Data Science and Analytics

Uncover valuable insights by accessing data you may not have been aware of previously

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Our Data Science and Analytics services are designed to unlock the full potential of your data, transforming it into actionable insights that drive business growth and efficiency. Our team of experts works closely with you to understand your business objectives and challenges, ensuring that our analytics solutions are perfectly tailored to your specific needs. From predictive analytics and customer segmentation to trend analysis and risk assessment, our services cover a wide range of applications.

Business Value Delivered

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  • Informed decision-making
  • Accelerated Time-to-market
  • Improved risk management
  • Increased operational efficiency

Our Data and Analytics Capabilities

Data Collection & Preparation

Sourcing data from various channels, cleaning it to remove inconsistencies, and pre-processing it to ensure it is in the right format for analysis.

Exploratory Data Analysis (EDA)

Uncover initial patterns, anomalies, trends, and relationships within the data for gaining insights and informing the direction of further analysis and model building.

Model Building

Leveraging the insights gained from EDA to build predictive or descriptive models tailored to your specific business needs.

Model Evaluation

Evaluate performance using various metrics and techniques to ensure the model's accuracy and effectiveness in making predictions or generating insights.

Parameter Tuning

Adjust the model parameters and fine-tune feature selection to improve its performance.

Deployment

Seamlessly integrate into your existing systems and workflows to provide ongoing support to maintain its performance over time.

Speak to an expert

In your line of work, we know every minute matters.

    Our Approach

    At Tx, we empower your business with our Data Science & Analytics services, leveraging advanced algorithms and data-driven insights to optimize your strategies and drive transformative outcomes.

    Data-Science-and-Analytics

    Why Choose Tx

    QA Domain Expertise
    Comprehensive Expertise

    We bring extensive expertise in data and analytics, encompassing data transformation, AI solutions, generative AI, and business process services. 

    Proven track record
    Client-Centric Approach

    Our team of experts collaborate closely, ensuring a transparent and communicative partnership that aligns with your business objectives.

    Data
    Holistic Data Transformation

    We go beyond data transformation, offering a holistic approach to turn your raw data into valuable assets and derive meaningful insights for strategic planning.

    Recent Insights

    August 5, 2025

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    Break Free from Legacy Bottlenecks – How Synthetic Test Data Fuels Agile Innovation

    In Agile software development, the demand for high-quality test data is crucial, but traditional production data often leads to bottlenecks due to privacy and compliance concerns. Synthetic test data, generated by AI, offers a secure, flexible alternative by mimicking real data without exposing sensitive information. It speeds up testing, improves coverage, and uncovers edge cases missed by traditional data. With synthetic data, teams can quickly generate tailored datasets for each test scenario, reducing waiting times and improving efficiency. Embracing synthetic test data helps businesses accelerate delivery, enhance product quality, and innovate faster.

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    August 4, 2025

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    Shift-Right Testing Isn’t Optional
    Here’s How AI and Real Users Are Making It Work

    The Shift-Right approach is rapidly becoming a cornerstone of modern quality engineering, offering enterprises a smarter way to ensure software excellence post-deployment. Unlike the traditional Shift-Left model, which focuses on early testing in the development lifecycle, Shift-Right emphasizes continuous validation in production using real-user data and behavior insights. This strategy helps organizations improve customer experience, resolve issues faster, and make data-informed decisions with greater precision. Read the blog now

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    July 30, 2025

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    From Distrust to Defense – How AI is Strengthening Cybersecurity

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    July 22, 2025

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    Win the Accessibility Game: Combining AI with Human Judgment

    AI is transforming accessibility testing by automating audits and reducing effort, but it can’t replace human judgment. This blog explores why a hybrid approach—AI-powered tools plus human-in-the-loop validation—is essential for reliable, inclusive digital experiences. Learn how Tx leverages this synergy to deliver accurate, scalable, and regulation-compliant accessibility testing solutions.

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    July 21, 2025

    BLOG

    Lead with Intelligence: Rethink QA Outsourcing for the AI Age

    The blog discusses how AI is leveling up the QA outsourcing industry by enhancing efficiency, improving code quality, and reducing costs. You will learn how to choose the right AI-driven QA partner and see how intelligent testing strategies can help you stay competitive in the digital age.

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    FAQ's

    How do Data Science and Data Analytics differ?
    • While Data Analytics focuses on processing and performing statistical analysis on existing datasets, Data Science encompasses a broader scope, including data analytics, data mining, machine learning, and predictive modeling.

    What industries benefit from Data Science and Analytics services?
    • Industries such as finance, healthcare, retail, manufacturing, and transportation utilize data science and analytics to improve decision-making, increase efficiency, and gain a competitive advantage.

    How do businesses implement Data Analytics strategies?
    • Implementing data analytics strategies involves defining clear objectives, collecting and preparing data, choosing appropriate analytical tools and techniques, and translating insights into actionable business decisions.

    How can businesses ensure data quality in analytics projects?
    • Ensuring data quality involves data cleaning, validation, and implementing robust data governance practices to maintain accuracy, consistency, and reliability in analytics projects.