资料探勘工具市场－全球产业规模、份额、趋势、机会和预测（按组件、按部署模式、按行业垂直、按地区和竞争细分，2020-2030 年预测）

2024 年全球资料探勘工具市场价值为 12.3 亿美元，预计到 2030 年将达到 24.5 亿美元，预测期内复合年增长率为 12.03%。

资料探勘工具市场是指软体解决方案和服务市场，这些解决方案和服务使企业能够分析大量结构化和非结构化资料，从而发现隐藏的模式、关联性和可操作的洞察，从而支持策略决策、风险管理和营运效率。这些工具利用聚类、分类、回归、关联规则挖掘和异常检测等技术来处理复杂的资料集，将原始资料转化为驱动商业智慧的有意义的资讯。资料探勘工具越来越多地应用于各个垂直行业，包括银行、金融服务和保险；医疗保健；零售和电子商务；製造业；资讯科技；能源和公用事业；以及政府和公共部门组织。

在金融领域，这些工具用于检测诈欺、评估信用风险和优化投资组合；而医疗保健机构则利用它们进行患者资料管理、疾病预测和个人化治疗计划。零售商和电子商务公司依靠资料探勘来了解客户行为、改善库存管理并设计有针对性的行销活动。製造业和能源产业则使用这些解决方案进行预测性维护、流程最佳化和资源管理。市场的成长是由来自数位平台、物联网设备、社交媒体和企业系统的资料的指数级增长所驱动的，这催生了对高级分析技术提取有意义洞察的迫切需求。

此外，人工智慧和机器学习与资料探勘工具的整合提高了预测准确性、自动化程度和可扩展性，使这些解决方案更有效率且易于存取。基于云端的部署模型透过为各种规模的企业提供灵活、经济高效且可扩展的基础设施，进一步支援市场扩张。政府和组织也在投资资料治理、网路安全和合规计划，这进一步鼓励了强大的资料探勘解决方案的采用。随着组织持续拥抱数位转型并优先考虑数据驱动的决策，资料探勘工具市场预计将持续增长，新兴经济体的采用率不断提高、技术持续创新以及资料作为战略资产的日益被认可，这些都将在预测期内推动市场长期扩张。

关键市场驱动因素

资料量和速度的不断增长推动了对高级资料探勘工具的需求

主要市场挑战

资料隐私和监管合规挑战

主要市场趋势

人工智慧与机器学习在资料探勘中的融合

目录

第 1 章：产品概述

第二章：研究方法

第三章：执行摘要

第四章：顾客之声

第五章：全球资料探勘工具市场展望

• 市场规模和预测
  • 按价值
• 市场占有率和预测
  • 按组件（软体、服务）
  • 依部署模式（本地、云端）
  • 按行业垂直划分（银行、金融服务和保险、资讯科技和电信、医疗保健、零售和电子商务、製造业、政府和公共部门、能源和公用事业、其他）
  • 按地区（北美、欧洲、南美、中东和非洲、亚太地区）
• 按公司分类（2024 年）
• 市场地图

第六章：北美资料探勘工具市场展望

• 市场规模和预测
• 市场占有率和预测
• 北美：国家分析
  • 美国
  • 加拿大
  • 墨西哥

第七章：欧洲资料探勘工具市场展望

• 市场规模和预测
• 市场占有率和预测
• 欧洲：国家分析
  • 德国
  • 法国
  • 英国
  • 义大利
  • 西班牙

第八章：亚太资料探勘工具市场展望

• 市场规模和预测
• 市场占有率和预测
• 亚太地区：国家分析
  • 中国
  • 印度
  • 日本
  • 韩国
  • 澳洲

第九章：中东和非洲资料探勘工具市场展望

• 市场规模和预测
• 市场占有率和预测
• 中东和非洲：国家分析
  • 沙乌地阿拉伯
  • 阿联酋
  • 南非

第 10 章：南美洲资料探勘工具市场展望

• 市场规模和预测
• 市场占有率和预测
• 南美洲：国家分析
  • 巴西
  • 哥伦比亚
  • 阿根廷

第 11 章：市场动态

• 驱动程式
• 挑战

第 12 章：市场趋势与发展

• 合併与收购（如有）
• 产品发布（如有）
• 最新动态

第十三章：公司简介

• IBM Corporation
• SAS Institute Inc.
• Oracle Corporation
• Microsoft Corporation
• SAP SE
• Teradata Corporation
• RapidMiner Inc.
• KNIME GmbH
• TIBCO Software Inc.
• Alteryx Inc.

第 14 章：策略建议

第15章调查会社について・免责事项

Global Data Mining Tools Market was valued at USD 1.23 billion in 2024 and is expected to reach USD 2.45 billion by 2030 with a CAGR of 12.03% during the forecast period.

The Data Mining Tools Market refers to the market for software solutions and services that enable organizations to analyze vast amounts of structured and unstructured data to uncover hidden patterns, correlations, and actionable insights that support strategic decision-making, risk management, and operational efficiency. These tools utilize techniques such as clustering, classification, regression, association rule mining, and anomaly detection to process complex datasets, transforming raw data into meaningful information that drives business intelligence. Data mining tools are increasingly adopted across diverse industry verticals, including banking, financial services, and insurance; healthcare; retail and e-commerce; manufacturing; information technology; energy and utilities; and government and public sector organizations.

In the financial sector, these tools are used to detect fraud, assess credit risk, and optimize investment portfolios, while healthcare organizations leverage them for patient data management, disease prediction, and personalized treatment planning. Retailers and e-commerce companies rely on data mining to understand customer behavior, improve inventory management, and design targeted marketing campaigns. Manufacturing and energy sectors use these solutions for predictive maintenance, process optimization, and resource management. The market's growth is being driven by the exponential increase in data generation from digital platforms, IoT devices, social media, and enterprise systems, which creates a critical need for advanced analytics to extract meaningful insights.

Additionally, the integration of artificial intelligence and machine learning with data mining tools enhances predictive accuracy, automation, and scalability, making these solutions more efficient and accessible. Cloud-based deployment models further support market expansion by offering flexible, cost-effective, and scalable infrastructure for enterprises of all sizes. Governments and organizations are also investing in data governance, cybersecurity, and compliance initiatives, which further encourage the adoption of robust data mining solutions. As organizations continue to embrace digital transformation and prioritize data-driven decision-making, the Data Mining Tools Market is expected to experience sustained growth, with increasing adoption across emerging economies, continuous technological innovation, and the rising recognition of data as a strategic asset driving long-term market expansion over the forecast period.

Key Market Drivers

Increasing Data Volume and Velocity Driving Demand for Advanced Data Mining Tools

In the contemporary business landscape, the exponential surge in data generation across various sectors has emerged as a pivotal force propelling the Data Mining Tools Market forward, compelling organizations to seek sophisticated solutions capable of extracting actionable insights from vast, unstructured datasets. As enterprises grapple with the deluge of information emanating from diverse sources such as social media platforms, Internet of Things devices, e-commerce transactions, and enterprise resource planning systems, the necessity for robust data mining tools becomes indispensable to maintain competitive advantage and operational efficiency.

These tools enable businesses to sift through petabytes of data, identifying patterns, correlations, and anomalies that would otherwise remain obscured, thereby facilitating informed decision-making processes that drive revenue growth and cost optimization. For instance, in the retail industry, data mining tools analyze customer purchase histories and browsing behaviors to personalize marketing strategies, resulting in enhanced customer engagement and loyalty retention rates. Similarly, in the healthcare sector, these tools process electronic health records and genomic data to predict disease outbreaks and personalize treatment protocols, ultimately improving patient outcomes and reducing healthcare expenditures. The financial services domain leverages data mining to detect fraudulent activities in real-time by examining transaction patterns, mitigating risks that could lead to substantial monetary losses.

Moreover, the manufacturing industry employs these tools to optimize supply chain logistics through predictive maintenance models derived from sensor data, minimizing downtime and enhancing productivity. The velocity at which data is generated-often in real-time-further amplifies the demand for advanced data mining capabilities, as traditional analytical methods falter under the pressure of high-speed data streams, necessitating tools equipped with stream processing and real-time analytics features. This rapid data influx is not merely a challenge but an opportunity for innovation, where companies investing in scalable data mining infrastructures can uncover hidden market trends, forecast consumer demands, and adapt swiftly to economic shifts.

The integration of big data technologies with data mining tools has revolutionized how organizations handle structured and unstructured data, allowing for the amalgamation of disparate data sources into cohesive analytical frameworks that yield comprehensive business intelligence. As global digital transformation initiatives accelerate, the Data Mining Tools Market benefits from the imperative to harness this data tsunami, with enterprises recognizing that untapped data represents untapped potential revenue streams. Regulatory pressures also play a role, as compliance with data handling standards requires meticulous mining to ensure accuracy and transparency in reporting.

Furthermore, the advent of edge computing has decentralized data processing, enabling data mining at the source to reduce latency and enhance responsiveness, particularly in industries like telecommunications and autonomous vehicles where split-second decisions are critical. The proliferation of mobile devices and wearable technologies contributes to this data explosion, generating continuous streams of location-based and biometric data that data mining tools can transform into valuable insights for targeted advertising and health monitoring applications. In the energy sector, data mining aids in analyzing consumption patterns to optimize grid management and promote sustainable practices. The challenge of data silos within organizations underscores the need for integrated data mining platforms that can unify disparate datasets, fostering cross-departmental collaboration and holistic strategic planning.

As artificial intelligence evolves, its synergy with data mining tools amplifies their efficacy, enabling automated pattern recognition and anomaly detection at scales previously unattainable. The economic implications are profound, with studies indicating that effective data mining can boost profitability by uncovering inefficiencies and market opportunities. In emerging economies, the adoption of data mining tools is accelerating due to increasing internet penetration and digital literacy, opening new avenues for market expansion. Cybersecurity threats, amplified by data volume, necessitate advanced mining techniques to identify vulnerabilities and preempt attacks.

Key Market Challenges

Data Privacy and Regulatory Compliance Challenges

One of the foremost challenges faced by the Data Mining Tools Market is ensuring data privacy and adhering to increasingly stringent regulatory frameworks. As organizations collect and process massive volumes of structured and unstructured data, including personally identifiable information, they are confronted with legal obligations to comply with regulations such as the General Data Protection Regulation, the California Consumer Privacy Act, and various industry-specific compliance mandates. Failure to comply with these regulations can result in substantial financial penalties, reputational damage, and operational disruptions. The challenge is compounded by the global nature of data operations, where organizations must navigate a complex matrix of international laws, local data sovereignty requirements, and sector-specific guidelines, all of which may differ in their interpretation and enforcement.

Implementing robust data anonymization, encryption, and access control mechanisms is critical to protecting sensitive information while maintaining the integrity of data analytics processes. Moreover, ensuring compliance requires continuous monitoring, auditing, and updating of data governance policies, which increases operational complexity and resource expenditure. Organizations must also contend with the challenge of balancing the need for comprehensive data analysis with the ethical responsibility to protect customer and employee privacy. Any lapse in safeguarding sensitive information can undermine stakeholder trust and negatively impact market credibility.

Consequently, vendors and users of data mining tools must invest in advanced security frameworks, automated compliance solutions, and staff training programs to navigate these regulatory pressures effectively. The evolving landscape of privacy regulations, coupled with the global nature of data flows, underscores the significance of this challenge and highlights the need for integrated strategies that align technological capabilities with regulatory obligations, ensuring both data utility and legal compliance.

Key Market Trends

Integration of Artificial Intelligence and Machine Learning in Data Mining

One of the most significant trends shaping the Data Mining Tools Market is the increasing integration of artificial intelligence and machine learning technologies into analytics platforms. Organizations are increasingly leveraging these advanced technologies to enhance the capabilities of data mining tools, enabling automated detection of patterns, predictive modeling, and advanced anomaly detection. Unlike traditional analytics approaches that require manual intervention and rule-based algorithms, AI-powered data mining solutions can learn from historical data, identify correlations, and generate actionable insights with minimal human oversight.

This trend is particularly relevant for sectors such as financial services, healthcare, retail, and manufacturing, where rapid decision-making and operational efficiency are critical. For instance, in the banking, financial services, and insurance sector, machine learning algorithms within data mining tools can detect fraudulent transactions in real time, assess credit risk with greater accuracy, and optimize investment strategies. In healthcare, AI integration allows for predictive patient outcome analysis, early disease detection, and optimization of treatment protocols based on large-scale patient datasets. Furthermore, the combination of AI and machine learning enhances the scalability of data mining tools, allowing enterprises to handle exponentially growing volumes of structured and unstructured data generated from digital platforms, Internet of Things devices, and social media channels.

Key Market Players

• IBM Corporation
• SAS Institute Inc.
• Oracle Corporation
• Microsoft Corporation
• SAP SE
• Teradata Corporation
• RapidMiner Inc.
• KNIME GmbH
• TIBCO Software Inc.
• Alteryx Inc.

Report Scope:

In this report, the Global Data Mining Tools Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Data Mining Tools Market, By Component:

• Software
• Services

Data Mining Tools Market, By Deployment Mode:

• On-Premise
• Cloud

Data Mining Tools Market, By Industry Vertical:

• Banking, Financial Services, and Insurance
• Information Technology and Telecommunications
• Healthcare
• Retail and E-commerce
• Manufacturing
• Government and Public Sector
• Energy and Utilities,
• Others

Data Mining Tools Market, By Region:

• North America
  • United States
  • Canada
  • Mexico
• Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
• South America
  • Brazil
  • Argentina
  • Colombia
• Asia-Pacific
  • China
  • India
  • Japan
  • South Korea
  • Australia
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • South Africa

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Data Mining Tools Market.

Available Customizations:

Global Data Mining Tools Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

• 1.1. Market Definition
• 1.2. Scope of the Market
  • 1.2.1. Markets Covered
  • 1.2.2. Years Considered for Study
  • 1.2.3. Key Market Segmentations

2. Research Methodology

• 2.1. Objective of the Study
• 2.2. Baseline Methodology
• 2.3. Key Industry Partners
• 2.4. Major Association and Secondary Sources
• 2.5. Forecasting Methodology
• 2.6. Data Triangulation & Validation
• 2.7. Assumptions and Limitations

3. Executive Summary

• 3.1. Overview of the Market
• 3.2. Overview of Key Market Segmentations
• 3.3. Overview of Key Market Players
• 3.4. Overview of Key Regions/Countries
• 3.5. Overview of Market Drivers, Challenges, and Trends

4. Voice of Customer

5. Global Data Mining Tools Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Component (Software, Services)
  • 5.2.2. By Deployment Mode (On-Premise, Cloud)
  • 5.2.3. By Industry Vertical (Banking, Financial Services, and Insurance, Information Technology and Telecommunications, Healthcare, Retail and E-commerce, Manufacturing, Government and Public Sector, Energy and Utilities, Others)
  • 5.2.4. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)
• 5.3. By Company (2024)
• 5.4. Market Map

6. North America Data Mining Tools Market Outlook

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Component
  • 6.2.2. By Deployment Mode
  • 6.2.3. By Industry Vertical
  • 6.2.4. By Country
• 6.3. North America: Country Analysis
  • 6.3.1. United States Data Mining Tools Market Outlook
    • 6.3.1.1. Market Size & Forecast
      • 6.3.1.1.1. By Value
    • 6.3.1.2. Market Share & Forecast
      • 6.3.1.2.1. By Component
      • 6.3.1.2.2. By Deployment Mode
      • 6.3.1.2.3. By Industry Vertical
  • 6.3.2. Canada Data Mining Tools Market Outlook
    • 6.3.2.1. Market Size & Forecast
      • 6.3.2.1.1. By Value
    • 6.3.2.2. Market Share & Forecast
      • 6.3.2.2.1. By Component
      • 6.3.2.2.2. By Deployment Mode
      • 6.3.2.2.3. By Industry Vertical
  • 6.3.3. Mexico Data Mining Tools Market Outlook
    • 6.3.3.1. Market Size & Forecast
      • 6.3.3.1.1. By Value
    • 6.3.3.2. Market Share & Forecast
      • 6.3.3.2.1. By Component
      • 6.3.3.2.2. By Deployment Mode
      • 6.3.3.2.3. By Industry Vertical

7. Europe Data Mining Tools Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Component
  • 7.2.2. By Deployment Mode
  • 7.2.3. By Industry Vertical
  • 7.2.4. By Country
• 7.3. Europe: Country Analysis
  • 7.3.1. Germany Data Mining Tools Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Component
      • 7.3.1.2.2. By Deployment Mode
      • 7.3.1.2.3. By Industry Vertical
  • 7.3.2. France Data Mining Tools Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Component
      • 7.3.2.2.2. By Deployment Mode
      • 7.3.2.2.3. By Industry Vertical
  • 7.3.3. United Kingdom Data Mining Tools Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Component
      • 7.3.3.2.2. By Deployment Mode
      • 7.3.3.2.3. By Industry Vertical
  • 7.3.4. Italy Data Mining Tools Market Outlook
    • 7.3.4.1. Market Size & Forecast
      • 7.3.4.1.1. By Value
    • 7.3.4.2. Market Share & Forecast
      • 7.3.4.2.1. By Component
      • 7.3.4.2.2. By Deployment Mode
      • 7.3.4.2.3. By Industry Vertical
  • 7.3.5. Spain Data Mining Tools Market Outlook
    • 7.3.5.1. Market Size & Forecast
      • 7.3.5.1.1. By Value
    • 7.3.5.2. Market Share & Forecast
      • 7.3.5.2.1. By Component
      • 7.3.5.2.2. By Deployment Mode
      • 7.3.5.2.3. By Industry Vertical

8. Asia Pacific Data Mining Tools Market Outlook

• 8.1. Market Size & Forecast
  • 8.1.1. By Value
• 8.2. Market Share & Forecast
  • 8.2.1. By Component
  • 8.2.2. By Deployment Mode
  • 8.2.3. By Industry Vertical
  • 8.2.4. By Country
• 8.3. Asia Pacific: Country Analysis
  • 8.3.1. China Data Mining Tools Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1. By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1. By Component
      • 8.3.1.2.2. By Deployment Mode
      • 8.3.1.2.3. By Industry Vertical
  • 8.3.2. India Data Mining Tools Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1. By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1. By Component
      • 8.3.2.2.2. By Deployment Mode
      • 8.3.2.2.3. By Industry Vertical
  • 8.3.3. Japan Data Mining Tools Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1. By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1. By Component
      • 8.3.3.2.2. By Deployment Mode
      • 8.3.3.2.3. By Industry Vertical
  • 8.3.4. South Korea Data Mining Tools Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Component
      • 8.3.4.2.2. By Deployment Mode
      • 8.3.4.2.3. By Industry Vertical
  • 8.3.5. Australia Data Mining Tools Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Component
      • 8.3.5.2.2. By Deployment Mode
      • 8.3.5.2.3. By Industry Vertical

9. Middle East & Africa Data Mining Tools Market Outlook

• 9.1. Market Size & Forecast
  • 9.1.1. By Value
• 9.2. Market Share & Forecast
  • 9.2.1. By Component
  • 9.2.2. By Deployment Mode
  • 9.2.3. By Industry Vertical
  • 9.2.4. By Country
• 9.3. Middle East & Africa: Country Analysis
  • 9.3.1. Saudi Arabia Data Mining Tools Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1. By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1. By Component
      • 9.3.1.2.2. By Deployment Mode
      • 9.3.1.2.3. By Industry Vertical
  • 9.3.2. UAE Data Mining Tools Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1. By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1. By Component
      • 9.3.2.2.2. By Deployment Mode
      • 9.3.2.2.3. By Industry Vertical
  • 9.3.3. South Africa Data Mining Tools Market Outlook
    • 9.3.3.1. Market Size & Forecast
      • 9.3.3.1.1. By Value
    • 9.3.3.2. Market Share & Forecast
      • 9.3.3.2.1. By Component
      • 9.3.3.2.2. By Deployment Mode
      • 9.3.3.2.3. By Industry Vertical

10. South America Data Mining Tools Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Component
  • 10.2.2. By Deployment Mode
  • 10.2.3. By Industry Vertical
  • 10.2.4. By Country
• 10.3. South America: Country Analysis
  • 10.3.1. Brazil Data Mining Tools Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Component
      • 10.3.1.2.2. By Deployment Mode
      • 10.3.1.2.3. By Industry Vertical
  • 10.3.2. Colombia Data Mining Tools Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Component
      • 10.3.2.2.2. By Deployment Mode
      • 10.3.2.2.3. By Industry Vertical
  • 10.3.3. Argentina Data Mining Tools Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Component
      • 10.3.3.2.2. By Deployment Mode
      • 10.3.3.2.3. By Industry Vertical

11. Market Dynamics

• 11.1. Drivers
• 11.2. Challenges

12. Market Trends and Developments

• 12.1. Merger & Acquisition (If Any)
• 12.2. Product Launches (If Any)
• 12.3. Recent Developments

13. Company Profiles

• 13.1. IBM Corporation
  • 13.1.1. Business Overview
  • 13.1.2. Key Revenue and Financials
  • 13.1.3. Recent Developments
  • 13.1.4. Key Personnel
  • 13.1.5. Key Product/Services Offered
• 13.2. SAS Institute Inc.
• 13.3. Oracle Corporation
• 13.4. Microsoft Corporation
• 13.5. SAP SE
• 13.6. Teradata Corporation
• 13.7. RapidMiner Inc.
• 13.8. KNIME GmbH
• 13.9. TIBCO Software Inc.
• 13.10. Alteryx Inc.

14. Strategic Recommendations

15. About Us & Disclaimer