Web design service companies have experienced significant growth over the past few years, driven by the expanding use of the Internet. As online operations have become more widespread, businesses and consumers have increasingly recognized the importance of maintaining an online presence, leading to robust demand for web design services and boosting the industry’s profit. The rise in broadband connections and online business activities further spotlight this trend, making web design a vital component of modern commerce and communication. This solid foundation suggests the industry has been thriving despite facing some economic turbulence related to global events and shifting financial climates. Over the past few years, web design companies have navigated a dynamic landscape marked by both opportunities and challenges. Strong economic conditions have typically favored the industry, with rising disposable incomes and low unemployment rates encouraging both consumers and businesses to invest in professional web design. Despite this, the sector also faced hurdles such as high inflation, which made cost increases necessary and pushed some customers towards cheaper substitutes such as website templates and in-house production, causing a slump in revenue in 2022. Despite these obstacles, the industry has demonstrated resilience against rising interest rates and economic uncertainties by focusing on enhancing user experience and accessibility. Overall, revenue for web design service companies is anticipated to rise at a CAGR of 2.2% during the current period, reaching $43.5 billion in 2024. This includes a 2.2% jump in revenue in that year. Looking ahead, web design companies will continue to do well, as the strong performance of the US economy will likely support ongoing demand for web design services, bolstered by higher consumer spending and increased corporate profit. On top of this, government investment, especially at the state and local levels, will provide further revenue streams as public agencies seek to upgrade their web presence. Innovation remains key, with a particular emphasis on designing for mobile devices as more activities shift to on-the-go platforms. Companies that can effectively adapt to these trends and invest in new technologies will likely capture a significant market share, fostering an environment where entry remains feasible yet competitive. Overall, revenue for web design service providers is forecast to swell at a CAGR of 1.9% during the outlook period, reaching $47.7 billion in 2029.

🇺🇸 미국

The global web design services market is experiencing tremendous growth, with a projected market size of USD 52.4 billion by the end of 2033. Driven by the rise of e-commerce and digital transformation, the market is expanding at a rapid CAGR of 12.2% from 2025 to 2033. North America and Asia Pacific are the leading regions, accounting for a significant share of the market. The growing adoption of mobile-first web design and the increasing demand for personalized user experiences are driving the demand for web design services. Market players such as Seller's Bay, WebFX, and Appnovation are key participants in the industry. These companies offer a range of web design services, including website design, website hosting, search engine optimization, and domain sales. The market is segmented based on application, with enterprise and private segments being the largest contributors. In terms of types, website design holds the dominant share, followed by website hosting. However, restraints such as security concerns, high development costs, and competition from open-source platforms may pose challenges to the market's growth.

Contains view count data for the top 20 pages each day on the Somerville MA city website dating back to 2020. Data is used in the City's dashboard which can be found at https://www.somervilledata.farm/.

The global marketing data analysis software market is projected to grow from XXX million in 2023 to XXX million by 2033, with a CAGR of XX% during the forecast period. The growth of the market is attributed to the increasing adoption of data-driven marketing strategies by businesses to improve their customer engagement and sales performance. Additionally, the growing popularity of cloud-based software solutions and the availability of advanced analytical tools are driving the market growth. The market is segmented based on application, type, company, and region. The retail and e-commerce segment holds the largest market share due to the high demand for data analysis in the industry. The website analysis software segment is expected to witness significant growth during the forecast period due to the increasing need for businesses to track and analyze website traffic and behavior. The North American region dominates the market, followed by Europe and Asia Pacific. The key players in the market are HubSpot, Semrush, Looker Data Sciences (Google), Insider, LeadsRx, SharpSpring, OWOX BI, and Whatagraph BV.

Crunchbase dataset to map your business ecosystem, make strategic decisions, and gather information on private and public companies. Common use cases include identifying investment opportunities, tracking company growth, and analyzing industry trends.

Use our Crunchbase Companies Information dataset to gain detailed insights into global startups and established companies across various industries. This dataset provides valuable company profiles, funding details, key executives, industry trends, and business performance, tailored for venture capitalists, market analysts, business development teams, and researchers.

By leveraging the Crunchbase Companies dataset, users can discover emerging startups, evaluate investment opportunities, track market growth, and perform competitive analysis. Whether you're seeking to enhance due diligence processes, identify new business prospects, or explore industry developments, this dataset empowers you to make data-driven decisions with confidence. Gain a deeper understanding of the business landscape and stay ahead in the competitive market by utilizing this essential dataset.

Dataset Features

Below is a breakdown of key dataset columns:
- name: The name of the company.
- url: Website or Crunchbase link for the company.
- id: Unique identifier for the company.
- cb_rank: Crunchbase ranking based on relevance and popularity.
- region: Geographic region where the company operates.
- about: Brief description of the company.
- industries: List of industries the company belongs to (e.g., photography, events, professional services).
- operating_status: Whether the company is active or inactive.
- company_type: Classification (e.g., for-profit, nonprofit).
- social_media_links: URLs to the company’s social media profiles.
- founded_date: Year or exact date when the company was founded.
- num_employees: Number of employees in the company.
- country_code: Country where the company is based.
- website: Official company website.
- contact_email: Contact email for the company.
- contact_phone: Contact phone number for the company.
- featured_list: Lists the company has been featured.
- full_description: Extended description of the company’s services or products.
- type: Type of organization (company, startup, etc.).
- uuid: Unique identifier for database tracking.
- active_tech_count: Number of technologies actively used by the company.
- builtwith_num_technologies_used: Number of technologies detected using BuiltWith.
- builtwith_tech: List of technologies used.
- ipo_status: Whether the company is public or private.
- similar_companies: URL of other companies similar to this one.
- image: Link to the company’s image or logo.
- monthly_visits: Estimated monthly web traffic.
- semrush_visits_latest_month: Website visits in the latest month according to SEMrush.
- semrush_last_updated: Last updated date for SEMrush traffic data.
- monthly_visits_growth: Change in web traffic over time.
- semrush_visits_mom_pct: Month-over-month percentage change in visits.
- num_contacts: Number of available contacts for the company.
- num_contacts_linkedin: Number of LinkedIn contacts.
- num_employee_profiles: Number of employee profiles available.
- total_active_products: Number of active products/services offered by the company.
- num_news: Number of news articles about the company.
- funding_rounds: Number of funding rounds the company has gone through.
- Bombora_last_updated: Bombora last updated date on website.
- num_investors: Number of investors associated with the company.
- legal_name: Official legal name of the company.
- num_event_appearances: Number of events the company has appeared in.
- num_acquisitions: Number of acquisitions made by the company.
- num_investments: Number of investments made by the company.
- num_advisor_positions: Number of advisor positions in the company.
- num_exits: Number of times the company has exited an investment.
- num_investments_lead: Number of times the company has led an investment round.
- num_sub_organizations: Number of sub-organizations under the company.
- num_alumni: Number of notable alumni from the company.
- Num_diversity_spotlight_investments: Number of diversity-focused investments.
- num_founder_alumni: Number of company founders who are alumni of a certain institution.
- num_funds: Number of investment funds the company has created.
- stock_symbol: Stock ticker symbol (if public).
- location: City and country where the company is headquartered.
- address: Full business address.
- contacts: List of business contacts.
- current_employees: Number of current employees.
- **semrush_loc

The Enterprise Website Construction market is experiencing robust growth, driven by the increasing digital transformation initiatives across various industries. Businesses are recognizing the critical role of a professional, high-performing website in enhancing brand image, driving sales, and improving customer engagement. This demand is fueled by the need for secure, scalable, and feature-rich platforms capable of handling complex business requirements, including e-commerce functionality, content management systems (CMS), and robust analytics dashboards. The market's growth is further accelerated by advancements in website technologies like Artificial Intelligence (AI) for personalized user experiences, improved SEO optimization tools, and the rise of headless CMS architectures offering greater flexibility and scalability. While specific market size figures are unavailable, based on industry trends and the presence of major players like Equinix and Digital Realty, a reasonable estimation would place the 2025 market size around $15 billion, with a Compound Annual Growth Rate (CAGR) of 12% projected through 2033. This substantial growth reflects a market ripe with opportunity for both established players and emerging companies. Several factors contribute to this positive outlook. The increasing adoption of cloud-based solutions simplifies website deployment and maintenance, attracting smaller businesses. Simultaneously, large enterprises require sophisticated solutions to handle their complex data and customer interactions. However, the market also faces restraints, including the high initial investment costs for enterprise-grade solutions, the need for ongoing maintenance and updates, and the potential for security vulnerabilities. Competition is fierce, with established players and smaller, specialized firms vying for market share. Geographic expansion, particularly into developing economies with growing digital adoption rates, presents a significant opportunity for future growth. Regional disparities exist, with North America and Europe currently dominating the market, followed by the Asia-Pacific region showing strong growth potential. Successful players will be those that can effectively address security concerns, offer innovative solutions, and provide comprehensive support services.

This group includes the provision of infrastructure for hosting, data processing services and related activities, as well as search facilities and other portals for the Internet.

Comparison of Seconds to Output 500 Tokens, including reasoning model 'thinking' time; Lower is better by Model

This dataset contains news headlines relevant to key forex pairs: AUDUSD, EURCHF, EURUSD, GBPUSD, and USDJPY. The data was extracted from reputable platforms Forex Live and FXstreet over a period of 86 days, from January to May 2023. The dataset comprises 2,291 unique news headlines. Each headline includes an associated forex pair, timestamp, source, author, URL, and the corresponding article text. Data was collected using web scraping techniques executed via a custom service on a virtual machine. This service periodically retrieves the latest news for a specified forex pair (ticker) from each platform, parsing all available information. The collected data is then processed to extract details such as the article's timestamp, author, and URL. The URL is further used to retrieve the full text of each article. This data acquisition process repeats approximately every 15 minutes.

To ensure the reliability of the dataset, we manually annotated each headline for sentiment. Instead of solely focusing on the textual content, we ascertained sentiment based on the potential short-term impact of the headline on its corresponding forex pair. This method recognizes the currency market's acute sensitivity to economic news, which significantly influences many trading strategies. As such, this dataset could serve as an invaluable resource for fine-tuning sentiment analysis models in the financial realm.

We used three categories for annotation: 'positive', 'negative', and 'neutral', which correspond to bullish, bearish, and hold sentiments, respectively, for the forex pair linked to each headline. The following Table provides examples of annotated headlines along with brief explanations of the assigned sentiment.

Examples of Annotated Headlines


    Forex Pair
    Headline
    Sentiment
    Explanation




    GBPUSD 
    Diminishing bets for a move to 12400 
    Neutral
    Lack of strong sentiment in either direction


    GBPUSD 
    No reasons to dislike Cable in the very near term as long as the Dollar momentum remains soft 
    Positive
    Positive sentiment towards GBPUSD (Cable) in the near term


    GBPUSD 
    When are the UK jobs and how could they affect GBPUSD 
    Neutral
    Poses a question and does not express a clear sentiment


    JPYUSD
    Appropriate to continue monetary easing to achieve 2% inflation target with wage growth 
    Positive
    Monetary easing from Bank of Japan (BoJ) could lead to a weaker JPY in the short term due to increased money supply


    USDJPY
    Dollar rebounds despite US data. Yen gains amid lower yields 
    Neutral
    Since both the USD and JPY are gaining, the effects on the USDJPY forex pair might offset each other


    USDJPY
    USDJPY to reach 124 by Q4 as the likelihood of a BoJ policy shift should accelerate Yen gains 
    Negative
    USDJPY is expected to reach a lower value, with the USD losing value against the JPY


    AUDUSD

    <p>RBA Governor Lowe’s Testimony High inflation is damaging and corrosive </p>

    Positive
    Reserve Bank of Australia (RBA) expresses concerns about inflation. Typically, central banks combat high inflation with higher interest rates, which could strengthen AUD.

Moreover, the dataset includes two columns with the predicted sentiment class and score as predicted by the FinBERT model. Specifically, the FinBERT model outputs a set of probabilities for each sentiment class (positive, negative, and neutral), representing the model's confidence in associating the input headline with each sentiment category. These probabilities are used to determine the predicted class and a sentiment score for each headline. The sentiment score is computed by subtracting the negative class probability from the positive one.

Get key insights from Market Research Intellect's Website Maintenance Services Market Report, valued at USD 10.5 billion in 2024, and forecast to grow to USD 18.2 billion by 2033, with a CAGR of 7.5% (2026-2033).

Repository for Thesis JSBA/Group 2 Binus University

Ongoing analytics for the main City of Las Vegas web site. Dataset meets the requirements for the US Cities Open Data Census.

Here is the updated list with web_events.csv included:

1. Orders Dataset:

   • Contains details of customer orders, including order dates, total order amounts (in USD), and associated customer IDs.
   • Helps analyze revenue trends, customer purchasing behavior, and seasonal patterns.

2. Accounts Dataset:

   • Represents customer account information such as account IDs, names, and sales representative assignments.
   • Useful for understanding customer demographics and their engagement with the company.

3. Regions Dataset:

   • Defines geographical regions managed by sales representatives, including region names and IDs.
   • Enables regional sales performance analysis and comparative insights across regions.

4. Sales Representatives Dataset:

   • Includes data on sales representatives, their IDs, names, and the regions they serve.
   • Helps link customer accounts to specific regions and analyze rep performance.

5. Web Events Dataset:

   • Logs customer interactions on the company's website, including timestamps, event types, and user IDs.
   • Helps track user activity, identify trends in website engagement, and optimize the online user experience.

These datasets collectively enable comprehensive insights into sales performance, customer behavior, website engagement, and regional trends, forming the backbone of the interactive dashboard.

Dashboard Link:

Click Here To Visit Dashboard 📊

The global website content writing services market is experiencing robust growth, driven by the increasing demand for high-quality online content across various industries. Businesses are recognizing the crucial role of compelling website content in attracting and engaging customers, improving search engine rankings (SEO), and establishing brand authority. This trend is further amplified by the rise of digital marketing strategies, content marketing's proven effectiveness, and the expanding e-commerce sector. The market is segmented by content type (product descriptions, press releases, other content formats) and application (agencies, in-house teams). While precise market sizing data wasn't provided, considering the numerous companies involved—ranging from large agencies like SmartSites and Ignite Digital to freelance platforms such as Upwork—and the widespread adoption of online content marketing, a conservative estimate would place the 2025 market size at around $15 billion. A projected Compound Annual Growth Rate (CAGR) of 12% over the next decade (2025-2033) reflects the ongoing digital transformation and growing reliance on professional content creation. Geographic distribution shows a strong presence in North America and Europe, representing established digital economies with high internet penetration and robust marketing budgets. However, growth potential exists in rapidly developing regions like Asia-Pacific, driven by increasing internet usage and expanding businesses. The market faces challenges such as ensuring content quality, managing writer talent pools effectively, and adapting to evolving search engine algorithms. However, the continued emphasis on digital presence and the escalating demand for customized content will likely overcome these restraints, fueling sustained market expansion in the coming years. The key players listed represent a spectrum of service providers, encompassing large agencies with diverse offerings, specialized boutiques, and freelance platforms that cater to varying client needs and budgets. This competitive landscape fosters innovation and ensures varied service offerings.

Market Size and Growth Drivers The global clickstream analytics market is expected to reach USD 856.9 million by 2033, growing at a CAGR of 12.2% from 2025 to 2033. This growth is fueled by the increasing adoption of digital technologies, rising demand for customer insights, and growing e-commerce activities. Businesses are leveraging clickstream analytics to optimize website and application performance, improve customer experiences, and personalize marketing campaigns. Additionally, the growing popularity of cloud-based clickstream analytics solutions is making these tools more accessible and affordable for organizations of all sizes. Market Landscape and Regional Analysis Major players in the clickstream analytics market include Adobe Systems, AT Internet, Google, IBM, Microsoft, Oracle, and SAP SE. The market is fragmented, with several niche players offering specialized solutions. North America is the largest regional market for clickstream analytics, followed by Europe and Asia-Pacific. Developing regions such as Latin America, the Middle East, and Africa are expected to experience significant growth in the coming years due to increasing internet penetration and digitalization. Companies are focusing on expanding their global presence through strategic partnerships and acquisitions to cater to the growing demand for clickstream analytics solutions.

The AI website builder market is experiencing rapid growth, driven by increasing demand for efficient and user-friendly website creation tools. The market's ease of use, coupled with advanced AI capabilities like automated design suggestions, content generation, and SEO optimization, is attracting both individual users and businesses. While precise market sizing data is not provided, considering the presence of major players like Wix, Shopify, and GoDaddy alongside numerous smaller, specialized competitors, we can estimate the 2025 market size to be around $1.5 billion, based on observed growth in related sectors like website building and SaaS. A Compound Annual Growth Rate (CAGR) of 25% over the forecast period (2025-2033) is a reasonable assumption, reflecting the ongoing technological advancements and expanding adoption of AI in various industries. This growth is fueled by trends such as the increasing need for businesses to have a strong online presence and a growing preference for no-code/low-code solutions. However, restraints such as the need for robust AI algorithms to handle complex website design requirements and potential concerns about data privacy and security could pose challenges. Segmentation within the market likely includes tools catering to different user needs (e.g., e-commerce, blogs, portfolios), pricing models (freemium, subscription), and technical capabilities. The competitive landscape is highly dynamic, with established players constantly innovating and new entrants emerging. Success in this market will depend on factors such as the sophistication of AI capabilities, ease of use, integration with other marketing tools, pricing strategy, and robust customer support. The regional distribution likely shows a higher market penetration in North America and Europe initially, followed by gradual expansion into Asia-Pacific and other regions as AI website builder adoption increases globally. The historical period (2019-2024) likely demonstrates a gradual increase in market size, paving the way for the exponential growth projected for the forecast period. Market players are likely focusing on enhancing AI features, expanding integrations, and improving user experience to gain a competitive edge.

The first step in any new digital experience optimization program is to build a strong understanding of the digital journey. The reason is pretty simple. Whether it’s a software registration experience or an ecommerce path to purchase, our goal is always to identify challenges and present a clear roadmap to address them. But we first […]

Big Data Analysis Platform Market Outlook

The global market size for Big Data Analysis Platforms is projected to grow from USD 35.5 billion in 2023 to an impressive USD 110.7 billion by 2032, reflecting a CAGR of 13.5%. This substantial growth can be attributed to the increasing adoption of data-driven decision-making processes across various industries, the rapid proliferation of IoT devices, and the ever-growing volumes of data generated globally.

One of the primary growth factors for the Big Data Analysis Platform market is the escalating need for businesses to derive actionable insights from complex and voluminous datasets. With the advent of technologies such as artificial intelligence and machine learning, organizations are increasingly leveraging big data analytics to enhance their operational efficiency, customer experience, and competitiveness. The ability to process vast amounts of data quickly and accurately is proving to be a game-changer, enabling businesses to make more informed decisions, predict market trends, and optimize their supply chains.

Another significant driver is the rise of digital transformation initiatives across various sectors. Companies are increasingly adopting digital technologies to improve their business processes and meet changing customer expectations. Big Data Analysis Platforms are central to these initiatives, providing the necessary tools to analyze and interpret data from diverse sources, including social media, customer transactions, and sensor data. This trend is particularly pronounced in sectors such as retail, healthcare, and BFSI (banking, financial services, and insurance), where data analytics is crucial for personalizing customer experiences, managing risks, and improving operational efficiencies.

Moreover, the growing adoption of cloud computing is significantly influencing the market. Cloud-based Big Data Analysis Platforms offer several advantages over traditional on-premises solutions, including scalability, flexibility, and cost-effectiveness. Businesses of all sizes are increasingly turning to cloud-based analytics solutions to handle their data processing needs. The ability to scale up or down based on demand, coupled with reduced infrastructure costs, makes cloud-based solutions particularly appealing to small and medium-sized enterprises (SMEs) that may not have the resources to invest in extensive on-premises infrastructure.

Data Science and Machine-Learning Platforms play a pivotal role in the evolution of Big Data Analysis Platforms. These platforms provide the necessary tools and frameworks for processing and analyzing vast datasets, enabling organizations to uncover hidden patterns and insights. By integrating data science techniques with machine learning algorithms, businesses can automate the analysis process, leading to more accurate predictions and efficient decision-making. This integration is particularly beneficial in sectors such as finance and healthcare, where the ability to quickly analyze complex data can lead to significant competitive advantages. As the demand for data-driven insights continues to grow, the role of data science and machine-learning platforms in enhancing big data analytics capabilities is becoming increasingly critical.

From a regional perspective, North America currently holds the largest market share, driven by the presence of major technology companies, high adoption rates of advanced technologies, and substantial investments in data analytics infrastructure. Europe and the Asia Pacific regions are also experiencing significant growth, fueled by increasing digitalization efforts and the rising importance of data analytics in business strategy. The Asia Pacific region, in particular, is expected to witness the highest CAGR during the forecast period, propelled by rapid economic growth, a burgeoning middle class, and increasing internet and smartphone penetration.

Component Analysis

The Big Data Analysis Platform market can be broadly categorized into three components: Software, Hardware, and Services. The software segment includes analytics software, data management software, and visualization tools, which are crucial for analyzing and interpreting large datasets. This segment is expected to dominate the market due to the continuous advancements in analytics software and the increasing need for sophisticated data analysis tools. Analytics software enables organizations to process and analyze data from multiple sources,

Contents

This pizza sales dataset make up 12 relevant features: - order_id: Unique identifier for each order placed by a table - order_details_id: Unique identifier for each pizza placed within each order (pizzas of the same type and size are kept in the same row, and the quantity increases) - pizza_id: Unique key identifier that ties the pizza ordered to its details, like size and price - quantity: Quantity ordered for each pizza of the same type and size - order_date: Date the order was placed (entered into the system prior to cooking & serving) - order_time: Time the order was placed (entered into the system prior to cooking & serving) - unit_price: Price of the pizza in USD - total_price: unit_price * quantity - pizza_size: Size of the pizza (Small, Medium, Large, X Large, or XX Large) - pizza_type: Unique key identifier that ties the pizza ordered to its details, like size and price - pizza_ingredients: ingredients used in the pizza as shown in the menu (they all include Mozzarella Cheese, even if not specified; and they all include Tomato Sauce, unless another sauce is specified) - pizza_name: Name of the pizza as shown in the menu

🍕The Pizza Challenge

For the Maven Pizza Challenge, you’ll be playing the role of a BI Consultant hired by Plato's Pizza, a Greek-inspired pizza place in New Jersey. You've been hired to help the restaurant use data to improve operations, and just received the following note:

Welcome aboard, we're glad you're here to help!

Things are going OK here at Plato's, but there's room for improvement. We've been collecting transactional data for the past year, but really haven't been able to put it to good use. Hoping you can analyze the data and put together a report to help us find opportunities to drive more sales and work more efficiently.

Here are some questions that we'd like to be able to answer:

1. What days and times do we tend to be busiest?
2. How many pizzas are we making during peak periods?
3. What are our best and worst-selling pizzas?
4. What's our average order value?
5. How well are we utilizing our seating capacity? (we have 15 tables and 60 seats)

That's all I can think of for now, but if you have any other ideas I'd love to hear them – you're the expert!

Thanks in advance,

Mario Maven (Manager, Plato's Pizza)

Colllection Methodology

The public dataset is completely available on the Maven Analytics website platform where it stores and consolidates all available datasets for analysis in the Data Playground. The specific individual datasets at hand can be obtained at this link below: https://www.mavenanalytics.io/blog/maven-pizza-challenge

📌I set up the data model to include all the related instances in one single table so obtaining data for analysis is made easier.

My Inspiration

Complete details were also provided about the challenge in the link if you are interested. The purpose of uploading here is to conduct exploratory data analysis about the dataset beforehand with the use of Pandas and data visualization libraries in order to have a comprehensive review of the data and translate my findings and insights in the form of a single page visualization.