To showcase the top big data companies in the United States, our team of 12 industry analysts evaluated each listing using five ranking criteria and insights from over 827 verified client reviews, transforming complex data into actionable insights.
Best United States Data Analytics Company Rankings
707 Companies - Rankings updated: April 01, 2026
DesignRush evaluates the listed big data companies based on demonstrated expertise and verified client reviews to support informed decision-making. Some placements may be paid.
United States ×
Think AI Build Bold Analyze Deep
At Siffrum, we don't just build technology we craft intelligent solutions that drive smarter, faster growth. As a full-stack IT and Software company with a dedicated Data Science wing, we blend innovation with strategy to deliver measurable results. From AI-powered analytics and custom software to scalable [... view Siffrum profile ]- Location
- Wilmington, Delaware
- Number of Employees
- Under 49
- Average Hourly Rate
- $20/hr
- Minimal Budget
- $1,000 - $10,000
Focused on machine manufacturers & industrial engineering businesses
In order to implement intelligent software, advanced analytics, and data platform engineering, we work with industrial engineering firms and machine manufacturers. [... view Saviant Consulting profile ]- Location
- North Port, Florida
- Number of Employees
- 100 - 249
One Stop Solutions for all your development needs.
Hire full stack developers from a top-notch tech company called Hire FullStacks & get next-gen web and mobile app development solutions. [... view Hire FullStacks profile ]- Location
- Atlanta, Georgia
- Number of Employees
- Under 49
- Average Hourly Rate
- $25/hr
- Minimal Budget
- $10,000 - $25,000
- mTouch Labs is a top-tier software development company in India, providing a wide range of web development and mobile app development services since 2011.We are a team of passionate people who solve complex problems through transformation aided by technology. [... view MTouch Labs profile ]
- Location
- Wilmington, Delaware
- Number of Employees
- 50 - 99
- Minimal Budget
- $1,000 - $10,000
“Simplifying doing business with innovative IT solutions”
A Trusted Global Partner for Transforming Businesses with AI, Salesforce & Analytics [... view Cymetrix profile ]- Location
- San Francisco, California
- Number of Employees
- 50 - 99
- Average Hourly Rate
- $50/hr
Empowering Organizations to Thrive with AI and Cutting-Edge Technological Solutions
Dawn IT Services powers B2B growth with smart, cost-efficient solutions that drive measurable results. We specialize in sales outsourcing, sales automation, lead generation, and staff augmentation, helping businesses scale with ease. Our expertise spans robotic process automation, digital transformation, data [... view Dawn IT Services profile ]- Location
- New York City, New York
- Number of Employees
- 100 - 249
- Minimal Budget
- Under $1,000
Your Partner in Digital Transformation
MultiQoS is a software development company offering web and mobile app development solutions. The company's prowess traverses beyond the realm of apps, extending its capabilities to encompass website development, enterprise software solutions, and of course, mobile app development. [... see all MultiQoS reviews ]- Location
- Chicago, Illinois
- Number of Employees
- 100 - 249
- Average Hourly Rate
- $25/hr
- Minimal Budget
- Under $1,000
- Portfolios Count
- 14 Projects Listed
Hiring Guide: How to Choose the Top Big Data Services Providers in the US
How do I choose the best big data company in the US?
Below are essential steps to guide your decision-making process:
- Define your business objectives
Outline the specific outcomes you want from data analytics, whether it is better forecasting or cost reduction. - Assess your current data infrastructure
Review existing data sources, tools, and pain points to determine the support you need, from basic reporting to predictive modeling. - Look for relevant industry experience
Choose companies familiar with your industry's data patterns, and compliance needs to speed onboarding and improve results. - Review technical capabilities and platforms
Make sure the agency is proficient with your tools and frameworks, such as Snowflake, Power BI, Databricks, or AWS. - Evaluate team structure and seniority
Ask about the team's data scientists, engineers, and project managers. A strong team with proven experience will reduce risks and ensure smoother execution. - Check references and case studies
Request examples of past projects and client references to gain insight into the agency's ability to deliver real business impact. - Request a proof of concept or pilot
Before committing, consider running a small pilot project to evaluate their approach, quality of insights, and collaboration style. - Compare pricing models and transparency
Look for clear, understandable pricing. Avoid agencies that can't explain rates or deliverables. - Send a formal RFP
A structured Request for Proposal makes it easier to compare vendors and select the best-fit partner.
Need help getting started?
Visit our Marketplace and leave your project brief. We'll match you with vetted big data analytics firms, completely free of charge.
What should I look for in a provider's track record or case studies?
Focus on measurable impact from large, complex datasets. Look for:
- Relevant use cases: Big data projects in your industry, such as predictive analytics, real-time insights, or automation.
- Measurable outcomes: Cost savings, revenue lift, improved retention, or faster decision-making driven by data. Using advanced analytics, for example, can improve customer satisfaction by 15%.
- Data complexity handled: High-volume, multi-source, or unstructured datasets.
- Scalability: Solutions that adapt as data volume or business needs grow.
- Long-term impact: Sustained insights and ongoing client value.
What are the key KPIs to track for effective big data campaigns?
Effective big data campaigns track KPIs across four levels:
- Data foundation KPIs (3Vs): Data volume processed, number of data sources integrated, data ingestion speed, and data accuracy or error rates. For instance, real-time analytics shortens response time by 60%, cutting it from 30 to just 12 minutes.
- Process efficiency KPIs: Time from data collection to analysis, reporting speed, refresh frequency, and the percentage of business questions answered.
- Business impact KPIs (lagging): Cost savings, revenue lift, customer retention improvements, and operational performance gains directly attributed to data-driven decisions.
- Strategic adoption KPIs (leading): Percentage of business goals supported by analytics, team adoption of dashboards and tools, and data literacy or training effectiveness.
Measure not just data volume, but speed to insight, decision adoption, and measurable business outcomes to keep analytics focused and strategic.
How can you find the best US big data providers on DesignRush that fit your budget?
Our directory features top big data agencies across different budget ranges so you can identify partners that align with your spending expectations.
| High budget: $50,000+ |
|
| Low budget: $25,000-$50,000 |
|
Beyond budget, the DesignRush agency directory lets you filter agencies by location, expertise, reviews, client types, team size, and hourly rates.
What questions should I ask before hiring a US big data analytics company?
Some of the questions you should ask before hiring one of these companies, are:
Its Relevant Background
- What industries do you have the most experience working with?
- As a big data analytics company; do you have in-house data scientists, engineers, and analysts, or do you outsource?
- What certifications or partnerships (e.g., AWS, Microsoft, Databricks) do you hold?
- Have you worked with companies of our size and data maturity level?
Its Services and Processes
- What data analytics tools, platforms, and frameworks do you specialize in?
- What is your approach to data cleaning, integration, and governance?
- How do you ensure data accuracy and compliance with U.S. regulations?
- How do you handle security and access control for sensitive data?
Related to Your Project
- What is the expected timeline to deliver results for a project like ours?
- How would you approach solving our specific data challenge?
- How do you measure the success of your analytics projects?
- Can you support scaling or expanding the solution if our data volume grows?
Why People Trust DesignRush
Rated 4.8 on Google and 4.7 on Trustpilot, DesignRush Agency Directory is a reliable resource for finding big data companies in United States. We owe this to our executive selection team, which follows a strict screening process when featuring agencies on the platform, assessing key performance indicators, like portfolio, client reviews, and industry reputation.
Learn more about DesignRush Agency Ranking Methodology.
Sources
DesignRush sustains a directory of over 40,000 agencies categorized by service category, location, expertise, and reviews. We build our database in two ways:
- Our dedicated team of agency experts actively searches the web for top-performing companies. We then pull information from their websites, online presence, and client testimonials to verify their status and qualifications prior to listing.
- The agencies listed get notified of their profiles on the website and they can choose to claim it or not, which suggests their availability for more collaborations.
Agencies can also reach out to DesignRush and must go through the verification process prior to being listed.
Big Data Services FAQs
What services do big data analytics companies provide?
They provide services that turn structured and unstructured data into decision-making insights, including:
- Data strategy & consulting: Defining business goals, identifying data sources, and planning analytics implementation.
- Data warehousing & integration: Centralizing data from multiple sources for consistent, accessible analysis.
- Business intelligence (BI) & reporting: Providing dashboards, reports, and KPIs that translate raw data into insights.
- Prescriptive & predictive analytics: Using statistical models and machine learning to forecast trends and guide optimal decisions. 55% of organizations use ML and AI in their analytics processes.
- Data visualization: Interactive charts and graphs simplify complex datasets, with over 39% of market revenue coming from this segment.
- Data governance & compliance: Ensure data accuracy, privacy, and regulatory adherence, reducing data breaches by 50% and fraud by 40%, saving an estimated $10 billion annually.
- ETL (Extract, Transform, Load) services: Automate data collection, transformation, and migration.
How much do big data companies in the US charge?
Their hourly rates range from $80–$350, depending on expertise and project scope:
- Entry-level analysts: $80–$100/hr
- Mid-level consultants: $100–$170/hr
- Senior data science experts: $200/hr
Project-based pricing models, based on our data:
- Basic analytics/reporting: $5,000 – $10,000 base rate + $1,000 – $3,000/mo retainer
- Mid-sized predictive projects: $25,000 – $50,000 base rate + $3,000 – $5,000/mo retainer
- Enterprise big data solutions: Over $50,000
Factors affecting pricing:
- Project complexity (real-time analytics, ML models cost more)
- Team seniority and expertise
- Data volume and infrastructure requirements
- Tools and tech stack (e.g., Databricks, Snowflake)
- Engagement length (long-term contracts may reduce hourly cost)
- Location and sourcing (U.S.-based firms typically charge more than offshore)
How long does it take to see results from big data campaigns?
Most campaigns show early results within the first few months, while long-term initiatives deliver the greatest value as insights compound over time.
| Timeline to Results | Typical Duration | What Can You Expect |
| Immediate wins | 1-3 months | Data extraction, dashboards, automated reports, and early AI integrations |
| Measurable insights | 4-12 months | Advanced analysis, model refinement, and insights that begin influencing strategic decisions. |
| Long-term impact | 12+ months | Continuous optimization and compounding ROI from large-scale big data programs and enterprise analytics initiatives. |
What industries do big data analytics companies serve in the US?
They mostly serve the following industries:
- Healthcare: Personalizes treatments, reduces readmissions, and improves efficiency. The U.S. healthcare analytics market is projected to reach $79.23B by 2028 (CAGR 28.9%).
- Financial Services: Supports fraud detection, risk scoring, compliance, and personalized offerings. Over 91% of financial firms use analytics, representing 32% of the global market.
- Retail & eCommerce: Optimizes pricing, predicts demand, and personalizes marketing. Companies using advanced analytics see 5–6% higher sales and profit growth.
- Manufacturing & Supply Chain: Enables predictive maintenance, inventory optimization, and process automation.
- Telecommunications: Manages network traffic, reduces churn, and improves targeting. The telecom analytics market is expected to reach $155B by 2032 (50%+ CAGR).
- Media and Entertainment: Streaming and gaming companies use big data to personalize content, optimize recommendations, and increase viewer engagement. Netflix, for example, uses analytics to guide viewing and save ~$1B annually.
How are big data analytics services different from traditional business intelligence (BI)?
- Traditional BI focuses on reporting and dashboards built from historical, structured data. They help businesses track performance and understand what has already happened.
- Big data companies handle much larger and more complex datasets, including unstructured and real-time data. It is used to identify patterns, predict outcomes, and support advanced decision-making.
Simply put, BI looks at past performance, while big data analytics focuses on scale, complexity, and future insights.
About The Author and Expert Reviewer
Selina Garcia has authored 500+ articles and edited 50+ published books in economics, law, and history. Her unique blend of experiences allows her to approach content creation from a well-rounded perspective. Currently, Selina applies her expertise to producing insightful articles on IT, software, and applications for DesignRush.
Robin Fishley is a digital professional with over 20 years of experience in programming, website architecture, and data optimization. Twice honored as Most Innovative Employee at his previous agency, he excelled in leadership roles across SEO, research, analytics, and strategy. At Saatchi & Saatchi, where he was the Director of Search and Data, he developed a successful Big Data analysis tool and provided expert consulting for renowned clients like P&G, Toyota, and VISA. A valuable asset to DesignRush, he used his technical background to drive success for the company's digital initiatives.
Latest Trends Related to Big Data Analytics
