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Top 10 Data as a Service Companies in 2024

Updated on Mar 27
6 min read
Written by
Cem Dilmegani
Cem Dilmegani
Cem Dilmegani

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

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Ezgi Alp
Ezgi Alp
Ezgi Alp
Ezgi is an industry analyst at AIMultiple and specializes in firewalls and firewall management.

Ezgi holds a PhD in finance and a bachelor's degree in management.
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Data as a Service (DaaS) refers to a cloud computing service model where data is provided on demand to users, applications, or systems, usually on a subscription basis. Service providers collect, process, and manage diverse datasets, making them available to users for various purposes. A report by Market Research Future projects that the market size of DaaS exhibits a Compound Annual Growth Rate (CAGR) of 23%, reaching USD 80 billion by 2030.1

While the data-as-a-service industry is experiencing rapid growth, some firms still opt to utilize internal storage for the information they generate instead of leveraging the services provided by these companies. This article explains the key features and benefits of DaaS companies, along with a list of the top service providers in the market.

Top 10 DaaS Provider

Potential customers rely on the user evaluations while deciding the service vendors fits for their needs. The table below exhibits user ratings of top 10 DaaS vendors from three review platforms.

Table 1. Summary of user ratings of top 10 DaaS vendors

VendorsRatings*Basic Pricing**Free Trial*Free Version*
Candid GuideStar4.9/5$174
Snowflake4.6/5$23
Tracxn4.3/5$550
Kantar Marketplace4.2/5No Information
Nielsen Marketing Cloud4.2/5No Information
CompAnalyst4.4/5No Information
Factiva4/5No Information
D&B Connect3.9/5No Information
Oracle DaaS4/5No Information
Infor Birst4.2/5$125

*The data was gathered from vendor websites as well as review platforms such as G2, Trustradius, and Capterra as of February 2024.

**Per month, per user.

Table 2. User experience comparison of top 10 Data as a Service (DaaS) vendors

VendorsValue for MoneyEase of UseCustomer ServiceAPI IntegrationLanguages Supported
Candid GuideStar5/54.5/54.5/5English
Snowflake4.3/54.5/54.3/5English
Tracxn4/54.5/54.5/5English
Kantar Marketplace4/54/54/5German, English, French, Italian, Japanese, Spanish, Chinese (Simplified)
Nielsen Marketing Cloud4/54.1/54.1/5English
CompAnalyst5/55/54/5English
Factiva2/53.5/55/5
English, French, German, Spanish, Italian, Japanese, Portuguese, Russian, Chinese (Simplified), Chinese (Traditional)
D&B Connect4.3/54.3/5English
Oracle DaaS4.1/54.1/54.2/5
Arabic, Chinese, Dutch, English, Finnish, French, German, Italian, Japanese, Korean, Norwegian, Portuguese, Russian, Spanish, Swedish, Thai, Turkish
Infor Birst5/54.4/54/5
Arabic, Czech, Danish, German, English, French, Croatian, Hungarian, Italian, Japanese, Korean, Dutch, Polish, Portuguese, Slovak, Slovenian, Spanish, Serbian, Swedish, Chinese (Simplified)

Key Data as a Service features

DaaS companies specialize in collecting, managing, and delivering data to users, enabling them to access and utilize the data without the need for internal cloud infrastructure. 

DaaS companies offer various functions, such as:

1. Data Provisioning

Data as a Service (DaaS) providers offer access to a diverse range of datasets, often sourced from various channels such as public databases, proprietary sources, or data aggregators. This addresses specific data needs that may be challenging to fulfill independently. Businesses mostly lack the tools, expertise, or direct access to required data, DaaS providers streamline the process. These services eliminate the complexities of permissions and data collection, allowing businesses to focus on deriving insights and value from the acquired datasets.

2. Data Management

DaaS companies excel in managing data by handling the storage, organization, and maintenance of large datasets. Beyond these fundamental aspects, they navigate the complex landscape of data permissions, ensuring compliance with regulations and addressing the nuances of data access rights. This includes securing necessary permissions and managing data in a way that aligns with legal requirements. DaaS platform also handles the data security risks of sensitive data in a more efficient way.

3. Data Analytics

Some DaaS providers offer data analytical tools and services, allowing users to derive insights from the organization’s data they access. This may include tools for business intelligence, predictive analytics, and machine learning. 

4. Application Programming Interfaces (APIs)

DaaS companies often provide APIs that allow users to integrate the business data directly into their applications, workflows, or systems. This functionality empowers businesses to harmonize their existing processes with the wealth of data offered by DaaS providers, fostering enhanced operational efficiency, real-time insights, and increased adaptability to evolving business needs. 

5. Scalability

DaaS are scalable, meaning users can adjust their data usage based on their evolving needs. This flexibility is particularly beneficial for businesses with changing data requirements. Moreover, unlike other data collection methods such as web scraping tools, DaaS eliminates the need for a dedicated IT team to manage the process of obtaining the required data. These services save time and effort by providing the need of the business, and also enhance decision-making accuracy and efficiency for businesses by providing timely data.

6. Subscription-Based Model

DaaS is typically offered through a subscription-based model, allowing users to pay for the data services they use. Businesses may negotiate with DaaS provider for the data that fits their needs, rather than investing in and maintaining their own data infrastructure. This enables users to pay only for the specific data services they utilize and offers cost savings. 

Benefits of Data as a Service Companies

DaaS empowers organizations by streamlining data processes, fostering a data-centric culture, and providing cost-effective access to valuable information, ultimately contributing to improved decision-making and business success. 

1. Efficient data storage and delivery 

DaaS leverages cloud infrastructure to store and deliver data, eliminating the need for organizations to invest in and maintain extensive internal data storage systems. This service spares businesses from the hassle of dealing with concerns such as available cloud space.

2. Data democratization 

DaaS plays a pivotal role in democratizing data by making it accessible and understandable for individuals across the organization, even those without technical expertise. This accessibility fosters a data-driven culture where insights are available to a broader audience, enabling better decision-making at all levels.

3. Monetization opportunities

DaaS opens up avenues for organizations to monetize their data assets. 

  • Direct monetization involves earning revenue by selling data to third parties. 
  • Indirect monetization is the usage of the data to extract valuable business insights.

This dual approach allows businesses to diversify revenue streams and capitalize on the intrinsic value of their data.

4. Automated maintenance

DaaS providers take on the responsibility of automated data maintenance, ensuring that data sets remain current, accurate, and reliable. Automation of maintenance enhances the efficiency of data management processes and also frees up resources within organizations to focus on core business activities.

5. Personalized services

The abundance of data available through DaaS enables organizations to create more personalized and targeted services. By analyzing consumer behavior and preferences, businesses may strategically tailor their marketing approaches, fostering increased customer engagement and satisfaction. Understanding individual purchase histories and preferences, for instance, enables companies to provide custom recommendations, creating a more personalized and satisfying shopping experience for customers.

6. Cost-Effective data acquisition

DaaS offers a cost-effective alternative to traditional data acquisition methods. Instead of investing in large datasets with excessive information, organizations can selectively purchase the specific data they need. This targeted approach minimizes costs associated with data processing and analysis, making data-driven initiatives more budget-friendly. Eliminating the need for organizations to invest in and maintain extensive internal data storage also reduces costs associated with hardware and maintenance.

How Data as a Service Companies Help B2B and B2C Sectors

DaaS platforms extend their solutions to various business domains, providing data consumers with diverse datasets, including anonymous multi-channel, social, and enterprise data. The widespread adoption of data in business has quickly become integral, offering on-demand solutions through Data as a Service (DaaS) platforms across diverse industries. 

In the Business-to-Business (B2B) sector, companies utilize DaaS providers to enhance datasets, enabling improved market segmentation and advanced analytics with on-demand firmographic information. This encompasses real-time insights sourced from public records, including recent funding details or newly established locations, empowering businesses with timely and relevant information for strategic decision-making.

In the Business-to-Customer (B2C) sector, data services contribute significantly to delivering timely and relevant information, enhancing the overall customer experience by ensuring access to fresh and rare insights precisely when needed. The utilization of data services in the B2C domain proves instrumental in optimizing marketing strategies, improving customer engagement, and fostering more personalized interactions between businesses and their customers.

How to Choose the Best Data as a Service Software for Your Business

When evaluating Data as a Service (DaaS) software solutions for enterprise adoption, industry analysts emphasize several critical factors that contribute to the overall suitability and efficacy of the platform within a business environment.

1. Determine the needs of your company

Before embarking on the search for a data solutions provider, it’s essential to define your specific data needs and business goals. Identify the type of data you want to work with, understand key challenges, and establish the objectives you aim to achieve through data solutions. This clarity will streamline the selection process, enabling you to identify DaaS providers that align with your unique requirements.

2. Examine user experience

Another important step of deciding the best DaaS for your business is examining user experiences. User experience and ratings play an important role in assessing the overall usability and effectiveness of DaaS solutions. Assessing the overall usability, performance, and flexibility of the DaaS software helps determine how well it integrates with your existing workflows.

3. Check the simplicity and ease of the product

When choosing a Data as a Service (DaaS) solution, prioritize simplicity, seeking a fully managed platform that alleviates concerns about systems, applications, and user interfaces. One factor determining the best DaaS for your business is choosing a user-friendly interface that is intuitive and easy to use for a diverse range of users.

4. Evaluate the customer service

Effective customer service is a crucial factor while deciding the best DaaS platform for your business. It ensures timely technical support, aids in customization and integration, provides training and onboarding assistance, resolves issues promptly, and values customer feedback for continuous improvement. A strong customer service system enhances the overall experience of using DaaS, offering vital support for seamless implementation and optimal utilization.

*Table 2 above may assist you to choose the right DaaS vendor that fits the needs of your business. It illustrates DaaS user experience concerning the value for money, ease of use, customer service support and languages supported by the vendor.

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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

Sources:

AIMultiple.com Traffic Analytics, Ranking & Audience, Similarweb.
Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
Data management barriers to AI success, Deloitte.
Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
Science, Research and Innovation Performance of the EU, European Commission.
Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

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