Data & Analytics Consulting
Discover what data & analytics consulting involves: how consultants help organisations get value from data with analytics, data science and AI, what they do day to day, the career ladder, and how students prepare for an application.
Introduction
What is data & analytics consulting?
Data & analytics consulting is about how an organisation gets value from its data. Consultants help unlock, analyse and turn data into models, dashboards and decisions, from classic business intelligence to data science and AI.
The work combines technology and business: a good model is only valuable if it answers a real question and is actually used. The consultant therefore constantly switches between data, technology and the people who work with the results.
Data & analytics is one of the fastest-growing parts of consulting, partly due to the rise of AI. It appeals to students with a quantitative background who want to stay close to the business.
The practice
Three settings where you practise this field
The breakdown below mainly says something about the type of employer and the clients you serve, not about the quality of the work.
At specialist data and AI firms you work deep in the technology of data and models. Technology and advisory firms often combine data with broader transformation. Strategy and Big Four firms often approach data from strategy or the broader advisory platform. In addition, many data professionals work in-house at a data company.
What they do
What data & analytics consultants do
The work differs by project, but the building blocks below come up in almost every data project.
Types of project
The main types of project
Data & analytics consulting has a number of recurring project types, even though the sector and technology differ greatly.
Sub-areas
The main sub-areas
Data & analytics is broad, and many consultants specialise over time in a technique or type of application.
Step by step
How a data project unfolds
Most data projects follow a similar path, from sharpening the question to a model or dashboard that runs in practice.
Who does which step depends on seniority and role. Junior consultants do much of the gathering, preparation and modelling, while senior consultants set the approach and make the translation to the business.
A large part of the work is in preparing the data: a model is only as good as the data it is built on.
Roles
Roles in the data & analytics practice
Each step up the ladder shifts the emphasis further from building models toward leading teams and managing the client relationship. Most consultants climb this ladder at the same firm, though moving to a data role in the business is common at any level.
Data Analyst / Consultant
The entry role straight after a bachelor's or master's.
Senior Consultant / Data Scientist
Independently handles a data part of a project.
Manager / Lead
Leads a team and the day-to-day running of a data project.
Senior Manager / Principal
Carries responsibility for several projects and client relationships.
Partner / Director
Holds ultimate responsibility for clients and the practice.
Career timeline
How long each step takes
Data & analytics consulting has a relatively fast career path. The pace differs by firm and individual, and relates to the projects and results you show.
Many consultants stay a few years and then move to a data role in the business, a data company or a startup. Those who stay progress toward Manager and eventually partner or director.
Depth in a technique such as machine learning or data engineering is valuable in this field and can speed up progression.
| Level | Typical time in role |
|---|---|
| Data Analyst | 2 to 3 years |
| Data Scientist | 2 to 4 years |
| Manager / Lead | 2 to 4 years |
| Partner | top level, 10+ years in total |
Compensation
Compensation in data & analytics consulting
Compensation usually consists of a fixed salary that rises with seniority, and at many firms a bonus tied to individual and firm performance. Given the demand for data professionals, pay in this field is generally good.
The ranges below are general indications for larger technology and advisory firms, and do not apply specifically to any particular firm. Actual pay varies by firm, background and year, and is listed where known in the individual vacancies on this site.
From partner or director level, the nature of compensation changes, tied more closely to your own client portfolio and the results of the firm as a whole.
| Level | Indicative range |
|---|---|
| Data Analyst | €45.000 – €65.000 |
| Data Scientist | €65.000 – €95.000 |
| Manager / Lead | €100.000 – €150.000 |
| Partner / Director | €200.000 – €500.000+ |
Ranges are general indications for larger technology and advisory firms, not specific to any particular firm. See the vacancy pages for concrete salary figures where a firm publishes them.
A day in the life
A typical day for a junior data consultant
The day often starts with a short team stand-up. After that, much of the time goes into preparing data, building or improving a model and making visualisations for the client.
A data consultant constantly switches between the technology and the business: a model is only valuable if it answers a real question. That requires both quantitative work and clear communication.
On a day with a delivery, the team shows the results to the client, explains how the model works, and discusses how the organisation will use it in practice.
Juniors
What junior data consultants do
Junior consultants carry much of the data and modelling work a data project rests on, under the supervision of a Manager or senior.
- Gathering and combining data
- Cleaning and preparing data
- Running exploratory analysis
- Building and training models
- Building dashboards and visualisations
- Validating models
- Documenting results
- Supporting the client with usage
Much of this work goes back and forth within the team and with the client before a model is delivered. That repetition is not inefficiency, it is how a junior consultant learns what makes a model reliable and usable in practice.
Skills
Skills you will need
Quantitative ability gets the most attention, but the consultants who stay longest often stand out for the ability to make a technical result understandable to the business.
Getting in
How you get into data & analytics consulting
Most routes run through a quantitative degree such as econometrics, data science, computer science, mathematics or physics. Programming skill and affinity with data are important pluses.
Preparation
How to prepare as a student
Preparation works best when it starts well before the application. Firms test your technical skill and whether you can explain a result clearly.
Compare
Data & Analytics versus other paths
These paths sometimes overlap, which is why students mix them up. The distinction mainly lies in how deep you sit in the data and the technology.
Data & Analytics vs Technology & Digital Consulting
Technology & digital is broader and covers systems and ways of working. Data & analytics focuses specifically on data, models and AI.
Data & Analytics vs Strategy Consulting
Strategy decides an organisation's choices. Data & analytics provides the models and insights that support those choices.
Data & Analytics vs an in-house data scientist
An in-house data scientist works for a single organisation. As a consultant you work for many clients and see many different data problems.
Data consulting vs a data engineer role
A data engineer mainly builds the platforms and pipelines. A data consultant sits closer to the business and the use of the results.
Data & Analytics vs Operations Consulting
Operations improves processes and execution. Data & analytics uses data and models to support that improvement.
Employers
Data and analytics firms in the Netherlands
A selection of firms with a strong data and analytics practice and an office in the Netherlands. We only name firms whose practice is confirmed.
In addition, the strategy houses and the Big Four have their own analytics and AI units, and many data professionals work in-house at a data company.
Specialist data and AI firms
Technology and advisory firms with a strong data practice
Vacancies
Data & analytics vacancies
We only show real, current openings with a link to the employer. Internships, traineeships and consultant roles appear here. In the meantime, browse all current vacancies.
View all vacanciesResources
Recommended resources
FAQ
Frequently asked questions
What is data & analytics consulting?
It is the advisory field around getting value from data: consultants help analyse data and turn it into models, dashboards and decisions, from business intelligence to data science and AI.
What degree do I need?
Most consultants come from a quantitative degree such as econometrics, data science, computer science, mathematics or physics. Programming skill and affinity with data are important.
What does a data consultant do day to day?
Consultants gather and prepare data, build models and dashboards, develop AI applications, and translate the results into decisions for the client.
Do I need to be able to code?
For most roles yes. Python and SQL come up in almost every data project, alongside knowledge of statistics and machine learning.
What is the difference with a data engineer?
A data engineer mainly builds the platforms and pipelines, while a data consultant sits closer to the business and focuses on models, insights and their use.
How much do you earn in data & analytics consulting?
Given the demand for data professionals, pay is generally good. Actual pay varies by firm and is listed where known in the vacancies on this site.
What skills do you need?
Statistics, programming, machine learning, data visualisation, analytical thinking and the ability to explain a technical result clearly.
How do I get into this field as a student?
Build quantitative and programming skills, work on your own data projects, do a relevant internship, and apply via campus or the firm's website.
Related
Related consulting paths
Start your journey in data & analytics consulting
Browse open vacancies or discover the other consulting paths.