Data analytics costs for a business can be between $1,000 USD and $100,000 USD per year depending on many factors. The total cost is made of the payments to data analysts and licensing costs for data analytics tools.
This article breaks down everything you need to know about data analytics costs: pricing models, service types, and so on, so you can have the highest ROI.
By the end of it, you will hopefully be able to understand a ballpark estimate of the costs that you need to budget for.
The costs associated with data analytics projects can vary significantly depending on four primary factors: project scope, technology used, technical expertise, and specific requirements.
The following diagram and explanations illustrate how each of these factors impacts overall project costs.
The cost of data analytics can be high or low depending on a couple of factors, some of which include:
The project scope determines how many hours are necessary to complete the data analytics project. Naturally, the more hours are needed to complete it, the higher the cost is going to be. The main project scope factors affecting the data analytics cost are:
To give you an example, creating a 1-2 page KPI dashboard with the data from Excel would cost you around $1,000 USD.
However, if you want to create a fully automated KPI dashboard from Xero, Clickup, Google Analytics and Google Ads, a project like this would cost $3,500-7,000 USD.
Being detailed with your project scope often helps to more accurately estimate the project cost and ensure that they do not increase unexpectedly. If you want to be really detailed, you can prepare an implementation plan and disuss it with your data analysts.
Sometimes you can spend more money on technology but save money on payments to the data analysts. The technology that goes into a data analytics project is:
For example, if you wanted to analyse your Clickup data in Power BI, you would need a Clickup Power BI integration which is $1000 per year and a license to Power BI which is $14 per user per month.
Data analytics consultants that create KPI dashboards usually charge $75-150 USD per hour. This level of expertise is sufficient for most small and medium businesses.
If you want to work with a data scientist to create predictive analytics or analyse image and video footage, be prepared to pay more. We find that this level of technical expertise is usually only needed for enterprise clients.
When it comes to data analytics, you can either engage data analytics consultants or hire a data analyst in-house.
Consultants usually work on an hourly or a fixed price basis whereas in-house data analysts would come at a recurring salary cost. It is important that the pricing model that you choose suits the project that you are working on.
Fixed pricing offers a predictable cost structure. Businesses pay a set fee for a defined set of services, ideal for companies with well-scoped projects and limited budgets. This model simplifies planning, provides financial certainty, and minimises billing surprises.
In our experience fixed-price projects start from $1,000 USD and most of them can be done under $10,000. The most expensive enterprise data analytics project that we have done was $100,000 but this was for 1 year of working every week.
Fixed pricing can be restrictive. If the scope of analysis expands or unforeseen data complexities arise, the service provider may be limited in how much support they can offer without renegotiation. A predetermined, set price for a defined scope of work or service package, regardless of usage or complexity.
Features:
Advantages:
Disadvantages:
If the scope of your project is not fully defined, an hourly data analytics pricing model would work better. Working on an hourly basis is better if you are looking to iterate multiple times until you reach the final deliverable. If your project requires quick delivery, it often easier to work on an hourly basis instead of negotiating separately on every new requirements.
The standard hourly rate for data analytics services is $75-120 USD per hour. If this is above your budget, you can look for beginner freelancers or offshore services if this is above your budget. This involves more risk and can compromise the speed of delivery but is still an option to consider.
The downside? Variable pricing can lead to cost unpredictability. Without careful monitoring, expenses can quickly escalate, especially in organisations with growing or poorly managed data ecosystems.
Advantages:
Disadvantages:
Data analytics projects are rarely performed under montly retainers but it is possible in some cases
Advantages:
Disadvantages:
Hiring an in-house data analyst makes sense if you want to develop new analysis every month. If you simply want to maintain the data analytics reports that you have built, it is cheaper to go for a monthly maintenance retainer.
You would need to pay a salary of about $40,000 USD per year for junior data analyst. A more senior data analyst could cost around $100,000-150,000 USD per year depending on the state you are in.
The most cost-efficient approach is to maximise the junior data analyst working hours. For example you can employ a junior data analyst to build data analytics reports from Excel data and involve outsourced senior consultants for more technical tasks like building a data warehouse.
Advantages:
Disadvantages:
A cost-benefit analysis (CBA) in data analytics is a structured approach for weighing the projected or actual costs of analytics initiatives against their expected benefits to determine if a project is financially and strategically justified.
A comprehensive cost-benefit analysis requires capturing all relevant costs, often categorised as:
Technology & Infrastructure:
People & Expertise:
Data Acquisition & Management:
Operational & Process Change:
A positive ROI validates the investment in data analytics.
| Category | Example Costs | Example Benefits |
| Software/Tools | Licensing, integration | Automation, faster analysis |
| Infrastructure | Cloud storage, upgrade fees | Scalability, lower hardware spend |
| Personnel | Data scientist salaries, training | New insights, process improvements |
| Operations | Maintenance, support | Reduced operational delays |
| Strategic/Intangible | Productivity disruption, opportunity | Market differentiation, culture shift |
The cost of data analytics implementation can vary significantly depending on the size and complexity of the business. From startups to large enterprises, the scope of data usage, infrastructure needs, and talent requirements all influence the final investment. Understanding these differences is crucial for selecting the right analytics approach and avoiding under- or over-investment.
Typical Cost Range: $1,000 – $20,000 (initial setup); $100 – $1,000/month (ongoing)
Small businesses typically have limited data volumes and fewer decision-making layers. As a result, small business analytics needs are often modest, focused on descriptive and diagnostic insights rather than advanced predictive models.
Typical Cost Range: $10,000– $100,000 (initial setup); $1,000 – $5,000/month (ongoing)
Mid-sized organisations often need more robust analytics to support departmental operations, regulatory reporting, and forecasting. Their data complexity increases, often requiring integration from multiple systems (CRM, ERP, marketing platforms, etc.).
Typical Cost Range: $20,000 – $300,000 + (initial setup); $5,000 – $25,000/month (ongoing)
Enterprises operate with massive datasets across departments, locations, and digital channels. Their analytics functions are typically advanced, involving predictive modelling, machine learning, AI, and real-time reporting.
| Business Size | Initial Setup Cost | Ongoing Monthly Cost | Key Focus Areas |
| Small Businesses | $1,000 – $20,000 | $100– $1,000 | Basic data analytics dashboards |
| Medium Businesses | $10,000 – $100,000 | $1,000 – $5,000 | Departmental reporting, forecasting |
| Large Enterprises | $20,000 – $300,000 | $5,000 – $25,000 | AI, ML, real-time analytics, data strategy |
Before spending on analytics, ask yourself how ready your team and systems are. Do you already collect data? And how clean is your data? Are your teams used to working with reports? If you’re just starting, going straight into complex analytics solutions might be a waste. The best way to start is to start small, with tools that scale with your data and needs and with a consultancy that can guide you every step of the way.
As you’ve seen in previous sections, different services have their respective costs. You must be clear and honest about your needs so you don’t end up blowing your budget on services that will only eat into your analytics ROI. Don’t go for a full-suite enterprise solution if all you need is a monthly report.
You might use a low-cost tool like Power BI or Looker Studio if you have simple and general needs. But if you’re dealing with industry-specific metrics, messy data, or want help making sense of everything, a data analytics consulting service will save you time and errors. Off-the-shelf tools are cheaper upfront, but custom consulting pays off when the stakes are high.
Vidi Corp data analytics consultancy has provided data cleaning, visualisation, and many other data analytics services to hundreds of clients.
Let’s see some examples of their dashboard and visualisation services:
This workforce overview dashboard helps HR teams and senior management understand employee satisfaction, attrition, and team performance on one page.
You can quickly know the roles or departments with low satisfaction or work-life balance and dig into tenure trends. Insights like these help HR teams improve retention and employee experience, which translates to high business throughput.
You can read more HR analytics dashboard case studies from Vidi Corp.
This sales revenue dashboard gives financial directors of Tikkurila a full view of how the sales team is performing by region, payment terms, and individual salesperson.
The revenue is broken down by month and compared to the target and the previous year.
It helps them pinpoint high-performing reps and underperforming regions and adjust sales strategy in real time based on data-backed facts, not guts.
Read the full sales and finance dashboard case study
Depending on your goals, tools, and team, data analytics may cost you something or nothing. With the right partner and service fit, it will surely pay for itself 100%. Make Vidi Corp consultancy your data analytics partner today and see for yourself.
Depending on scope and complexity, it may run anywhere from $500 for small jobs to $15,000+ for comprehensive solutions.
Yes. Especially if they go with off-the-shelf options or customised plans for start-ups or SMEs.
There are two major pricing models: Fixed and Variable
