Data analytics outsourcing companies offer a wide range of services: data visualization, predictive analytics, data engineering, natural text processing, etc.
Everybody knows about the juggernauts of the data analytics outsourcing industry like Accenture, Tata Consulting Group and IBM. However, outsourcing your data analytics needs to the companies is not always the best option.
In this article we will cover the leading outsourcing firms for data analytics and what they specialize in. We will also discuss the full range of data analytics solutions that these companies provide and advise for how to choose your data analytics partner.
The data analytics field has so many branches that it is nearly impossible for a single company to have deep expertise in all of them. As a result, data analytics outsourcing companies usually specialize in a single area of data analytics and have a more superficial understanding of all the others.
The common solutions provided by data analytics outsourcing companies are:
As you can see, every type of data analytics requires skills in different technologies which means that a single firm can not be an expert in all of them. It is therefore important to identify which type of analytics you need and know which data analytics outsourcing company specializes in this type of analytics.
Choosing a data analytics outsourcing provider for your project is an important decision. When you get outsourced analytics help from a qualified partner, you start getting your first actionable insights within first few weeks. However, choosing poorly leads to excessive project management, a sharp increase in costs and unnecessary delays.
We recommend paying attention to 4 key factors when choosing your data analytics outsourcing provider: technical expertise, good reputation, proven track record and reasonable pricing.
1) Technical Expertise
Make sure that the company you are evaluating has technical experience in your preferred tool stack. For example all of our Power BI developers are professionally certified in Power BI by Microsoft. Similar certifications exist for other data analytics technologies.
Ideally you would find a company that also has experience in analyzing data from your sources. This way your data analytics outsourcing partner would already be familiar with your data and be able to produce the analysis quicker and more efficiently.
2) Good Reputation
It is important to note that even technically-gifted developers can provide a bad service. We recommend to check reviews and testimonials to make sure that you are choosing a company that cares deeply about customer experience.
Reviews are a good indication of the level of service that you can expect. Ideally you want to see 50+ reviews and the average rating of 4.9+/5. For example at Vidi Corp we have 200+ verified reviews of our data analytics services across different platforms.
3) Proven Track Record
It is important to check case studies when choosing a data analytics outsourcing company. Ideally those case studies would be for other companies in your industry and resemble your own needs very closely.
It is also a good sign if a company you are evaluating has a lot of case studies as it shows their deep experience in data analytics and a proven track record of successful projects.
4) Reasonable Pricing
Reasonable doesn’t always mean low. The pricing of the data analytics outsourcing services should be based on the complexity of analysis that you want to create.
If you want to create simple analysis that takes a lot of time put together but requires little skill, you can get away with paying $10-20 per hour to a virtual assistant company.
If the analysis you want to create requires advanced technical skills and experience in the field, you are probably looking for a mixture of experience and good value. In this case you would likely work with data analytics firms in the $75-100 per hour range.
If you are looking for unique analysis that very few companies have created before, you are probably looking to hire the smartest data analyst out there. In this case you would pay a high premium of $200+ per hour.
When exploring top-rated data analytics services for outsourcing, businesses should look for providers that combine advanced technology with proven industry expertise to deliver measurable results. Leading outsourcing firms for data analytics typically offer a wide range of services, including big data processing, predictive analytics, business intelligence reporting, and AI-driven insights tailored to specific business goals.
Check out the best data analytics outsourcing companies.
Website: https://vidi-corp.com/
Vidi Corp is ranked the world’s #1 Business Intelligence consultancy by G2. The team has delivered 1,000+ projects for 600+ international clients, including Google, Heineken, and the UK Ministry of Defence, and has earned dozens of awards, notably being named Best Data Analytics & Automation Consultancy at the UK Enterprise Awards.
How Vidi Corp differs from competitors
Website: https://quantiphi.com
Award-winning AI-first digital engineering firm Quantiphi helps businesses accelerate their digital transformation. As a Google partner of the year, they have a proven track record of delivering AI-driven data analytics solutions computer vision, NLP and time series forecasting.
How Quantiphi differs from competitors
Website: https://stape.io/
Stape is a well-known company in the Google Analytics space for their server-side tracking software. However, on top of their software they also provide packaged Google Analytics support including Google Analytics setups, audits and maintenance. They provide web analytics services through their Stape care plan which is starting from $600 set up fee and $1,000 per year retainer fee. The company reports that they have handled 2,000+ Google Analytics setups.
How Stape is different from competitors:
Website: https://www.accenture.com/us-en
Accenture is one of the most well-known data analytics outsourcing companies in the world with almost 800,000 employees worldwide. Having so many consultants in house gives them advantage in having a breadth of experience to deliver projects that can benefit from it. For example, if you are an enterprise-level client and you need help on a project that requires business intelligence, AI, data engineering and automation, Accenture may be a good fit.
How Accenture is different from competitors:
Website: https://www.mentatanalytics.co/
Mentat is the most prominent SaaS data analytics outsourcing company and a Mixpanel partner of the year 2022. They have the skills in most important SaaS data analytics platforms like Metabase, Amplitude and Mixpanel which clearly shows their specialization in product analytics.
How Mentat is different from competitors:
Website: https://fastdatascience.com/
If you have a large amount of text data that you need to analyze, Fast Data Science might be the right data analytics outsourcing provider for you. Even though they provide a wide range of data science services, their NLP offerings look especially impressive.
They are a UK-based company hiring most of their team from Oxford and Cambridge so you know that they when you work with them the level of talent will be exceptional.
How Fast Data Science is different from competitors:
Website: https://ventionteams.com
If you want to analyze the data from images or videos, Venition might be the right data analytics outsourcing company for you. They offer a wide range of computer vision solutions including visual search, facial recognition, contextual analysis, etc.
Their case studies highlight in-depth experience with computer vision libraries like OpenCV and frameworks like Tensorflow.
How Vention is different from competitors:
Website: https://xebia.com/
GetInData is an expert in real-time analytics platforms and big data engineering. If you are in an industry where it is important to get real-time data like financial trading or cybersecurity, GetInData might be a good option to consider.
Their technical expertise in Apache Kafka, Spark, Flink, Hadoop, and Kubernetes enables businesses to create adaptable, scalable infrastructures without being locked into a single vendor.
How GetInData is different from competitors:
Website: https://aimleap.com/
AIMLEAP is primarily a data analytics outsourcing company specializing in AI but they are a great choice where your projects require a lot of data engineering work. If you need to scrape data from publicly avaialble websites or build data pipelines with enterprise-level security, they might be the choice for you.
How AIMLEAP is different from competitors:
Website: https://www.exlservice.com/
EXL is a multinational operations management and analytics outsourcing firm that helps companies elevate performance and customer engagement by fusing domain knowledge with cutting-edge data analytics.
If you are working in a large corporation and planning to become a fully data-driven organization, EXL has a number of solutions to help you prepare. EXL has been recognised as a top AI development firm by Forester Consulting which is a very prestegious award.
How EXL is different from competitors:
Pricing for outsourcing data analytics varies with scope, complexity, security requirements, and whether you want a one-off build or an ongoing managed service. Use the structures below to compare apples to apples and to keep surprises out of your Statement of Work (SoW).
The table below shows the factors driving the cost of outsourcing data analytics.
Dimension | Key Considerations | Impact on Delivery/Cost |
---|---|---|
Problem scope & complexity | Number and diversity of data sources Data quality issues Depth of modeling – Real-time vs batch needs | More sources, quality issues, and advanced modeling raise complexity and timeline |
Team composition & seniority | Architect Data Engineer (DE) BI Analyst Data Scientist (DS) QA Delivery/PM | Advanced skills and senior team members increase quality, mitigate risk, and impact cost |
Compliance & security | GDPR/CCPA HIPAA/PCI Data residency Audit logging and traceability | Regulated industries/protected data drive higher compliance, requiring specialist expertise |
Delivery speed | Rush fees Parallel staffing | Tight deadlines increase resource requirements and overall project cost |
Onshore vs near/offshore | Time-zone overlap Language skills | Onshore maximises alignment and communication, but is more expensive; near/offshore cuts costs |
Enablement & handover depth | Documentation Training Shadowing | Comprehensive handover adds upfront effort, but minimises long-term support dependency |
Time & Materials: Hourly or daily rates per role (e.g., Data Engineer, Analyst, Data Scientist).
You can check the hourly rates here
Fixed-price projects: Scope is tightly defined, making them suitable for migrations or dashboard packs.
Retainers / Managed services: Monthly fee for a defined velocity (e.g., 2–4 sprints/month) and SLA.
Outcome-based add-ons: Performance bonuses tied to KPIs (e.g., reduced churn, improved forecast accuracy).
For growth-focused teams, data analytics outsourcing brings meaningful cost savings, deep expertise, and flexible scaling that supports rapid change.
Outsourcing minimises recruitment, ongoing training, and infrastructure investments, allowing businesses to convert large fixed expenses into manageable, variable costs. This ensures financial flexibility and rapid ROI, as organisations can focus resources on strategic growth initiatives rather than maintaining extensive in-house capabilities.
A top data analytics agency like brings global talent pools and advanced technology stacks to the table. This specialist expertise in data analytics and visualisation is often inaccessible or cost-prohibitive for firms building from scratch internally, especially in tight labour markets.
Business data needs fluctuate. Outsourcing empowers companies to quickly scale analytics resources up or down based on project loads, seasonality, or sudden market opportunities. This dynamic resourcing is virtually impossible at the same speed or cost in traditional hiring models.
Outsourcing partners streamline analytics workflows, often delivering actionable insights faster than in-house teams. With established processes, businesses experience responsive, data-backed decision-making to stay ahead of competitors.
Specialised analytics firms are experienced in privacy protocols, robust data governance, and industry-specific compliance standards. Businesses can be confident that their sensitive information is protected under evolving regulatory frameworks.
By shifting data processing burdens off internal teams, companies are freed to innovate, drive customer loyalty, and enhance their core business functions. Outsourcing elevates overall productivity and facilitates growth initiatives that directly impact the bottom line.
Data analytics outsourcing fosters a culture of innovation. With more capacity to deploy the latest technologies like AI and big data, companies can transform raw information into business value, fuelling differentiation in competitive markets.
For organisations of any size, outsourcing data analytics is often a practical way to keep teams focused on core competencies and day-to-day operations. With clear goals and strong governance, many industry practitioners view analytics outsourcing as a sound strategy for most companies.
The key benefits include cost efficiency, access to expertise, scalability and flexibility
The top data analytics providers include Vidi Corp Ltd, Wipro and Accenture
One of the key pros of outsourcing data analytics is access to specialised expertise and advanced technologies without the high cost of building an in-house team. However, the cons of outsourcing data analytics include reduced control over data handling, which may raise concerns around security, compliance, and data privacy.