2024_Top Data Science Service Providers

AIMResearch’s Penetration and Maturity (PeMa) Quadrant for Data Science Service Providers—a reliable industry standard to

evaluate vendor competencies aids businesses in choosing the most suitable Data Science service provider aligned to their

business needs. The PeMa report aims to empower decision-makers with the knowledge required to select the right Data Science

service provider for their unique needs. Through an exploration of market dynamics and vendor profiles, we provide a

comprehensive map for navigating the Data Science landscape, ensuring that organizations can harness the full potential of Data

Science to transform their operations and stay competitive in the digital age.

01

Customization and Tailored

Solutions

02

Organizations often require customized models or

solutions that off-the-shelf products might not

provide. Service providers can build and fine-tune

these models to meet specific requirements.

For example, vendors like Akaike and Artivatic are

streamlining services on top of their flagship

platforms, enabling organizations to accelerate

their data initiatives.

Service providers offer end-to-end project

management, ensuring that all aspects of a Data

Science project are handled efficiently with

continuous or on-demand support. For example,

Fractal Analytics provides comprehensive data

science services, from strategy to implementation.

Their services include data science consulting,

model development, training, and deployment.

End-to-End Project Execution

03

Businesses often struggle to recruit data scientists

with the necessary skills and experience for a

critical project. Service providers can quickly

provide the right talent, ensuring that the project

proceeds without delays. For Example, beyond

academic qualifications, EXL places a significant

emphasis on practical experience and specialized

skills and certifications that are crucial for

advancing their Data Science capabilities.

Bridging the Talent Gap

04

Building in-house Data Science capabilities for complex

projects can be prohibitively expensive and time-

consuming. Service providers offer a cost-effective

alternative by bringing in the required expertise and

resources on demand. For example, by continuously

upgrading the models developed a few years ago to the

latest versions of programming languages, Think

Analytics (Think360.ai) drastically reduces TAT and the

cost of model deployment for their clients.

Cost-Effectiveness for Complex

Projects

Significance of Data Science

Service Providers

AIM Research’s PeMa Quadrant

RESEARCH

Data Science Service Providers

PeMa 2024

06

Made with Publuu - flipbook maker