****Attribute information:****

Row ID: A unique identifier for each row in the table Order ID: The identifier for each sales order Order Date: The date the order was placed Ship Date: The date the order was shipped Delivery Duration: The amount of time it took to deliver the order Ship Mode: The shipping method used for the order Customer ID: The identifier for the customer who placed the order Customer Name: The name of the customer who placed the order Country: The customer's country City: The customer's city State: The customer's state Postal Code: The customer's postal code Region: The customer's region Product ID: The identifier for the product that was ordered Category: The category of the product that was ordered (e.g., furniture, office supplies, technology) Sub-Category - This attribute likely refers to a subcategory within a larger product category (e.g., Tables within Furniture). (Bookcases - Chairs - Labels - Tables - Storage - Furnishings - Art - Phones - Binders - Appliances - Paper - Others). Product Name - This attribute specifies the name of the product sold. (Bush Somerset Collection Bookcase - Hon Deluxe Fabric Upholstered Stacking Chairs, Rounded Back - Self-Adhesive Address Labels for Typewriters by Universal - Bretford CP4500 Series Slim Rectangular Table - Others).

Sales - This attribute shows the total sales amount for each product. Values are listed in currency format Quantity - This attribute specifies the number of units sold for each product. Integer values. Discount - This attribute indicates the discount offered on the product. Discount Value - This attribute shows the total discount amount applied to the product. Profit - This attribute shows the profit earned on the sale of each product. COGS - This attribute likely refers to each product's Cost of Goods Sold. COGS = Sales - Profit

This is a realistic and structured pizza sales dataset covering the time span from **2024 to 2025. ** Whether you're a beginner in data science, a student working on a machine learning project, or an experienced analyst looking to test out time series forecasting and dashboard building, this dataset is for you.

📁 What’s Inside? The dataset contains rich details from a pizza business including:

✅ Order Dates & Times ✅ Pizza Names & Categories (Veg, Non-Veg, Classic, Gourmet, etc.) ✅ Sizes (Small, Medium, Large, XL) ✅ Prices ✅ Order Quantities ✅ Customer Preferences & Trends

It is neatly organized in Excel format and easy to use with tools like Python (Pandas), Power BI, Excel, or Tableau.

💡** Why Use This Dataset?** This dataset is ideal for:

📈 Sales Analysis & Reporting 🧠 Machine Learning Models (demand forecasting, recommendations) 📅 Time Series Forecasting 📊 Data Visualization Projects 🍽️ Customer Behavior Analysis 🛒 Market Basket Analysis 📦 Inventory Management Simulations

🧠 Perfect For: Data Science Beginners & Learners BI Developers & Dashboard Designers MBA Students (Marketing, Retail, Operations) Hackathons & Case Study Competitions

pizza, sales data, excel dataset, retail analysis, data visualization, business intelligence, forecasting, time series, customer insights, machine learning, pandas, beginner friendly

The report offers Business Data Visualization Software Market Dynamics, Comprises Industry development drivers, challenges, opportunities, threats and limitations. A report also incorporates Cost Trend of products, Mergers & Acquisitions, Expansion, Crucial Suppliers of products, Concentration Rate of Steel Coupling Economy. Global Business Data Visualization Software Market Research Report covers Market Effect Factors investigation chiefly included Technology Progress, Consumer Requires Trend, External Environmental Change.

This fictional sales dataset was created using a R code for the purpose of visualizing trends in customer demographics, product performance, and sales over time. A link to my Github repository containing all the codes used in generating the data frame and all the preceding processes can be found here

The global Sales Mobile BI market is experiencing robust growth, driven by the increasing need for real-time sales data access and analysis on mobile devices. The market's expansion is fueled by several key factors, including the widespread adoption of smartphones and tablets, the rising demand for improved sales force efficiency and productivity, and the growing need for better decision-making based on immediate sales insights. Businesses across various sectors are leveraging mobile BI solutions to empower their sales teams, track key performance indicators (KPIs) in real-time, and respond swiftly to changing market conditions. This allows for more agile sales strategies, quicker identification of sales bottlenecks, and enhanced customer relationship management (CRM) capabilities. The market is witnessing innovation in areas like advanced analytics, predictive modeling, and integration with existing CRM systems, further enhancing its appeal. While initial investment costs and data security concerns might pose some challenges, the overall market outlook remains positive, driven by consistent technological advancements and the ever-increasing reliance on data-driven decision-making in sales operations. The competitive landscape is marked by a mix of established players and emerging vendors. Major companies such as IBM, SAP, Microsoft, and Oracle are leveraging their existing enterprise software portfolios to offer comprehensive Mobile BI solutions. Specialized vendors like Tableau and Qlik are focusing on user-friendly interfaces and advanced analytics capabilities to gain market share. The market is expected to see continued consolidation as larger companies acquire smaller players to expand their product offerings and geographical reach. Future growth will likely depend on the seamless integration of mobile BI with other enterprise systems, the development of more intuitive user interfaces tailored for mobile devices, and addressing security and privacy concerns surrounding sensitive sales data. The overall market projection suggests a sustained period of growth, driven by the undeniable benefits of mobile BI in improving sales performance and operational efficiency.

Passenger EV sales are rising quickly, but trail two and three wheel EV sales.

The Data Visualization Market report segments the industry into Organizational Department (Executive Management, Marketing, Operations, Finance, Sales, Other Organizational Departments), Deployment Mode (On-premise, Cloud/On-demand), End User (BFSI, IT and Telecommunication, Retail/E-commerce, Education, Manufacturing, Government, Other End Users), and Geography (North America, Europe, Asia-Pacific, and more).

Dataset

This dataset was created by Muhammad Hassan

Contents

The market for funnel visualization tools is experiencing robust growth, driven by the increasing need for businesses to understand and optimize their customer journeys. The demand for data-driven decision-making, coupled with the rising adoption of marketing automation and sales methodologies, is fueling this expansion. The market is segmented by various factors, including tool functionality (basic to advanced analytics), pricing models (subscription-based vs. one-time purchase), and target user (marketing professionals, sales teams, product managers). Key players like Funnelytics, Google, MindMeister, and Lucidchart are competing fiercely, each offering unique features and integrations. The market's growth is expected to continue at a healthy Compound Annual Growth Rate (CAGR) of 15%, reaching an estimated market size of $2.5 billion by 2033, up from an estimated $1 billion in 2025. This growth reflects a shift towards visual, interactive tools that allow for more intuitive understanding and improvement of complex sales and marketing funnels.
The competitive landscape is marked by both established players with extensive feature sets and emerging startups focusing on niche functionalities. This leads to a diverse range of options available to businesses, enabling them to choose tools tailored to their specific needs and budgets. Future trends indicate a move towards AI-powered analytics within these tools, allowing for more predictive insights and automated optimizations. Integration with existing CRM and marketing automation platforms is another significant trend, ensuring seamless data flow and improved efficiency. However, factors such as the initial cost of implementation and the need for specialized training can act as restraints to market penetration, particularly among smaller businesses. Despite these limitations, the long-term outlook for the funnel visualization tools market remains positive, propelled by the growing importance of data-driven strategies and the continuous evolution of marketing and sales techniques.

Global Data Visualization Tools market size is expected to reach $15.75 billion by 2029 at 13.4%, big data’s role in fueling the growth of the data visualization tools market

Electric two-wheelers are predicted to dominate sales over their internal combustion counterparts.

Report of Data Visualization Tools and Software Market is currently supplying a comprehensive analysis of many things which are liable for economy growth and factors which could play an important part in the increase of the marketplace in the prediction period. The record of Data Visualization Tools and Software Industry is providing the thorough study on the grounds of market revenue discuss production and price happened. The report also provides the overview of the segmentation on the basis of area, contemplating the particulars of earnings and sales pertaining to marketplace.

1) Data Introduction • The Power BI Sample Data is a financial sample dataset provided for Power BI practice and data visualization exercises that includes a variety of financial metrics and transaction information, including sales, profits, and expenses.

2) Data Utilization (1) Power BI Sample Data has characteristics that: • This dataset consists of numerical and categorical variables such as transaction date, region, product category, sales, profit, and cost, optimized for aggregation, analysis, and visualization. (2) Power BI Sample Data can be used to: • Revenue and Revenue Analysis: Analyze sales and profit data by region, product, and period to understand business performance and trends. • Power BI Dashboard Practice: Utilize a variety of financial metrics and transaction data to design and practice dashboards, reports, visualization charts, and more directly at Power BI.

Vrinda Store: Interactive Ms Excel dashboardVrinda Store: Interactive Ms Excel dashboard Feb 2024 - Mar 2024Feb 2024 - Mar 2024 The owner of Vrinda store wants to create an annual sales report for 2022. So that their employees can understand their customers and grow more sales further. Questions asked by Owner of Vrinda store are as follows:- 1) Compare the sales and orders using single chart. 2) Which month got the highest sales and orders? 3) Who purchased more - women per men in 2022? 4) What are different order status in 2022?

And some other questions related to business. The owner of Vrinda store wanted a visual story of their data. Which can depict all the real time progress and sales insight of the store. This project is a Ms Excel dashboard which presents an interactive visual story to help the Owner and employees in increasing their sales. Task performed : Data cleaning, Data processing, Data analysis, Data visualization, Report. Tool used : Ms Excel The owner of Vrinda store wants to create an annual sales report for 2022. So that their employees can understand their customers and grow more sales further. Questions asked by Owner of Vrinda store are as follows:- 1) Compare the sales and orders using single chart. 2) Which month got the highest sales and orders? 3) Who purchased more - women per men in 2022? 4) What are different order status in 2022? And some other questions related to business. The owner of Vrinda store wanted a visual story of their data. Which can depict all the real time progress and sales insight of the store. This project is a Ms Excel dashboard which presents an interactive visual story to help the Owner and employees in increasing their sales. Task performed : Data cleaning, Data processing, Data analysis, Data visualization, Report. Tool used : Ms Excel Skills: Data Analysis · Data Analytics · ms excel · Pivot Tables

Overseas sales accounted for more than 10% of BYD's sales portfolio in 2024.

The global sales mapping system market size was valued at USD 1.5 billion in 2025 and is projected to expand at a CAGR of 12.5% from 2025 to 2033. The market growth is primarily driven by the increasing adoption of customer relationship management (CRM) systems, the need for enhanced sales productivity, and the growing popularity of data visualization tools. Sales mapping systems provide businesses with a visual representation of their sales territories, customer locations, and other relevant data, enabling them to optimize their sales strategies and improve decision-making. North America held the largest market share in 2025, accounting for over 35% of the global revenue. The region's dominance is attributed to the presence of a large number of technology companies and the high adoption rate of CRM systems. However, the Asia Pacific region is expected to witness the fastest growth over the forecast period, owing to the increasing investment in digital transformation and the growing number of small and medium-sized enterprises (SMEs) in the region. Key players in the market include Workbooks, CallProof, Akero, LeadSquared, Map My Customers, Mapline, eSpatial, ZooM, Badger Maps, Wingman, MapBusinessOnline.com, Outfield, Bid Track Sell, VeloxyIO, Maptive, Xactly Corp, Geographic Enterprises, Caliper Corporation, Cozmix, and EasyTerritory.

Report of Designing Data Visualization Services Market is currently supplying a comprehensive analysis of many things which are liable for economy growth and factors which could play an important part in the increase of the marketplace in the prediction period. The record of Designing Data Visualization Services Industry is providing the thorough study on the grounds of market revenue discuss production and price happened. The report also provides the overview of the segmentation on the basis of area, contemplating the particulars of earnings and sales pertaining to marketplace.

VinFast's reliance on sales to related parties like Xanh SM Taxi has been significant but is gradually falling.

Data Intelligence Solutions for Sales Market Outlook

The global market size for Data Intelligence Solutions for Sales was valued at approximately USD 4.5 billion in 2023 and is projected to reach around USD 11.3 billion by 2032, growing at a CAGR of 10.8% during the forecast period. This substantial growth is driven by the increasing adoption of data-driven decision-making processes across various industries to enhance sales strategies. As businesses increasingly focus on leveraging data to gain competitive advantages, the demand for advanced data intelligence solutions is expected to rise significantly.

One of the primary growth factors for the Data Intelligence Solutions for Sales market is the rapid digital transformation across industries. Companies are now more inclined to adopt digital tools and technologies that can provide deep insights into consumer behavior, market trends, and sales performance. This transition is fueled by the need for real-time data analytics to make informed decisions, optimize sales processes, and ultimately increase revenue. Furthermore, the integration of artificial intelligence (AI) and machine learning (ML) technologies into data intelligence solutions is providing enhanced predictive analytics capabilities, enabling businesses to forecast sales trends more accurately and efficiently.

Another significant growth driver is the increasing focus on personalized customer experiences. Modern consumers expect highly personalized interactions with brands, which necessitates the use of sophisticated data intelligence tools to analyze customer data and tailor marketing and sales strategies accordingly. By leveraging data intelligence solutions, companies can segment their customer base more effectively, identify individual preferences, and deliver customized offers, thereby improving customer satisfaction and loyalty. This trend is particularly evident in sectors such as retail, BFSI, and healthcare, where customer-centric approaches are crucial for success.

The growing importance of regulatory compliance and data security also plays a vital role in the expansion of the Data Intelligence Solutions for Sales market. With increasing concerns over data privacy and the implementation of stringent regulations such as GDPR and CCPA, companies are investing heavily in robust data management solutions to ensure compliance and protect sensitive information. Data intelligence solutions help organizations maintain data integrity, ensure regulatory adherence, and mitigate risks associated with data breaches, thereby fostering trust among customers and stakeholders.

Regionally, North America holds a dominant position in the Data Intelligence Solutions for Sales market, attributed to the presence of leading technology companies and early adoption of advanced data analytics solutions. The region's well-established IT infrastructure, coupled with high investments in research and development, further strengthens its market position. Europe also represents a significant market, driven by increasing regulatory requirements and a growing emphasis on data protection. Meanwhile, Asia Pacific is expected to witness the highest growth rate, fueled by rapid economic development, digitalization initiatives, and a burgeoning e-commerce sector in countries such as China and India.

Component Analysis

The Data Intelligence Solutions for Sales market is broadly segmented into Software and Services. The software segment encompasses various software tools and platforms designed to collect, process, analyze, and visualize sales data. These tools enable organizations to derive actionable insights from vast amounts of data, supporting data-driven decision-making processes. The software segment is anticipated to witness significant growth during the forecast period, driven by the increasing need for advanced analytics and real-time data processing capabilities. Additionally, the integration of AI and ML technologies into software solutions is enhancing their predictive and prescriptive analytics capabilities, further boosting market demand.

Within the software segment, various sub-categories are gaining traction, including customer relationship management (CRM) software, sales analytics software, and data visualization tools. CRM software helps businesses manage and analyze customer interactions and data throughout the customer lifecycle, aiming to improve customer relationships and drive sales growth. Sales analytics software provides detailed insights into sales performance, helping organizations identify trends, measure effectiveness, and optimize sales strategies. Da

Dataset

This dataset was created by shubham kumar

Contents