What is Data Acquisition ?

Data acquisition involves gathering information from diverse sources to uncover insights, answer research questions, and evaluate outcomes. It’s essential for creating high-quality datasets that fuel machine learning and AI. Effective data acquisition ensures that the data used for training models is accurate, relevant, and representative of the problem domain, setting the stage for exceptional AI performance.

Our Clients

Our Data Acquisition Services

Aya Data offers broad data acquisition services to help clients build high-quality datasets for their AI and machine learning projects. We are adept at sourcing the valuable, hard-to-find data that powers successful AI models. 

Data Collection

We use advanced methods to gather data, including drones for aerial imagery, surveys to capture target audience insights, and our extensive partner network to source information across a broad range of industries. Our team ensures the data is diverse, relevant, and perfectly aligned with your project requirements.

Data Procurement

Access exclusive datasets through our strategic partnerships and collaborations. Aya Data’s alliances with academic institutions, research centres, and industry leaders allow us to procure high-quality data assets unavailable elsewhere. 

Web Scraping

Leverage our web scraping expertise to extract valuable insights from online sources efficiently and at scale. We use the latest the techniques to collect data from complex websites and handle dynamic content, all while adhering to ethical standards and legal requirements. 

Data Curation

Data curation involves cleaning, splitting, and augmenting datasets. Cleaning corrects errors, handles missing values, and standardises formats. Data is split into training, validation, and testing sets, with sampling ensuring representativeness. Augmentation techniques like rotation or noise injection can increase dataset size and variance when data is limited.

Why Use Aya for Your Data Acquisition Project

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    • Exceptional Customer EXPERIENCE

      • 1. Customised data collection strategy
      • 2. Regular updates and communication
      • 3. Flexible engagement models
      • 4. Tailored to project requirements
      • 5. Responsive customer support team
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    • Unwavering QUALITY

      • 1. Multi-domain data collection experience
      • 2. Diverse data-gathering methods
      • 3. Hard-to-find data sourcing
      • 4. Rigorous quality control processes
      • 5. Skilled and trained annotators
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    • Unparalleled EXPERTISE

      • 1. Strict data security protocols
      • 2. Regulatory compliance (GDPR, ISO, HIPAA)
      • 3. Secure transmission and storage
      • 4. Experienced data science team
      • 5. Cutting-edge annotation tools employed
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What Our Clients
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Data Acquisition Process

STEP 01

Project Scoping

  • We work with you to define the scope of your data collection project, identifying key objectives, data sources, and desired outcomes.

STEP 02

Resource Estimation & Project Planning

  • We assess the resources required for your project and develop a plan outlining timelines, milestones, and deliverables.

STEP 03

Data Collection

  • We employ numerous data collection methods, such as surveys, web scraping, drone imagery, and sensor data, to gather the necessary data for your project.

STEP 04

Quality Control

  • Our rigorous quality control processes ensure that the collected data meets the highest standards of accuracy, completeness, and relevance.

STEP 05

Data Delivery

  • We deliver the collected data in your preferred format, along with complete documentation and support for integrating it into your machine learning workflows.
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