2024_Top Data Science Service Providers

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RESEARCH

Top

Data Science

Service Providers

2024

information, email info@aimmediahouse.com or visit aimresearch.co.

August 2024

AIM Research's annual initiative to recognize leading Data Science

Service Providers sets an industry standard, helping businesses

quickly assess the potential of vendors.

AIM Research

Penetration Maturity (PeMa) Quadrant

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Table of

The Data Science Services PeMa Quadrant

Vendor’s Key Competencies and Differentiators

Contents

Market Outlook

Introduction

Significance of Data Science Service Providers

Strategic Developments in the space of Data Science offerings

Scope and Methodology

The Quadrants

PeMa Quadrant for Data Science Service Providers 2024

PeMa Quadrant for Data Science Service Providers 2023 Vs 2024

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AIM Research PeMa Quadrant Citation Policy

About AIM Research

Tiger Analytics

Genpact

EXL

EY GDS

MathCo

WNS

Fractal

Axtria

Tech Mahindra

LatentView Analytics

C5i

Penetration and Maturity Indices

Market Outlook

Significance of Service Providers and

Strategic Developments

This section provides an overview of the

Data Science service providers market

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Data Science Service Providers

PeMa 2024

aimresearch.co

The Data Science industry has become a critical driver of

innovation and business growth across several sectors. As

organizations increasingly rely on data-driven insights to guide

strategic decisions, the demand for specialized Data Science

service providers has surged.

To assess and identify leading service providers in the Data

Science industry , AIM Research conducts an annual survey in

which Vendors participate voluntarily to benchmark their

capabilities against their peers.

A total of thirty-six service providers participated in this

year’s assessment. All the vendors featured in this report are

analyzed through a survey, which gathered quantitative and

qualitative data on various aspects of their operations, such as

financial health, growth, customer confidence, client reach,

work delivery, tech advancement, employee maturity, and

support infrastructure.

Through this analysis, we aim to show how the industry has

advanced over the past year and highlight the top Data Science

service providers, with firms expanding their teams, enhancing

their expertise, and forging strategic partnerships to stay

competitive in a rapidly evolving market.

Introduction

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Data Science Service Providers

PeMa 2024

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.

Customization and Tailored

Solutions

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

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

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

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Data Science Service Providers

PeMa 2024

Key Developments in the

space of Data Science

Service Industry

In addition to the growing need for focusing on Data

Governance, Data Science Service industry vendors are also

required to focus on upskilling their talents, partnerships for

advancement of technology and industry expertise,

scalability, and deliver better business insights by integrating

GenAI intelligence systems into Data Science offerings.

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Vendors are focusing on upskilling

and reskilling their teams in emerging

areas like AI/ML, GenAI, cloud

computing, and big data analytics.

They are also investing in training

their teams on industry-specific

knowledge, especially in sectors like

healthcare, finance, and retail, to

enhance domain expertise.

Focus on Upskilling &

Reskilling

There is a trend towards specialization

for developing industry-specific

solutions that cater to the unique needs

of sectors such as BFSI and Healthcare

and Life Sciences.

Providers focusing on the financial

services sector are developing advanced

risk assessment models, while those in

healthcare are creating predictive

analytics tools for patient outcomes.

There is a strong shift towards cloud-

based and hybrid solutions, driven by

the need for scalability, flexibility, and

remote accessibility. Many providers

are integrating their services with

leading cloud platforms such as AWS,

Google Cloud, and Microsoft Azure,

offering clients the ability to scale

their Data Science initiatives

efficiently.

Emphasis on Industry-

Specific Solutions

Demand for Cloud Native

Solutions

Data science service providers are

expanding their offerings beyond

traditional data analytics to include

advanced services such as AI and

ML, Deep Learning , Computer

Vision, and GenAI.

Many service providers have

introduced GenAI accelerators to

quickly deliver advanced AI-driven

analytics solutions and stay

competitive in the evolving market.

Expansion of GenAI

Service Portfolios

Service providers are implementing

policies and practices to address

issues such as bias in AI models,

data privacy, and compliance with

regulatory standards like GDPR.

With the rising concerns around

data privacy, the creation of

synthetic data, which can mimic the

statistical properties of real data

without containing any actual

information, will become prominent.

Data Governance &

Synthetic Data

Strategic partnerships and alliances

are becoming a key component of

growth strategies for Data Science

service providers. These partnerships

often involve collaboration in the

areas of AI and cloud optimization

with hyperscalers, academic

institutions, and industry-specific

leading organizations to enhance

capabilities and extend market reach.

Partnerships and

Alliances

Data Science Service Providers

PeMa 2024

The Data Science

Service Providers

PeMa Quadrant

aimresearch.co

This section presents the different

quadrants and the positions

occupied by participating vendors,

along with their penetration and

maturity indices

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Data Science Service Providers

PeMa 2024

Scope and Methodology

The methodology employed in the PeMa

Data Science study is based on primary and

secondary research methodologies tailored

to the dynamics of the Data Science industry.

Primary research data is collected through

surveys distributed among participating Data

Science service providing firms, ensuring a

direct assessment of their practices and

capabilities. These surveys are meticulously

designed based on initial research to capture

key factors that define a provider's market

penetration and service maturity in the Data

Science domain.

Each survey question is crafted to assess

critical aspects, such as financial health,

growth, customer confidence, client reach,

work delivery, tech advancement, employee

maturity, and support infrastructure.

Responses are evaluated using a

standardized criterion, and outliers are

identified and addressed to maintain data

integrity. To ensure a fair comparison,

scores are normalized within a range of 0 to

1, allowing for meaningful comparisons

across vendors.

The resulting normalized scores are

aggregated to derive sub-index scores for

Penetration and Maturity, providing a

nuanced understanding of each provider's

market presence and proficiency in

delivering high-quality Data Science

solutions. A thorough analysis of these

indices enables businesses to gauge the

breadth of a vendor's client base, industry

reputation, and the depth of their technical

expertise and experience in deploying Data

Science solutions.

The study encompasses a diverse sample of Data

Science service providers, with participation being

voluntary and cost-free. Responses are collected

through user-friendly platforms such as Zoho

Forms, with follow-up communication conducted

to resolve any discrepancies or clarify responses.

Additionally, briefing calls are scheduled (if

required) to gain deeper insights into the offerings

and methodologies of Data Science vendors,

ensuring a comprehensive evaluation process.

Penetration, within the context of Data Science,

evaluates a provider's market reach and strategic

initiatives aimed at expanding their client base.

This includes factors such as financial health,

growth, pricing models, and the breadth of their

service offerings. A high Penetration score

indicates a robust market presence and strong

industry reputation, essential for businesses

seeking reliable Data Science partners.

Maturity, on the other hand, assesses the depth of

a provider's technical expertise, experience, and

ability to deliver sophisticated Data Science

solutions that meet evolving client needs.

This encompasses factors such as innovation,

reliability, scalability, and the ability to adapt to

emerging technologies and industry trends. A high

Maturity score signifies a provider's proficiency in

delivering value-added Data Science services and

demonstrates their readiness to address complex

challenges in AI implementation.

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Data Science Service Providers

PeMa 2024

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The Quadrants

Seasoned Vendors

With strong technical capabilities

and consulting experience, these

vendors have made an impact in

the market. However, they still

must strive to keep pace with our

Leaders if they wish to excel even

further!

Data Science Service Providers

PeMa 2024

Leaders

These vendors are highly sought-

after on the market, with a long

track record of expanding reach

and success in multiple sectors

worldwide. Their teams boast

unparalleled experience and

skillset when it comes to providing

comprehensive services using

cutting edge technology that’s

always at the forefront.

Challengers

At first glance, Challengers may

appear to be at a disadvantage

when competing with larger

analytics providers. However, their

smaller size and scope of services

equip them with an advantage that

rivals can’t compete against –

superior training and delivery

capabilities!

Growth Vendors

Among the top contenders in their

industry, these vendors have seen

remarkable revenue expansion.

While they still trail behind the

market leaders with regards to

delivery capabilities maturity, it’s

clear that impressive progress has

been made.

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