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Key Features
  • SQL queries and SSIS packages to extract and transform data from SQL Server database.
  • Power Query in Power BI to connect to SQL Server and load data.
  • Compare results from SQL SSIS vs Power Query.
  • Power BI reports and dashboards to visualize sales trends and customer insights.
  • Insights into best selling pizzas, toppings, customer preferences and more.
Built Using
  • SQL Server - As the database to store sales data.
  • SQL Server Integration Services (SSIS) - To extract and transform data.
  • Power BI - Power Query to connect to SQL and Power BI reports for analysis.
SQL Server SSIS Queries File Contains SQL Queries and results screenshots:
Pizza Sales SQL Queries.docx
Benefits
  • Compare ETL techniques using SQL SSIS vs Power Query.
  • Understand performance and limitations of each approach.
  • Gain insights into pizza sales trends, customer preferences and more.
  • Optimize menu, ingredients and marketing based on analysis.
This dashboard in Power BI shows an overview of total sales, top pizzas sold and sales by Pizza type.
Screenshot 2024-02-03 165956Screenshot 2024-02-03 170157Screenshot 2024-02-03 170045Screenshot 2024-02-03 170024
Analysis provides insights to:
  • Improve menu options
  • Optimize ingredient stocking
  • Target marketing and promotions
Comparing SQL SSIS vs Power Query helps determine:
  • Which ETL technique is faster
  • Which is easier to maintain
  • Any limitations of each approach
Power BI Sales Analytics File :
Pizza Sales Analytics.pbix
Hope this helps! Let me know if you have any other questions.
About
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Topics
capstone-projectdata-analysisdata-visualizationpizzastoreportfoliopower-bipredictive-analyticssales-analysissales-dashboardsales-forecastingsales-trendssqlsql-analysissqlserverssisssms
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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Pizza Sales SQL Queries.docx
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README.md
README.md
Repository files navigation
Pizza-Shop-Sales-Analysis-SQL-Power-BI
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Key Features
  • SQL queries and SSIS packages to extract and transform data from SQL Server database.
  • Power Query in Power BI to connect to SQL Server and load data.
  • Compare results from SQL SSIS vs Power Query.
  • Power BI reports and dashboards to visualize sales trends and customer insights.
  • Insights into best selling pizzas, toppings, customer preferences and more.
Built Using
  • SQL Server - As the database to store sales data.
  • SQL Server Integration Services (SSIS) - To extract and transform data.
  • Power BI - Power Query to connect to SQL and Power BI reports for analysis.
SQL Server SSIS Queries File Contains SQL Queries and results screenshots:
Pizza Sales SQL Queries.docx
Benefits
  • Compare ETL techniques using SQL SSIS vs Power Query.
  • Understand performance and limitations of each approach.
  • Gain insights into pizza sales trends, customer preferences and more.
  • Optimize menu, ingredients and marketing based on analysis.
This dashboard in Power BI shows an overview of total sales, top pizzas sold and sales by Pizza type.
Screenshot 2024-02-03 165956Screenshot 2024-02-03 170157Screenshot 2024-02-03 170045Screenshot 2024-02-03 170024
Analysis provides insights to:
  • Improve menu options
  • Optimize ingredient stocking
  • Target marketing and promotions
Comparing SQL SSIS vs Power Query helps determine:
  • Which ETL technique is faster
  • Which is easier to maintain
  • Any limitations of each approach
Power BI Sales Analytics File :
Pizza Sales Analytics.pbix
Hope this helps! Let me know if you have any other questions.
About
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Topics
capstone-projectdata-analysisdata-visualizationpizzastoreportfoliopower-bipredictive-analyticssales-analysissales-dashboardsales-forecastingsales-trendssqlsql-analysissqlserverssisssms
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Pizza Sales SQL Queries.docx
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README.md
README.md
Repository files navigation
Pizza-Shop-Sales-Analysis-SQL-Power-BI
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Key Features
  • SQL queries and SSIS packages to extract and transform data from SQL Server database.
  • Power Query in Power BI to connect to SQL Server and load data.
  • Compare results from SQL SSIS vs Power Query.
  • Power BI reports and dashboards to visualize sales trends and customer insights.
  • Insights into best selling pizzas, toppings, customer preferences and more.
Built Using
  • SQL Server - As the database to store sales data.
  • SQL Server Integration Services (SSIS) - To extract and transform data.
  • Power BI - Power Query to connect to SQL and Power BI reports for analysis.
SQL Server SSIS Queries File Contains SQL Queries and results screenshots:
Pizza Sales SQL Queries.docx
Benefits
  • Compare ETL techniques using SQL SSIS vs Power Query.
  • Understand performance and limitations of each approach.
  • Gain insights into pizza sales trends, customer preferences and more.
  • Optimize menu, ingredients and marketing based on analysis.
This dashboard in Power BI shows an overview of total sales, top pizzas sold and sales by Pizza type.
Screenshot 2024-02-03 165956Screenshot 2024-02-03 170157Screenshot 2024-02-03 170045Screenshot 2024-02-03 170024
Analysis provides insights to:
  • Improve menu options
  • Optimize ingredient stocking
  • Target marketing and promotions
Comparing SQL SSIS vs Power Query helps determine:
  • Which ETL technique is faster
  • Which is easier to maintain
  • Any limitations of each approach
Power BI Sales Analytics File :
Pizza Sales Analytics.pbix
Hope this helps! Let me know if you have any other questions.
About
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Topics
capstone-projectdata-analysisdata-visualizationpizzastoreportfoliopower-bipredictive-analyticssales-analysissales-dashboardsales-forecastingsales-trendssqlsql-analysissqlserverssisssms
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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4 Commits
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NameName
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Pizza Sales Analytics.pbix
Pizza Sales Analytics.pbix
Pizza Sales SQL Queries.docx
Pizza Sales SQL Queries.docx
README.md
README.md
Repository files navigation
Pizza-Shop-Sales-Analysis-SQL-Power-BI
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Key Features
  • SQL queries and SSIS packages to extract and transform data from SQL Server database.
  • Power Query in Power BI to connect to SQL Server and load data.
  • Compare results from SQL SSIS vs Power Query.
  • Power BI reports and dashboards to visualize sales trends and customer insights.
  • Insights into best selling pizzas, toppings, customer preferences and more.
Built Using
  • SQL Server - As the database to store sales data.
  • SQL Server Integration Services (SSIS) - To extract and transform data.
  • Power BI - Power Query to connect to SQL and Power BI reports for analysis.
SQL Server SSIS Queries File Contains SQL Queries and results screenshots:
Pizza Sales SQL Queries.docx
Benefits
  • Compare ETL techniques using SQL SSIS vs Power Query.
  • Understand performance and limitations of each approach.
  • Gain insights into pizza sales trends, customer preferences and more.
  • Optimize menu, ingredients and marketing based on analysis.
This dashboard in Power BI shows an overview of total sales, top pizzas sold and sales by Pizza type.
Screenshot 2024-02-03 165956Screenshot 2024-02-03 170157Screenshot 2024-02-03 170045Screenshot 2024-02-03 170024
Analysis provides insights to:
  • Improve menu options
  • Optimize ingredient stocking
  • Target marketing and promotions
Comparing SQL SSIS vs Power Query helps determine:
  • Which ETL technique is faster
  • Which is easier to maintain
  • Any limitations of each approach
Power BI Sales Analytics File :
Pizza Sales Analytics.pbix
Hope this helps! Let me know if you have any other questions.
About
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Topics
capstone-projectdata-analysisdata-visualizationpizzastoreportfoliopower-bipredictive-analyticssales-analysissales-dashboardsales-forecastingsales-trendssqlsql-analysissqlserverssisssms
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Pizza-Shop-Sales-Analysis-SQL-Power-BI
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Key Features
  • SQL queries and SSIS packages to extract and transform data from SQL Server database.
  • Power Query in Power BI to connect to SQL Server and load data.
  • Compare results from SQL SSIS vs Power Query.
  • Power BI reports and dashboards to visualize sales trends and customer insights.
  • Insights into best selling pizzas, toppings, customer preferences and more.
Built Using
  • SQL Server - As the database to store sales data.
  • SQL Server Integration Services (SSIS) - To extract and transform data.
  • Power BI - Power Query to connect to SQL and Power BI reports for analysis.
SQL Server SSIS Queries File Contains SQL Queries and results screenshots:
Pizza Sales SQL Queries.docx
Benefits
  • Compare ETL techniques using SQL SSIS vs Power Query.
  • Understand performance and limitations of each approach.
  • Gain insights into pizza sales trends, customer preferences and more.
  • Optimize menu, ingredients and marketing based on analysis.
This dashboard in Power BI shows an overview of total sales, top pizzas sold and sales by Pizza type.
Screenshot 2024-02-03 165956Screenshot 2024-02-03 170157Screenshot 2024-02-03 170045Screenshot 2024-02-03 170024
Analysis provides insights to:
  • Improve menu options
  • Optimize ingredient stocking
  • Target marketing and promotions
Comparing SQL SSIS vs Power Query helps determine:
  • Which ETL technique is faster
  • Which is easier to maintain
  • Any limitations of each approach
Power BI Sales Analytics File :
Pizza Sales Analytics.pbix
Hope this helps! Let me know if you have any other questions.
About
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
Topics
capstone-projectdata-analysisdata-visualizationpizzastoreportfoliopower-bipredictive-analyticssales-analysissales-dashboardsales-forecastingsales-trendssqlsql-analysissqlserverssisssms
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