The QSR IT market is booming, projected to reach $18.8 billion by 2033 with a 3.1% CAGR. This report analyzes market trends, key players (Microsoft, Oracle, NCR), and driving factors like mobile ordering and data analytics. Discover how technology is transforming the quick-service restaurant industry.

Gain valuable financial information, data and news pertaining to equities, commodities, and more from LSEG's Quick News Service Data.

This case study is towards Capstone project requirement for the Google Data Analytics Professional Certificate. The author uses the data analysis process consisting of ask, prepare, process, analyze, share and act, and chooses spreadsheet and Tableau as tools to perform data processing, data analysis and data visualization.

Quick Commerce Market Outlook 2032

The global quick commerce market size was USD 150 Billion in 2024 and is likely to reach USD 750 Billion by 2033, expanding at a CAGR of

19.60% during


2025-2033. The market is propelled by the growing trend of online shopping.



Increasing consumer demand for speed and convenience is expected to propel the market during the forecast period. The latest trends in the market include the integration of advanced technologies such as AI and machine learning to optimize delivery routes and enhance operational efficiency. This shift towards technology-driven solutions has made quick commerce efficient and reliable, meeting the growing consumer expectations for instant gratification.

Growing penetration of smartphones and high-speed internet has revolutionized the quick commerce sector. These technological advancements have made it easier for consumers to place orders anytime, anywhere, driving the demand for quick commerce services. Moreover, the use of data analytics in quick commerce provides valuable insights into consumer behavior and preferences, enabling businesses to tailor their offerings and improve customer satisfaction.



Rising innovation in logistics and supply chain management has opened up new opportunities for quick commerce. The advent of autonomous delivery vehicles and drones has the potential to significantly reduce delivery times and costs. Furthermore, the use of smart lockers for secure and convenient pick-up of orders is gaining popularity. These innovations not only enhance the efficiency of quick co

Systems Of Insight Market size was valued at USD 2.68 Billion in 2023 and is projected to reach USD 10.89 Billion by 2030, growing at a CAGR of 22.2% during the forecast period 2024-2030.

Global Systems Of Insight Market Drivers

The market drivers for the Systems Of Insight Market can be influenced by various factors. These may include:

Data Explosion and Complexity: In order to extract valuable insights, enterprises are producing data at a faster, more varied, and larger volume. This has led to a demand for sophisticated systems. Businesses can better understand complicated and diverse data sets by utilizing insight systems. Demand for Real-Time Analytics: In order to make quick, well-informed decisions, businesses are looking for real-time insights more and more. Organizations may now evaluate data in real-time thanks to systems of insight, which makes it possible to respond more quickly to changes in the market, in customer behavior, and in operational problems. Digital Transformation Initiatives: Organizations must use data to make strategic decisions as a result of the continuous digital transformation taking place in many industries. Systems of insight, which offer useful insights from a variety of data sources, are essential for assisting digital projects. Integration with Machine Learning (ML) and Artificial Intelligence (AI): Adding ML and AI capabilities to insight systems improves their capacity to identify trends, patterns, and anomalies in data. More precise forecasts and prescriptive insights for improved decision-making are thus made possible as a result. Customer Experience Optimization: In order to stay competitive, businesses are concentrating on improving customer experiences. Systems of insight enable businesses to better understand the preferences, behaviors, and feedback of their customers, resulting in more tailored and effective customer interactions. Regulatory Compliance Requirements: The adoption of insight systems is influenced by regulatory compliance norms, particularly in sectors such as banking and healthcare. Organizations may handle and analyze data in compliance with security and privacy standards thanks to these technologies. Cross-Functional Collaboration Is Necessary: Systems of insight help departments within a company work together more effectively. These solutions dismantle data silos and promote cooperation for more thorough decision-making by offering a single, cross-functional view of the data. Predictive analytics: is becoming more and more important for businesses as a means of projecting future trends, predicting shifts in the market, and streamlining internal operations. Predictive analytics-enabled insight systems let businesses take proactive measures in decision-making Growth of IoT and Sensor Data: As Internet of Things (IoT) devices and sensors proliferate, enormous volumes of data are produced. By offering useful insights for enhancing operational effectiveness and decision-making, systems of insight assist businesses in deriving value from this data. Cloud Adoption: Systems of insight have become more widely used as a result of the move to cloud computing. Cloud-based solutions facilitate the deployment and management of these systems for enterprises by providing scalability, flexibility, and accessibility.

Scenario I am a junior data analyst working in the marketing analyst team at Cyclistic, a bike-share company in Chicago. The director of marketing believes the company’s future success depends on maximizing the number of annual memberships. Therefore, your team wants to understand how casual riders and annual members use Cyclistic bikes differently. From the insights taken from the data, the marketing team must be given recommendations according to the problem statement of the company. For the purpose of answering the key business questions, you will follow the steps of the data analysis process: ask, prepare, process, analyze, share, and act.

Three questions will guide the future marketing program:

1) How do annual members and casual riders use Cyclistic bikes differently? 2) Why would casual riders buy Cyclistic annual memberships? 3) How can Cyclistic use digital media to influence casual riders to become members?

I have been assigned the first question. I have to extract insights from the company’s data to analyze how annual members and casual riders use Cyclistic bikes differently.

This is a fictional case study; hence the company name being mentioned differs from the actual company to whom this data belongs. It is a public dataset that has been made available by Motive International Inc. For our fictional study for the company ‘Cyclist’, we would be using data from January 2022 to December 2022. The user trends from this period would be analyzed to answer the question that I have been assigned, “How do annual members and causal riders use Cyclistic bikes differently?”

Data Source: https://divvy-tripdata.s3.amazonaws.com/index.html Data License Agreement: https://www.divvybikes.com/data-license-agreement

The Quick-Frozen Food market has become a vital segment of the global food industry, addressing the increasing demand for convenience and quality in meal preparation. Quick-frozen foods, which include a wide variety of items such as frozen fruits, vegetables, meals, and snacks, offer a viable solution to time-strapp

The global big data market is forecasted to grow to 103 billion U.S. dollars by 2027, more than double its expected market size in 2018. With a share of 45 percent, the software segment would become the large big data market segment by 2027. What is Big data? Big data is a term that refers to the kind of data sets that are too large or too complex for traditional data processing applications. It is defined as having one or some of the following characteristics: high volume, high velocity or high variety. Fast-growing mobile data traffic, cloud computing traffic, as well as the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the increasing volume and complexity of data sets. Big data analytics Advanced analytics tools, such as predictive analytics and data mining, help to extract value from the data and generate new business insights. The global big data and business analytics market was valued at 169 billion U.S. dollars in 2018 and is expected to grow to 274 billion U.S. dollars in 2022. As of November 2018, 45 percent of professionals in the market research industry reportedly used big data analytics as a research method.

Quick Delivery Commerce Market size was valued at USD 92.88 billion in 2021 and is poised to grow from USD 106.89 billion in 2022 to USD 291.17 billion by 2030, growing at a CAGR of 13.10% in the forecast period (2023-2030).

The Individual Quick Frozen (IQF) Cheese market is experiencing a significant transformation, driven by increasing demand for convenience food products and the rising popularity of cheese as a versatile ingredient in various cuisines. IQF cheese refers to cheese that has been frozen quickly in small pieces, allowing

The Quick-melt Cheese Ingredients market has been experiencing significant growth, driven by the increasing demand for convenient and versatile cheese options across various culinary applications. Quick-melt cheese, known for its ability to melt seamlessly and retain its texture, is widely used in food service estab

Performance Analytics Market size was valued at USD 3.6 Billion in 2023 and is projected to reach USD 14.6 Billion by 2031 growing at a CAGR of 10.6% from 2024 to 2031.

Global Performance Analytics Market Dynamics

The key market dynamics that are shaping the Performance Analytics Market include:

Key Market Drivers:

Demand for Data-Driven Decision Making: The importance of data-driven decision-making processes is being recognized by organizations in all sectors of the economy. Through data-driven insights, performance analytics solutions enable businesses to make decisions that maximize productivity, profitability, and efficiency.

Digital Transformation Initiatives: The use of performance analytics solutions is being driven by the continuous digital transformation occurring across many industries. Companies are using these tools to streamline processes, improve client interactions, and maintain their competitiveness in quickly changing industries.

Key Challenges:

Scalability: Performance analytics systems must expand to accommodate growing businesses and increasing data volumes. It's a constant struggle to make sure analytics tools can manage massive amounts of data properly and efficiently without compromising performance.

Interpretability and Actionability: extracting knowledge from data is one thing, but making sure that knowledge is comprehensible and useful is quite another. Decision-makers must be able to quickly and readily understand the information presented by performance analytics systems so they can act appropriately in response to the insights.

Key Trends:

Growing Adoption of AI and Machine Learning: These two technologies were starting to be included as standard features in performance analytics products. Businesses are now able to more correctly predict future performance and make data-driven decisions because to these technologies enhanced predictive and prescriptive analytics capabilities.

Emphasis on Real-time Analytics: Real-time analytics solutions have gained popularity as a result of the increasing volume and velocity of data generated by enterprises. Companies aimed to evaluate data as it was produced in order to obtain quick insights and react quickly to shifting consumer preferences and market situations.

The size of the Quick Link market was valued at USD XXX million in 2024 and is projected to reach USD XXX million by 2033, with an expected CAGR of XX% during the forecast period.

The Quick-Frozen Prepared Foods market has emerged as a vital segment in the broader food industry, revolutionizing convenience and accessibility for consumers. Quick-frozen prepared foods, ranging from frozen entrees and snacks to desserts, cater to the increasing demand for ready-to-eat solutions that save time an

The Reddit Subreddit Dataset by Dataplex offers a comprehensive and detailed view of Reddit’s vast ecosystem, now enhanced with appended AI-generated columns that provide additional insights and categorization. This dataset includes data from over 2.1 million subreddits, making it an invaluable resource for a wide range of analytical applications, from social media analysis to market research.

Dataset Overview:

This dataset includes detailed information on subreddit activities, user interactions, post frequency, comment data, and more. The inclusion of AI-generated columns adds an extra layer of analysis, offering sentiment analysis, topic categorization, and predictive insights that help users better understand the dynamics of each subreddit.

2.1 Million Subreddits with Enhanced AI Insights: The dataset covers over 2.1 million subreddits and now includes AI-enhanced columns that provide: - Sentiment Analysis: AI-driven sentiment scores for posts and comments, allowing users to gauge community mood and reactions. - Topic Categorization: Automated categorization of subreddit content into relevant topics, making it easier to filter and analyze specific types of discussions. - Predictive Insights: AI models that predict trends, content virality, and user engagement, helping users anticipate future developments within subreddits.

Sourced Directly from Reddit:

All social media data in this dataset is sourced directly from Reddit, ensuring accuracy and authenticity. The dataset is updated regularly, reflecting the latest trends and user interactions on the platform. This ensures that users have access to the most current and relevant data for their analyses.

Key Features:

• Subreddit Metrics: Detailed data on subreddit activity, including the number of posts, comments, votes, and user participation.
• User Engagement: Insights into how users interact with content, including comment threads, upvotes/downvotes, and participation rates.
• Trending Topics: Track emerging trends and viral content across the platform, helping you stay ahead of the curve in understanding social media dynamics.
• AI-Enhanced Analysis: Utilize AI-generated columns for sentiment analysis, topic categorization, and predictive insights, providing a deeper understanding of the data.

Use Cases:

• Social Media Analysis: Researchers and analysts can use this dataset to study online behavior, track the spread of information, and understand how content resonates with different audiences.
• Market Research: Marketers can leverage the dataset to identify target audiences, understand consumer preferences, and tailor campaigns to specific communities.
• Content Strategy: Content creators and strategists can use insights from the dataset to craft content that aligns with trending topics and user interests, maximizing engagement.
• Academic Research: Academics can explore the dynamics of online communities, studying everything from the spread of misinformation to the formation of online subcultures.

Data Quality and Reliability:

The Reddit Subreddit Dataset emphasizes data quality and reliability. Each record is carefully compiled from Reddit’s vast database, ensuring that the information is both accurate and up-to-date. The AI-generated columns further enhance the dataset's value, providing automated insights that help users quickly identify key trends and sentiments.

Integration and Usability:

The dataset is provided in a format that is compatible with most data analysis tools and platforms, making it easy to integrate into existing workflows. Users can quickly import, analyze, and utilize the data for various applications, from market research to academic studies.

User-Friendly Structure and Metadata:

The data is organized for easy navigation and analysis, with metadata files included to help users identify relevant subreddits and data points. The AI-enhanced columns are clearly labeled and structured, allowing users to efficiently incorporate these insights into their analyses.

Ideal For:

• Data Analysts: Conduct in-depth analyses of subreddit trends, user engagement, and content virality. The dataset’s extensive coverage and AI-enhanced insights make it an invaluable tool for data-driven research.
• Marketers: Use the dataset to better understand your target audience, tailor campaigns to specific interests, and track the effectiveness of marketing efforts across Reddit.
• Researchers: Explore the social dynamics of online communities, analyze the spread of ideas and information, and study the impact of digital media on public discourse, all while leveraging AI-generated insights.

This dataset is an essential resource for anyone looking to understand the intricacies of Reddit's vast ecosystem, offering the data and AI-enhanced insights needed to drive informed decisions and strategies across various fields. Whether you’re tracking emerging trends, analyzing user behavior, or conduc...

The Quick Wash Dishwasher market has emerged as a transformative segment within the home appliance industry, catering to the growing demand for convenience and efficiency in kitchen chores. Quick wash dishwashers, designed to deliver rapid cleaning cycles without compromising cleanliness, have seen a significant upt

The Mobile Quick Charge market is rapidly evolving, driven by the increasing reliance on smartphones and portable devices in our daily lives. As consumers demand faster charging solutions to keep up with their busy schedules, manufacturers are responding with innovative technologies that significantly reduce chargin

The Individual Quick Freeze (IQF) fruit market has witnessed significant evolution over the past few years, driven by the growing demand for convenience foods and an increasing focus on maintaining nutritional quality. IQF technology enables fruits to be frozen individually, ensuring they retain their flavor, textur

ExactOne delivers unparalleled consumer transaction insights to help investors and corporate clients uncover market opportunities, analyze trends, and drive better decisions.

Dataset Highlights - Source: Debit and credit card transactions from 600K+ active users and 2M accounts connected via Open Banking. Scale: Covers 250M+ annual transactions, mapped to 1,800+ merchants and 330+ tickers. Historical Depth: Over 6 years of transaction data. Flexibility: Analyse transactions by merchant/ticker, category/industry, or timeframe (daily, weekly, monthly, or quarterly).

ExactOne data offers visibility into key consumer industries, including: Airlines - Regional / Budget Airlines - Cargo Airlines - Full Service Autos - OEMs Communication Services - Cable & Satellite Communication Services - Integrated Telecommunications Communication Services - Wireless Telecom Consumer - Services Consumer - Health & Fitness Consumer Staples - Household Supplies Energy - Utilities Energy - Integrated Oil & Gas Financial Services - Insurance Grocers - Traditional Hotels - C-corp Industrial - Tools And Hardware Internet - E-commerce Internet - B2B Services Internet - Ride Hailing & Delivery Leisure - Online Gambling Media - Digital Subscription Restaurants - Quick Service Restaurants - Fast Casual Restaurants - Pubs Restaurants - Specialty Retail - Softlines Retail - Mass Merchants Retail - European Luxury Retail - Specialty Retail - Sports & Athletics Retail - Footwear Retail - Dept Stores Retail - Luxury Retail - Convenience Stores Retail - Hardlines Technology - Enterprise Software Technology - Electronics & Appliances Technology - Computer Hardware Utilities - Water Utilities

Use Cases

For Private Equity & Venture Capital Firms: - Deal Sourcing: Identify high-growth opportunities. - Due Diligence: Leverage transaction data to evaluate investment potential. - Portfolio Monitoring: Track performance post-investment with real-time data.

For Consumer Insights & Strategy Teams: - Market Dynamics: Compare sales trends, average transaction size, and customer loyalty. - Competitive Analysis: Benchmark market share and identify emerging competitors. - E-commerce vs. Brick & Mortar Trends: Assess channel performance and strategic opportunities. - Demographic & Geographic Insights: Uncover growth drivers by demo and geo segments.

For Investor Relations Teams: - Shareholder Insights: Monitor brand performance relative to competitors. - Real-Time Intelligence: Analyse sales and market dynamics for public and private companies. - M&A Opportunities: Evaluate market share and growth potential for strategic investments.

Key Benefits of ExactOne - Understand Market Share: Benchmark against competitors and uncover emerging players. - Analyse Customer Loyalty: Evaluate repeat purchase behavior and retention rates. - Track Growth Trends: Identify key drivers of sales by geography, demographic, and channel. - Granular Insights: Drill into transaction-level data or aggregated summaries for in-depth analysis.

With ExactOne, investors and corporate leaders gain actionable, real-time insights into consumer behaviour and market dynamics, enabling smarter decisions and sustained growth.

The Google Reviews & Ratings Dataset provides businesses with structured insights into customer sentiment, satisfaction, and trends based on reviews from Google. Unlike broad review datasets, this product is location-specific—businesses provide the locations they want to track, and we retrieve as much historical data as possible, with daily updates moving forward.

This dataset enables businesses to monitor brand reputation, analyze consumer feedback, and enhance decision-making with real-world insights. For deeper analysis, optional AI-driven sentiment analysis and review summaries are available on a weekly, monthly, or yearly basis.

Dataset Highlights

• Location-Specific Reviews – Reviews and ratings for the locations you provide.
• Daily Updates – New reviews and rating changes updated automatically.
• Historical Data Access – Retrieve past reviews where available.
• AI Sentiment Analysis (Optional) – Summarized insights by week, month, or year.
• Competitive Benchmarking – Compare performance across selected locations.

Use Cases

• Franchise & Retail Chains – Monitor brand reputation and performance across locations.
• Hospitality & Restaurants – Track guest sentiment and service trends.
• Healthcare & Medical Facilities – Understand patient feedback for specific locations.
• Real Estate & Property Management – Analyze tenant and customer experiences through reviews.
• Market Research & Consumer Insights – Identify trends and analyze feedback patterns across industries.

Data Updates & Delivery

• Update Frequency: Daily
• Data Format: CSV for easy integration
• Delivery: Secure file transfer (SFTP or cloud storage)

Data Fields Include:

• Business Name
• Location Details
• Star Ratings
• Review Text
• Timestamps
• Reviewer Metadata

Optional Add-Ons:

• AI Sentiment Analysis – Aggregate trends by week, month, or year.
• Custom Location Tracking – Tailor the dataset to fit your specific business needs.

Ideal for

• Marketing Teams – Leverage real-world consumer feedback to optimize brand strategy.
• Business Analysts – Use structured review data to track customer sentiment over time.
• Operations & Customer Experience Teams – Identify service issues and opportunities for improvement.
• Competitive Intelligence – Compare locations and benchmark against industry competitors.

Why Choose This Dataset?

• Accurate & Up-to-Date – Daily updates ensure fresh, reliable data.
• Scalable & Customizable – Track only the locations that matter to you.
• Actionable Insights – AI-driven summaries for quick decision-making.
• Easy Integration – Delivered in a structured format for seamless analysis.

By leveraging Google Reviews & Ratings Data, businesses can gain valuable insights into customer sentiment, enhance reputation management, and stay ahead of the competition.