Welzin Services for the
E-Commerce Industry
Optimize business performance, enhance customer engagement, and drive innovative growth in the digital marketplace with AI-adopted technologies.
Data Engineering Services Satisfy Needs
Scale infrastructure effectively, optimize user experience and supply chain, improve customer service with AI, and derive actionable insights.
Harness advanced analytical techniques and AI/ML algorithms to interpret complex data. Analyze user behavior and preferences, forecast demand, and use intelligent chatbots.
Gather customer feedback and queries from various platforms to train and improve AI models.
The Core Essence of Data Science
Data Scraping and Customer Service Automation
Aggregate and harmonize data from diverse sources, providing a comprehensive view. Combine big data from various supply chain sources.
Create dashboards and reporting tools that are accessible through a website or an intranet.
Data Integration for Informed Decision-Making
Web Development for User-Friendly Trading
Managing Large-Scale Infrastructure with DataOps
Optimize data workflows, making scaling more responsive to fluctuating demands.View page
Better Products and Experiences
Benefits of e-commerce using our services and solutions:
01 Enhanced decision-making
05 Personalized customer experiences
02 Optimized inventory management
06 Fraud detection and prevention
03 Customer segmentation for targeted marketing
07 Predictive analytics for
future planning
04 Efficient supply chain management
08 Competitive advantage
Steps
Towards Good Development
These data engineering development stages ensure that solutions are well-designed, thoroughly tested, and aligned with business objectives.
In the early phases of our data engineering development process, we engage in a free consultation to gauge project compatibility. During the discovery and feasibility analysis, we adapt to your needs, whether it's high-level requirements. We gather information to define project scope through discussions, including feature lists, data fields, and solution architecture. We craft a project plan to guide our progress, reflecting our dedication to achieving project goals and delivering effective data engineering solutions.
Initial Project Assessment and Definition
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In this stage, the technical architecture and design of the solution are formulated. Data engineers plan how data will be collected, stored, processed, and presented. Simultaneously, the project backlog is created — a list of tasks and features to be developed. This backlog is prioritized, ensuring that high-priority items are addressed first.
Tech Design and Backlog Planning
3
Discovery
So, you have finally decided that you are ready to cooperate with DATAFOREST.
The discovery stage involves delving into the details of the project. Data engineers gather requirements, analyze existing systems, and understand the needs of the business. This step is crucial for laying the groundwork for development, as it ensures that the project aligns with business goals and user needs.
2
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Development Based on Sprints
4
The deployment phase involves releasing the solution to the production environment, making it accessible to users. It requires careful planning to ensure a seamless transition and minimal disruption. After deployment, the rollout phase begins, involving training for users and ongoing support to address any hiccups.
Deployment and Rollout
6
Quality Assurance is an ongoing process that permeates the entire project development lifecycle. It ensures rigorous testing, identification, and resolution of any bugs or issues to guarantee the solution's smooth operation, compliance with requirements, and alignment with quality standards. The solution is prepared for release as QA activities persist and necessary adjustments are continuously implemented.
Project Wide QA
5
In the final stages, we ensure ongoing excellence. We guarantee optimal performance and swiftly address any issues. Simultaneously, our feedback process empowers us to continuously enhance the solution based on user insights, aligning it with evolving needs and driving continuous innovation.