Data Science and Analytics

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

Talk to our Experts

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

Get In Touch
  • 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

    July 7, 2025

    BLOG

    Why NLP Virtual Assistants Are No
    Longer Optional for Insurers

    This blog explores how NLP-powered virtual assistants transform insurance customer support and improve underwriting. It explains core technologies like machine learning, speech recognition, and context awareness, driving these assistants. The blog also highlights crucial security and compliance guardrails needed for ethical deployment.

    Read More

    July 1, 2025

    BLOG

    Your Customers See More Than Reality:
    Is Your Mobile Strategy Keeping Up?

    Extended Reality (XR) transforms mobile app experiences through spatial interactions, real-time data, and immersive design. This blog explores key XR components, UX principles, testing strategies, and use cases across healthcare, retail, and gaming industries. It also addresses security, privacy, and ethical challenges unique to XR environments.

    Read More

    June 30, 2025

    BLOG

    Why the Future Belongs to Enterprises That Build Intelligent Hyperautomation

    The blog discusses how Enterprise Hyperautomation combines AI, RPA, and low-code platforms to automate complex processes, improve data accuracy, and accelerate digital transformation. By integrating these technologies, organizations streamline workflows, reduce manual effort, enhance compliance, and deliver agile, scalable solutions.

    Read More

    June 24, 2025

    BLOG

    AI Workbenches Powering Underwriting – Catch Up or Leap Ahead

    The blog discusses how an AI-powered underwriting workbench streamlines insurance operations by centralizing risk tools, data, and workflows. It enhances decision accuracy, supports automation, and delivers faster, more consistent underwriting outcomes. Insurers can boost efficiency and stay compliant in a complex digital environment with built-in machine learning and real-time analytics.

    Read More

    June 23, 2025

    BLOG

    Digital Accessibility Is Rising: Here’s How APAC and LATAM Are Leading the Shift

    The blog discusses how accessibility laws in APAC and Latin America are evolving, making compliance a business-critical need. It also explores regional legal updates and how AI-powered accessibility testing helps ensure inclusion, reduce risk and support ethical, user-friendly design.

    Read More

    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.