A league table of the 120 cryptocurrencies with the highest market cap reveals how diverse each crypto is and potentially how much risk is involved when investing in one. Bitcoin (BTC), for instance, had a so-called "high cap" - a market cap worth more than 10 billion U.S. dollars - indicating this crypto project has a certain track record or, at the very least, is considered a major player in the cryptocurrency space. This is different in Decentralize Finance (DeFi), where Bitcoin is only a relatively new player. A concentrated market The number of existing cryptocurrencies is several thousands, even if most have a limited significance. Indeed, Bitcoin and Ethereum account for nearly 75 percent of the entire crypto market capitalization. As crypto is relatively easy to create, the range of projects varies significantly - from improving payments to solving real-world issues, but also meme coins and more speculative investments. Crypto is not considered a payment method While often talked about as an investment vehicle, cryptocurrencies have not yet established a clear use case in day-to-day life. Central bankers found that usefulness of crypto in domestic payments or remittances to be negligible. A forecast for the world's main online payment methods took a similar stance: It predicts that cryptocurrency would only take up 0.2 percent of total transaction value by 2027.

In 2024, convenience was the leading reason to spend more money online during Cyber Week than in the previous year. Prices being lower online was the second most common reason for U.S. Cyber Week shoppers.

For 2024's Black Friday and Cyber Monday sales event, also known as the 'Cyber Week', approximately 77 percent of shoppers in the United States that planned to visit online retailers during Cyber Week specifically intended to buy clothing and accessories, making it the most popular product category. Just over 70 percent of respondents also planned to buy electronics.

As of early 2023, approximately ** percent of consumers in the United States said they would prefer to shop mostly online rather than in-store, making it the country with highest online shopping preference. In contrast, more shoppers preferred visiting physical stores in countries such as Austria, Finland, and New Zealand.

Graph and download economic data for E-Commerce Retail Sales as a Percent of Total Sales (ECOMPCTSA) from Q4 1999 to Q2 2025 about e-commerce, retail trade, percent, sales, retail, and USA.

About Dataset

📑 The structure of the online_shop dataset consists of interconnected tables that simulate a real-world e-commerce platform. Each table represents a key aspect of the business, such as products, orders, customers, suppliers, and reviews. Below is a detailed breakdown of each table and its columns:

🛍️ The "orders" table includes the following columns:

• order_id: A unique identifier for each order.
• order_date: The date when the order was placed.
• customer_id: A reference to the customer who placed the order (linked to the customers table).
• total_price: The total cost of the order, calculated as the sum of all items in the order.

👩‍💼 The "customers" table includes the following columns:

• customer_id: A unique identifier for each customer.
• first_name: The customer's first name.
• last_name: The customer's last name.
• address: The address of the customer.
• email: The email address of the customer (unique for each customer).
• phone_number: The phone number of the customer.

🛒 The "products" table includes the following columns:

• product_id: A unique identifier for each product.
• product_name: The name of the product.
• category: The category to which the product belongs (e.g., Electronics, Home & Kitchen).
• price: The price of the product.
• supplier_id: A reference to the supplier providing the product (linked to the suppliers table).

📦 The "order_items" table includes the following columns:

• order_item_id: A unique identifier for each item in an order.
• order_id: A reference to the order containing the item (linked to the orders table).
• product_id: A reference to the product being ordered (linked to the products table).
• quantity: The quantity of the product ordered.
• price_at_purchase: The price of the product at the time of the order.

🏢 The "suppliers" table includes the following columns:

• supplier_id: A unique identifier for each supplier.
• supplier_name: The name of the supplier.
• contact_name: The name of the contact person at the supplier.
• address: The address of the supplier.
• phone_number: The phone number of the supplier.
• email: The email address of the supplier.

🌟 The "reviews" table includes the following columns:

• review_id: A unique identifier for each product review.
• product_id: A reference to the product being reviewed (linked to the products table).
• customer_id: A reference to the customer who wrote the review (linked to the customers table).
• rating: The rating given to the product (1-5, where 5 is the best).
• review_text: The text content of the review.
• review_date: The date when the review was written.

💳 The "payments" table includes the following columns:

• payment_id: A unique identifier for each payment.
• order_id: A reference to the order being paid for (linked to the orders table).
• payment_method: The method of payment (e.g., Credit Card, PayPal).
• payment_date: The date when the payment was made.
• amount: The amount of the payment.
• transaction_status: The status of the payment (e.g., Pending, Completed, Failed).

🚚 The "shipments" table includes the following columns:

• shipment_id: A unique identifier for each shipment.
• order_id: A reference to the order being shipped (linked to the orders table).
• shipment_date: The date when the shipment was dispatched.
• carrier: The company responsible for delivering the shipment.
• tracking_number: The tracking number for the shipment.
• delivery_date: The date when the shipment was delivered (if applicable).
• shipment_status: The status of the shipment (e.g., Pending, Shipped, Delivered, Cancelled).

This dataset provides a comprehensive simulation of an e-commerce platform, covering everything from customer orders to supplier relationships, payments, shipments, and customer reviews. It is an excellent resource for practicing SQL, understanding relational databases, or performing data analysis and machine learning tasks.

This chart offers an insightful look at the store count by category in Nepal. Leading the way is Apparel, with 423 stores, which is 14.06% of the total stores in the region. Next is Home & Garden, contributing 287 stores, or 9.54% of the region's total. Travel also has a notable presence, with 251 stores, making up 8.34% of the store count in Nepal. This breakdown provides a clear picture of the diverse retail landscape in Nepal, showcasing the variety and scale of stores across different categories.

This chart provides a detailed overview of the number of Nepal online retailers by Monthly Visitors. Most Nepal stores' Monthly Visitors are Less than 100, there are 1.08K stores, which is 71.86% of total. In second place, 294 stores' Monthly Visitors are 100 to 1K, which is 19.51% of total. Meanwhile, 102 stores' Monthly Visitors are 1K to 10K, which is 6.77% of total. This breakdown reveals insights into Nepal stores distribution, providing a comprehensive picture of the performance and efficient of online retailer.

In Nepal, the distribution of stores across different platforms presents a dynamic picture of the market. WooCommerce, as a leading platform, hosts 2.41K stores, accounting for 65.51% of the total store count in the region. This is closely followed by Custom Cart, which supports 786 stores, representing 21.35% of the region's total. Shopify makes a significant contribution with 216 stores, or 5.87% of the total. The chart underscores the diversity and preferences of store owners in Nepal regarding their choice of platform.

This chart provides a detailed overview of the number of Nepal online retailers by Monthly Sales. Most Nepal stores' Monthly Sales are Less than $100.00, there are 1.08K stores, which is 98.99% of total. In second place, 9 stores' Monthly Sales are $10.00M to $100.00M, which is 0.82% of total. Meanwhile, 1 stores' Monthly Sales are $1.00M to $10.00M, which is 0.09% of total. This breakdown reveals insights into Nepal stores distribution, providing a comprehensive picture of the performance and efficient of online retailer.

The number of users in the e-commerce market in the United States was modeled to stand at ************** users in 2024. Following a continuous upward trend, the number of users has risen by ************* users since 2017. Between 2024 and 2029, the number of users will rise by ************* users, continuing its consistent upward trajectory.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on eCommerce.

Overview:

This dataset contains 1000 rows of synthetic online retail sales data, mimicking transactions from an e-commerce platform. It includes information about customer demographics, product details, purchase history, and (optional) reviews. This dataset is suitable for a variety of data analysis, data visualization and machine learning tasks, including but not limited to: customer segmentation, product recommendation, sales forecasting, market basket analysis, and exploring general e-commerce trends. The data was generated using the Python Faker library, ensuring realistic values and distributions, while maintaining no privacy concerns as it contains no real customer information.

Data Source:

This dataset is entirely synthetic. It was generated using the Python Faker library and does not represent any real individuals or transactions.

Data Content:

Potential Use Cases (Inspiration):

Customer Segmentation: Group customers based on demographics, purchasing behavior, and preferences.

Product Recommendation: Build a recommendation system to suggest products to customers based on their past purchases and browsing history.

Sales Forecasting: Predict future sales based on historical trends.

Market Basket Analysis: Identify products that are frequently purchased together.

Price Optimization: Analyze the relationship between price and demand.

Geographic Analysis: Explore sales patterns across different cities.

Time Series Analysis: Investigate sales trends over time.

Educational Purposes: Great for practicing data cleaning, EDA, feature engineering, and modeling.

In 2024, global retail e-commerce sales reached an estimated ************ U.S. dollars. Projections indicate a ** percent growth in this figure over the coming years, with expectations to come close to ************** dollars by 2028. World players Among the key players on the world stage, the American marketplace giant Amazon holds the title of the largest e-commerce player globally, with a gross merchandise value of nearly *********** U.S. dollars in 2024. Amazon was also the most valuable retail brand globally, followed by mostly American competitors such as Walmart and the Home Depot. Leading e-tailing regions E-commerce is a dormant channel globally, but nowhere has it been as successful as in Asia. In 2024, the e-commerce revenue in that continent alone was measured at nearly ************ U.S. dollars, outperforming the Americas and Europe. That year, the up-and-coming e-commerce markets also centered around Asia. The Philippines and India stood out as the swiftest-growing e-commerce markets based on online sales, anticipating a growth rate surpassing ** percent.

This chart provides a detailed overview of the number of Pakistan online retailers by Monthly Sales. Most Pakistan stores' Monthly Sales are Less than $100.00, there are 11.89K stores, which is 97.96% of total. In second place, 132 stores' Monthly Sales are $100.00K to $1.00M, which is 1.09% of total. Meanwhile, 86 stores' Monthly Sales are $10.00M to $100.00M, which is 0.71% of total. This breakdown reveals insights into Pakistan stores distribution, providing a comprehensive picture of the performance and efficient of online retailer.

Custom Growth Charts for Kids Market Outlook

According to our latest research, the global Custom Growth Charts for Kids market size reached USD 735 million in 2024, reflecting a robust consumer interest in personalized children’s products. The market is projected to grow at a CAGR of 6.2% during the forecast period, reaching a value of USD 1,259 million by 2033. This growth is primarily driven by rising parental awareness of early childhood development, increasing demand for customized home décor, and the expanding influence of e-commerce platforms. As per the latest research, the market’s dynamic evolution is attributed to both innovation in product offerings and the growing inclination of millennial parents toward personalized, interactive, and educational children’s products.

One of the most significant growth factors in the Custom Growth Charts for Kids market is the increasing emphasis on early childhood development and education among modern parents. Parents are becoming more aware of the importance of tracking their child’s physical growth, not only for health reasons but also as a means of creating lasting family memories. This awareness has fueled demand for visually appealing and interactive growth charts that serve both as functional tools and decorative elements in children’s rooms. The trend is further amplified by the proliferation of social media platforms, where parents frequently share milestones and personalized products, thereby encouraging others to invest in similar items. Additionally, advancements in printing and design technologies have enabled manufacturers to offer a wide array of customizable options, catering to diverse consumer preferences and themes.

Another crucial driver is the surge in online retail and digital marketing, which has revolutionized the distribution and accessibility of custom growth charts for kids. E-commerce platforms provide a convenient and diverse marketplace for parents to explore, compare, and purchase personalized growth charts. This digital shift has allowed small and medium-sized enterprises to enter the market with innovative designs and competitive pricing, thereby intensifying market competition and expanding product variety. Online customization tools further enhance consumer engagement, enabling users to personalize charts with names, themes, colors, and even photographs, which significantly boosts the perceived value of these products. The direct-to-consumer model facilitated by online stores also allows brands to gather valuable customer insights and feedback, driving continuous product improvement and innovation.

A third notable growth factor is the growing trend of gifting personalized items for occasions such as baby showers, birthdays, and holidays. Custom growth charts for kids have emerged as popular gift choices due to their practicality, sentimental value, and aesthetic appeal. This has led manufacturers and retailers to collaborate with artists and designers to introduce limited-edition collections and themed growth charts, further broadening the market’s appeal. Moreover, the increasing focus on sustainability and eco-friendly materials has prompted companies to offer growth charts made from wood, canvas, and other environmentally responsible materials, aligning with the values of eco-conscious consumers. These initiatives not only enhance product differentiation but also foster brand loyalty among discerning parents.

From a regional perspective, North America currently dominates the Custom Growth Charts for Kids market, accounting for the largest market share in 2024, followed closely by Europe and Asia Pacific. The high disposable income, advanced retail infrastructure, and strong presence of leading brands contribute to North America’s leadership. Europe is witnessing steady growth, driven by rising consumer interest in personalized children’s products and a strong culture of gifting. Meanwhile, Asia Pacific is emerging as a lucrative market, fueled by a growing middle-class population, increasing urbanization, and the rapid adoption of online shopping. Latin America and the Middle East & Africa are expected to experience moderate growth, supported by improving economic conditions and expanding retail networks. The regional outlook suggests that while mature markets will continue to innovate, emerging regions present significant untapped potential for market expansion.

Product Type Analysis

The Product Type segment in the Custom Growth Charts for Kids mark

Online Retail Transaction Records

Online Retail Sales: Product Transactions and Customer Details

By Ali Prasla [source]

About this dataset

The Online Retail Sales Dataset, often referred to as the Online Retail.csv file, is an extensive and comprehensive collection of data points relating to e-commerce transactions. This dataset provides a detailed view of sales activities within the online retail sector, covering numerous essential attributes necessary for a quantitative understanding of consumer behavior and the overall business performance.

One of the key elements covered in this dataset is 'InvoiceNo', which is a unique identifier for each transaction taking place in this retail environment. Given its uniqueness, it serves as a primary key for distinguishing individual transactions. It's worthwhile to note that these Invoice Numbers are numerical values.

Another important attribute included here is 'StockCode'. Each product listed or sold on this online retail platform has been assigned with its unique identification code or StockCode. These codes are also numerical values that offer another layer to clearly classify items and distinguish one from another.

For further understanding, every product comes with a basic description noted under the 'Description' column. In textual form, these descriptions provide insights into what exactly each product item entails. Aside from aiding identification efforts, they can potentially open avenues for text-based analysis such as sentiment analysis or keyword flagging based on product trends.

'Moving onto details about transactions themselves', we have two crucial columns: 'Quantity' and 'UnitPrice'. As their names suggest, these show respectively how many particular units of an item were sold per transaction and at what price per unit was sold at.

Further adding detail to our transactions information comes 'InvoiceDate', which records when each separate purchase occurred down to accurate date & time records. This data can be pivotal in recognizing sales patterns throughout different periods or predicting future trends based on historical timing behavior.

Finally yet importantly comes our global indicator - The ‘Country’ column specifies various countries where customers reside who interacts with this particular online platform regularly by making purchases. This application allows us insights into the geographical dispersion of user base across various countries, potentially providing us insights into regional preferences or global market segmentation.

Ith such a wealth of detailed transaction records and customer information, the Online Retail.csv dataset stands as an invaluable tool for those looking to delve deep into online retail sales data analysis. The possibilities with this dataset are vast, ranging from shaping efficient marketing strategies based on geographical data to predicting sales & growth metrics using historical behavior and much more

How to use the dataset

Here's how to make best use of this dataset:

Getting Started Before you start analyzing your data – you'll have to load it into statistical software such as Python (using pandas library) or R. The dataset is saved in .csv file format which supports easy reading into most data manipulation software.

Understand The Fields

• InvoiceNo: Each transaction made has an associated unique numerical identifier called InvoiceNo. Consider it like a receipt code - these allow for tracking individual transactions.

• StockCode: To identify each product uniquely during analysis, refer to each StockCode value which is essentially a product identification code.

• Description: A brief textual description about each product that can be invaluable when dealing with categories for market-basket type analysis.

• Quantity: Each row lists out how many units of a particular item were involved in a single transaction - watch out for very large values as they might represent bulk orders.

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Flip Chart Market Outlook

According to our latest research, the global flip chart market size reached USD 1.12 billion in 2024, reflecting a robust demand across educational, corporate, and training sectors. The market is expected to grow at a CAGR of 4.7% from 2025 to 2033, reaching a forecasted value of USD 1.69 billion by 2033. This steady expansion is primarily driven by the growing emphasis on collaborative learning, interactive presentations, and the increasing integration of traditional and digital communication tools in both developed and emerging economies. As per our latest research, the flip chart market is experiencing a transformation fueled by technological advancements and evolving end-user preferences, making it a key segment within the broader office supplies and educational tools industry.

One of the primary growth factors propelling the flip chart market is the persistent demand for effective visual communication tools in educational and corporate environments. Despite the proliferation of digital devices, flip charts remain indispensable for brainstorming sessions, group discussions, and interactive teaching methods. Their simplicity, portability, and ease of use make them a preferred choice for educators and business professionals who value real-time engagement and flexibility. Moreover, the rise in blended learning models, where traditional and digital tools are used in tandem, has further cemented the relevance of flip charts as a complementary resource. This trend is particularly evident in regions where digital infrastructure is still developing, underscoring the enduring appeal of flip charts in facilitating face-to-face communication and collaboration.

Another significant driver is the increasing adoption of flip charts in training and seminar settings across various industries. As organizations prioritize employee development and continuous learning, the demand for tools that foster interactive participation and idea generation is on the rise. Flip charts, especially portable and electronic variants, are being increasingly utilized in workshops, seminars, and off-site training programs to enable dynamic content creation and real-time feedback. The versatility of flip charts, coupled with advancements in materials and design, has led to the introduction of products that cater to specific user needs, such as eco-friendly paper flip charts and smart electronic flip charts with digital integration. These innovations are attracting a broader customer base, including environmentally conscious organizations and tech-savvy professionals.

The flip chart market is also benefiting from expanding distribution networks and the growing influence of e-commerce. Online stores and specialty retailers are playing a crucial role in enhancing product accessibility and offering a diverse range of flip chart options to consumers worldwide. The convenience of online shopping, coupled with competitive pricing and detailed product information, has made it easier for schools, offices, and training centers to procure flip charts that meet their unique requirements. Additionally, manufacturers are increasingly focusing on customization and after-sales support to differentiate their offerings and build customer loyalty. These factors are collectively contributing to the sustained growth and diversification of the flip chart market on a global scale.

Regionally, the Asia Pacific region is emerging as a key growth engine for the flip chart market, driven by rapid urbanization, expanding educational infrastructure, and the proliferation of corporate offices. Countries like China, India, and Southeast Asian nations are witnessing increased investments in education and professional training, creating substantial opportunities for flip chart manufacturers and distributors. Meanwhile, North America and Europe continue to be mature markets with stable demand, supported by established corporate and educational sectors. The Middle East & Africa and Latin America, though smaller in market size, are showing promising growth trajectories as awareness about the benefits of interactive learning tools increases. The regional dynamics underscore the importance of tailored strategies to address the unique needs and preferences of diverse customer segments.

Context

This data set is based on transactions of customers who bought occasion gift ware from an online store.

Content

This data is blended with the real time transactions of different online retail stores. The description of the data is defined as below:

Acknowledgements

Center for Machine Learning and Intelligent Systems (UCI)

Inspiration

Question: Which customers are more important for the business? Question: What is the recent visiting period of each customer? Question: What is the purchasing frequency of the customer? Question: What is the spending frequency of the customer?

Custom Growth Charts for Kids Market Outlook

According to our latest research, the global Custom Growth Charts for Kids market size reached USD 545 million in 2024, with a robust year-on-year growth rate. The market is projected to expand at a CAGR of 7.2% from 2025 to 2033, reaching an estimated USD 1,017 million by 2033. This growth is primarily driven by the increasing demand for personalized and aesthetically appealing children’s products, along with a rising focus on child development and milestone tracking among modern parents. As per our most recent analysis, the market’s upward trajectory is underpinned by a surge in e-commerce adoption, innovative design trends, and the growing influence of social media parenting communities.

One of the most significant growth factors for the Custom Growth Charts for Kids market is the heightened parental interest in tracking the developmental milestones of their children. Modern parents are increasingly seeking products that blend functionality with personalization, enabling them to celebrate their child’s growth journey in a unique way. The availability of customizable features such as personalized names, themed designs, and even photo integration has transformed growth charts from simple measurement tools into cherished keepsakes. This trend is further amplified by the influence of social media platforms, where parents share milestone moments, thereby fueling demand for visually appealing and customizable growth charts. The shift toward nuclear families and urban lifestyles has also contributed, as parents look for creative ways to document and display their children’s progress within limited living spaces.

Another crucial driver is the rapid expansion of online retail channels, which has made custom growth charts more accessible to a global audience. E-commerce platforms provide a wide variety of options, allowing parents to compare designs, customization features, and prices with ease. The convenience of online shopping, coupled with targeted digital marketing campaigns, has significantly broadened the consumer base for these products. Additionally, the ability to preview and personalize growth charts online before purchase has enhanced customer satisfaction and encouraged repeat purchases. The proliferation of direct-to-consumer brands specializing in personalized children’s products has also intensified competition, leading to greater product innovation and improved quality standards across the market.

Sustainability and safety concerns are also shaping the evolution of the Custom Growth Charts for Kids market. Parents are increasingly prioritizing eco-friendly materials and non-toxic inks, particularly for products intended for infants and toddlers. Manufacturers are responding by offering growth charts made from sustainable wood, recycled paper, and water-based inks, thereby aligning with the values of environmentally conscious consumers. This focus on health and safety is particularly pronounced in regions with stringent regulatory standards, such as North America and Europe. Furthermore, collaborations with artists and designers who emphasize sustainability in their creations are helping brands differentiate themselves in a crowded market. As consumer awareness continues to rise, the demand for ethically produced and safe custom growth charts is expected to grow, further propelling market expansion.

Regionally, North America currently dominates the Custom Growth Charts for Kids market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The North American market benefits from high disposable incomes, widespread digital literacy, and a strong culture of celebrating childhood milestones. Europe’s market is characterized by a preference for artisanal and eco-friendly products, while Asia Pacific is witnessing rapid growth due to a burgeoning middle class and increasing urbanization. Latin America and the Middle East & Africa are emerging markets, with rising awareness and growing e-commerce penetration expected to drive future growth. Regional dynamics are influenced by cultural preferences, regulatory environments, and the pace of digital transformation, all of which will continue to shape market opportunities and challenges over the forecast period.

Our People data is gathered and aggregated via surveys, digital services, and public data sources. We use powerful profiling algorithms to collect and ingest only fresh and reliable data points.

Our comprehensive data enrichment solution includes a variety of data sets that can help you address gaps in your customer data, gain a deeper understanding of your customers, and power superior client experiences.

1. Geography - City, State, ZIP, County, CBSA, Census Tract, etc.
2. Demographics - Gender, Age Group, Marital Status, Language etc.
3. Financial - Income Range, Credit Rating Range, Credit Type, Net worth Range, etc
4. Persona - Consumer type, Communication preferences, Family type, etc
5. Interests - Content, Brands, Shopping, Hobbies, Lifestyle etc.
6. Household - Number of Children, Number of Adults, IP Address, etc.
7. Behaviours - Brand Affinity, App Usage, Web Browsing etc.
8. Firmographics - Industry, Company, Occupation, Revenue, etc
9. Retail Purchase - Store, Category, Brand, SKU, Quantity, Price etc.
10. Auto - Car Make, Model, Type, Year, etc.
11. Housing - Home type, Home value, Renter/Owner, Year Built etc.

People Data Schema & Reach: Our data reach represents the total number of counts available within various categories and comprises attributes such as country location, MAU, DAU & Monthly Location Pings:

Data Export Methodology: Since we collect data dynamically, we provide the most updated data and insights via a best-suited method on a suitable interval (daily/weekly/monthly).

People Data Use Cases:

360-Degree Customer View: Get a comprehensive image of customers by the means of internal and external data aggregation.

Data Enrichment: Leverage Online to offline consumer profiles to build holistic audience segments to improve campaign targeting using user data enrichment

Fraud Detection: Use multiple digital (web and mobile) identities to verify real users and detect anomalies or fraudulent activity.

Advertising & Marketing: Understand audience demographics, interests, lifestyle, hobbies, and behaviors to build targeted marketing campaigns.

Using Factori People Data you can solve use cases like:

Acquisition Marketing Expand your reach to new users and customers using lookalike modeling with your first party audiences to extend to other potential consumers with similar traits and attributes.

Lookalike Modeling

Build lookalike audience segments using your first party audiences as a seed to extend your reach for running marketing campaigns to acquire new users or customers

And also, CRM Data Enrichment, Consumer Data Enrichment B2B Data Enrichment B2C Data Enrichment Customer Acquisition Audience Segmentation 360-Degree Customer View Consumer Profiling Consumer Behaviour Data

Here's the schema of People Data: person_id first_name last_name age gender linkedin_url twitter_url facebook_url city state address zip zip4 country delivery_point_bar_code carrier_route walk_seuqence_code fips_state_code fips_country_code country_name latitude longtiude address_type metropolitan_statistical_area core_based+statistical_area census_tract census_block_group census_block primary_address pre_address streer post_address address_suffix address_secondline address_abrev census_median_home_value home_market_value property_build+year property_with_ac property_with_pool property_with_water property_with_sewer general_home_value property_fuel_type year month household_id Census_median_household_income household_size marital_status length+of_residence number_of_kids pre_school_kids single_parents working_women_in_house_hold homeowner children adults generations net_worth education_level occupation education_history credit_lines credit_card_user newly_issued_credit_card_user credit_range_new
credit_cards loan_to_value mortgage_loan2_amount mortgage_loan_type
mortgage_loan2_type mortgage_lender_code
mortgage_loan2_render_code
mortgage_lender mortgage_loan2_lender
mortgage_loan2_ratetype mortgage_rate
mortgage_loan2_rate donor investor interest buyer hobby personal_email work_email devices phone employee_title employee_department employee_job_function skills recent_job_change company_id company_name company_description technologies_used office_address office_city office_country office_state office_zip5 office_zip4 office_carrier_route office_latitude office_longitude office_cbsa_code
office_census_block_group
office_census_tract office_county_code
company_phone
company_credit_score
company_csa_code
company_dpbc
company_franchiseflag
company_facebookurl company_linkedinurl company_twitterurl
company_website company_fortune_rank
company_government_type company_headquarters_branch company_home_business
company_industry
company_num_pcs_used
company_num_employees
company_firm_individual company_msa company_msa_name
company_naics_code
company_naics_description
company_naics_code2 company_naics_description2
company_sic_code2
company_sic_code2_description
company_sic...