Top 10 Data Mining Companies in 2024

Companies	Employees	HQ location	Revenue	Website	Industry
EBay	View 1,389 employees	🇺🇸 United States, California, San Jose	$ >1000M	ebay.com	Data and Analytics, Software, Information Technology, Design, Commerce and Shopping, Hardware
SAS	View 23,106 employees	🇺🇸 United States, North Carolina, Cary	$ 500-1000M	sas.com	Artificial Intelligence, Data and Analytics, Software, Science and Engineering, Information Technology
Teradata	View 9,216 employees	🇺🇸 United States, California, San Diego	$ 500-1000M	teradata.com	Data and Analytics, Design, Information Technology, Internet Services, Software, Hardware
EXL	View 29,899 employees	🇺🇸 United States, New Jersey, West New York	$ 500-1000M	exlservice.com	Data and Analytics, Information Technology, Software, Artificial Intelligence, Professional Services, Apps
RxDataScience	View 61 employees	🇺🇸 United States, North Carolina, Durham	$ 500-1000M	rxdatascience.com	Data and Analytics, Software, Artificial Intelligence, Information Technology, Science and Engineering, Professional Services, Health Care, Design, Biotechnology
Saia	View 3,203 employees	🇺🇸 United States, Georgia, Johns Creek	$ >1000M	saia.com	Data and Analytics, Software, Transportation, Information Technology
Dynata	View 3,140 employees	🇺🇸 United States, Connecticut, Shelton	$ 500-1000M	dynata.com	Data and Analytics, Information Technology, Software, Design, Artificial Intelligence
Esri	View 6,241 employees	🇺🇸 United States, California, Redlands	$ 500-1000M	esri.com	Data and Analytics, Internet Services, Navigation and Mapping, Information Technology, Hardware, Software
ICIS	View 792 employees	🇬🇧 United Kingdom, London	$ 500-1000M	icis.com	Data and Analytics, Design, Information Technology
Evalueserve	View 5,892 employees	🇨🇭 Switzerland, ZUG, Zug	$ 500-1000M	evalueserve.com	Artificial Intelligence, Data and Analytics, Science and Engineering, Software, Information Technology, Professional Services

1. EBay

eBay, a global e-commerce leader, specializes in consumer-to-consumer and business-to-consumer sales through its innovative online platform. The company leverages data mining to enhance user experiences and streamline transaction processes. By analyzing vast amounts of data, eBay is able to offer personalized shopping recommendations, optimize its search engine functionality, and predict market trends, which helps sellers maximize their sales and enables buyers to find products more efficiently. This strategic use of data mining underscores eBay’s commitment to continuous improvement and customer satisfaction in the dynamic e-commerce landscape.

Location 🇺🇸 United States, California, San Jose	Size View 1,389 employees
Revenue $ >1000M	Industries Data and Analytics, Software, Information Technology, Design, Commerce and Shopping, Hardware
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2. SAS

SAS Institute Inc. is a trusted leader in analytics, known for its robust suite of data mining, statistical analysis, and business intelligence tools. With decades of experience in refining complex data into actionable insights, SAS helps organizations across various industries make informed decisions that drive growth and efficiency. Their advanced analytics software and solutions are designed to tackle vast data sets, enabling users to predict outcomes, optimize processes, and uncover hidden opportunities. The company’s commitment to innovation and excellence makes it an essential partner for businesses looking to leverage data for a competitive edge.

Location 🇺🇸 United States, North Carolina, Cary	Size View 23,106 employees
Revenue $ 500-1000M	Industries Artificial Intelligence, Data and Analytics, Software, Science and Engineering, Information Technology
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3. Teradata

Teradata is a global leader in data analytics and management solutions, specializing in data warehousing and business intelligence. As an expert in data mining, Teradata enables businesses to uncover valuable insights from large and complex datasets, helping them make data-driven decisions to enhance operational efficiency and foster innovation. Their robust analytics solutions are designed to handle massive volumes of data, providing scalable and reliable platforms that support various industries in achieving optimized outcomes through advanced data analysis.

Location 🇺🇸 United States, California, San Diego	Size View 9,216 employees
Revenue $ 500-1000M	Industries Data and Analytics, Design, Information Technology, Internet Services, Software, Hardware
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4. EXL

EXL is a leading global provider of data analytics and digital operations solutions, specializing in data mining services that help businesses extract valuable insights from vast amounts of data. By integrating advanced analytics and machine learning, EXL enables companies across various industries such as insurance, healthcare, finance, and retail to optimize their operations, enhance decision-making, and drive strategic growth. With a robust approach to analyzing trends, predicting customer behavior, and improving service delivery, EXL stands as a pivotal partner for organizations looking to leverage data for a competitive edge.

Location 🇺🇸 United States, New Jersey, West New York	Size View 29,899 employees
Revenue $ 500-1000M	Industries Data and Analytics, Information Technology, Software, Artificial Intelligence, Professional Services, Apps
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5. RxDataScience

RxDataScience is a prominent player in the data mining sector, offering comprehensive solutions that transform complex data into actionable insights. The company specializes in utilizing advanced analytics and machine learning techniques to help businesses across multiple industries, including healthcare and retail, optimize operations, improve customer engagement, and drive innovation. By developing user-friendly software and tools, RxDataScience empowers organizations to harness the full potential of their data, ensuring they remain competitive in an increasingly data-driven world.

Location 🇺🇸 United States, North Carolina, Durham	Size View 61 employees
Revenue $ 500-1000M	Industries Data and Analytics, Software, Artificial Intelligence, Information Technology, Science and Engineering, Professional Services, Health Care, Design, Biotechnology
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6. Saia

Saia, a prominent player in the data mining sector, harnesses advanced analytical techniques to extract valuable insights from large datasets. Specializing in transforming raw data into actionable intelligence, Saia empowers businesses to make informed decisions, optimize operations, and predict future trends. Their robust solutions cater to various industries, enabling clients to not only meet but exceed their strategic goals through data-driven methodologies. Saia’s commitment to innovation and excellence in data analysis makes them a pivotal resource for companies looking to leverage data for competitive advantage.

Location 🇺🇸 United States, Georgia, Johns Creek	Size View 3,203 employees
Revenue $ >1000M	Industries Data and Analytics, Software, Transportation, Information Technology
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7. Dynata

Dynata is a leading provider of first-party data and insights, specializing in data mining and analysis to help businesses understand consumer behavior and marketplace trends. Leveraging advanced technology and a global network, Dynata transforms raw data into actionable insights, enabling companies to make informed decisions and tailor their strategies to meet market demands. Their comprehensive approach to data collection and analysis makes Dynata a crucial partner for organizations aiming to optimize performance, enhance customer engagement, and drive growth through data-driven decisions.

Location 🇺🇸 United States, Connecticut, Shelton	Size View 3,140 employees
Revenue $ 500-1000M	Industries Data and Analytics, Information Technology, Software, Design, Artificial Intelligence
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8. Esri

Esri, a leading provider in geographic information system (GIS) software, specializes in data mining technologies that harness spatial data to unlock profound insights for various industries. Their comprehensive suite of tools aids businesses in visualizing, analyzing, and interpreting geographic data, turning it into actionable intelligence. By allowing companies to effectively map and scrutinize both geographic and demographic patterns, Esri plays a crucial role in informed decision-making and strategic planning, thus enhancing operational efficiency and competitive edge across multiple sectors.

Location 🇺🇸 United States, California, Redlands	Size View 6,241 employees
Revenue $ 500-1000M	Industries Data and Analytics, Internet Services, Navigation and Mapping, Information Technology, Hardware, Software
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9. ICIS

ICIS is a renowned leader in the data mining sector, providing comprehensive solutions that transform massive datasets into actionable insights. Their advanced analytics and data processing technologies empower businesses to enhance decision-making and boost operational efficiencies. By leveraging machine learning and artificial intelligence, Icis helps companies across various industries, from healthcare to finance, unlock the value hidden in their data, enabling them to predict trends, optimize processes, and drive innovation. This focus on harnessing the power of data strategically positions Icis at the forefront of the data-driven business landscape.

Location 🇬🇧 United Kingdom, London	Size View 792 employees
Revenue $ 500-1000M	Industries Data and Analytics, Design, Information Technology
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10. Evalueserve

Evalueserve is a global professional services provider specializing in data mining and analytics. They leverage cutting-edge technology to transform complex data sets into actionable insights, helping businesses optimize their performance and drive strategic decision-making. Evalueserve’s expertise in extracting and interpreting data enables companies across various industries to stay ahead of trends, manage risk effectively, and enhance operational efficiencies. Their dedicated approach to data-driven solutions positions them as a crucial partner for organizations looking to capitalize on the power of their information assets.

Location 🇨🇭 Switzerland, ZUG, Zug	Size View 5,892 employees
Revenue $ 500-1000M	Industries Artificial Intelligence, Data and Analytics, Science and Engineering, Software, Information Technology, Professional Services
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Things to Consider When Prospecting into Data Mining Companies

Common Pain Points and Challenges for Companies in Data Mining

Data Quality

Ensuring data quality is foundational in data mining, as poor data leads to unreliable outcomes and insights.

Inaccurate or incomplete data sets.
Lack of standardization across data sources.
Difficulty in filtering noise from useful data.

Sales Insight: Emphasize your solution’s strengths in enhancing data accuracy and integration. Showing your understanding of the importance of high-quality data can build trust with your prospects, ensuring them that your solution can deliver reliable and actionable insights.

Data Security and Privacy Concerns

With increasing digital data usage, security and privacy concerns are a significant hurdle in the data mining industry.

Strict compliance and regulatory requirements.
Risk of data breaches or unauthorized access.
Ethical concerns surrounding data usage.

Sales Insight: Highlight how your product adheres to the highest standards of data security and compliance. By reassuring potential customers about these aspects, you can alleviate their concerns and position your solution as both secure and ethical.

Integration with Existing Systems

Seamlessly integrating new data mining tools into existing IT infrastructure is often a complex challenge for many businesses.

Compatibility issues with legacy systems.
High costs and complexities of integration.
Potential disruption to ongoing operations.

Sales Insight: Point out the flexibility and compatibility features of your data mining solution. If you can demonstrate that your product can integrate smoothly without disrupting current operations, it makes a strong case for its ease of adoption and efficiency improvements.

Skill Gap

There is often a significant skill gap in organizations, with a shortage of professionals adept at data mining techniques.

Limited availability of skilled data analysts.
Need for continuous employee training and development.
The high cost of hiring specialized talent.

Sales Insight: Address this pain point by detailing how user-friendly and accessible your data mining solution is. Offer training support or learning resources to ease the transition, thereby reducing the intimidation factor and encouraging adoption.

Data Volume and Complexity

The exponential growth in data volume and its complexity poses a significant challenge in data mining.

Managing massive volumes of data from diverse sources.
Increased complexity in data analysis.
Scalability issues with existing data analysis tools.

Sales Insight: Discuss how your solution can handle vast and complex data sets efficiently. Demonstrate scalability and robustness, ensuring prospects that your tool grows with their needs and remains performant under increasing loads.

Lack of Understanding of Data Mining Value

A fundamental challenge is the lack of understanding among some businesses about the full value of data mining.

Difficulty in justifying ROI from data mining investments.
Perception of data mining as a non-critical operation.
Limited awareness of data mining benefits beyond surface-level insights.

Sales Insight: Educate your prospects about the transformative potential of data mining, using case studies and clear ROI calculations. When businesses understand the impact of data-driven decisions, they’re more likely to invest in your solution.

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Key Decision-Makers and Influencers in Data Mining

Key Departments

IT & Systems

Insight: This department ensures the seamless operation of data infrastructure. IT leaders focus on purchasing reliable, scalable solutions that offer security and efficient data handling. They highly value vendor support and system compatibility.

Research and Development

Insight: R&D focuses on innovation and developing new applications for data analytics. They seek cutting-edge technology that can provide them a competitive edge in developing new products or services.

Marketing

Insight: Utilizes data mining to understand customer behavior and market trends. Marketing professionals are interested in solutions that offer deep insights and can be easily integrated into their existing digital marketing platforms.

Sales

Insight: Sales departments use data to refine sales strategies and improve customer relations. They value tools that help with customer segmentation, sales forecasting, and performance analysis.

Strategic Planning

Insight: Involved in shaping long-term goals using data-driven insights. Strategic planners look for solutions that provide comprehensive data analysis, robust reporting tools, and forecasting accuracy to inform business strategies.

Seniority Level

Vice Presidents of Data Analytics

Insight: Vice Presidents in this field oversee the data analytics department and are deeply involved in how data mining tools can enhance data-driven decision-making. Their focus is on integrating solutions that increase accuracy and speed of analytics, supporting overall business goals.

Directors of Business Intelligence

Insight: Directors of Business Intelligence evaluate and integrate data mining technologies that improve the extraction of actionable insights from vast data sets. They look for solutions that are scalable and can be effectively integrated with existing IT infrastructure.

IT Managers

Insight: IT Managers handle the technical aspects of data mining implementations. They assess the technical compatibility of new data mining tools with existing systems and their operational impacts, focusing on efficiency, cost-effectiveness, and support requirements.

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Buying Processes and Behaviors in Data Mining

Emphasis on Data Security and Compliance

Ensuring data security and compliance is central to the purchasing decisions of data mining firms.

Data mining involves handling sensitive information, making security paramount.
Regulatory compliance cannot be compromised in any data-oriented solutions.
Trust and reliability in vendors play a significant role in final decisions.

How to leverage: Highlight your product’s security features and compliance with relevant regulations. Obtain trustworthy certifications and showcase testimonials from credible clients to build confidence among potential customers in the data mining industry.

Preference for Customizable Solutions

Data mining entities prefer customizable solutions that can adapt to specific analytical needs.

No one-size-fits-all: different companies have unique data challenges.
Customization allows for optimized performance tailored to specific datasets.
Flexibility in solutions can lead to better customer satisfaction and retention.

How to leverage: Offer modular solutions that allow for customization based on the customer’s needs. Stress the adaptability and efficiency of your product, and be prepared to demonstrate how your solution can be tailored during sales presentations.

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Prospecting Tips for Selling to Data Mining Companies

Highlight Customization Capabilities

One size doesn’t fit all in the data mining sector. Tailor your pitch to show how your service or product adapts to specific needs and scales based on individual company demands.

Tip: Provide examples where your product was customized to meet unique client requirements in the data mining field.

Stress Data Security and Compliance

Data mining involves handling sensitive information, making security a top priority. Stress how your product meets the highest standards of data security and regulatory compliance.

Tip: Mention specific security certifications your software has received and outline your compliance with international data protection regulations.

Showcase Ease of Integration

Data mining tools need to integrate smoothly with existing systems to be truly effective. Point out how easy it is to integrate your solution with other tools and platforms.

Tip: Highlight specific integrations that have benefited other companies in the data mining industry.

Focus on Real-time Analytics

The ability to analyze data in real-time can significantly enhance decision-making for data mining firms. Emphasize real-time capabilities of your solution, if applicable.

Tip: Share examples of how real-time analytics has transformed decision-making processes for your existing clients.

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Want to see more Data Mining companies?

Things to Consider When Prospecting into Data Mining Companies

Common Pain Points and Challenges for Companies in Data Mining

Skill Gap

Data Volume and Complexity

Lack of Understanding of Data Mining Value

Start finding new prospects that match your ICP

Key Decision-Makers and Influencers in Data Mining

Key Departments

Seniority Level

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Buying Processes and Behaviors in Data Mining

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Prospecting Tips for Selling to Data Mining Companies

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Top 10 Data Mining Companies — a guide for sales

Want to see more Data Mining companies?

Things to Consider When Prospecting into Data Mining Companies

Common Pain Points and Challenges for Companies in Data Mining

Lack of Understanding of Data Mining Value

Start finding new prospects that match your ICP

Key Decision-Makers and Influencers in Data Mining

Key Departments

Seniority Level

Not joined surfe yet? Sign up to Surfe today

Buying Processes and Behaviors in Data Mining

Not joined Surfe yet? Get 20 free credits

Prospecting Tips for Selling to Data Mining Companies