VOLTERA 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.
Customized E-Commerce Data Solutions
Adjust prices dynamically with real-time data and much more.
Data Warehousing and Integration
Are you having difficulty managing data from multiple sources? The solution centralizes data from various sources, providing a robust infrastructure for easy access.
Advanced Sales Optimization Solution
Have you struggled with increasing sales, improving customer satisfaction, and reducing cart abandonment rates? The solution enhances sales, customer engagement, and conversion rates.
Don’t make the process harder than it is.
Jack Welch, American business executive
Better Products and Experiences
Benefits of e-commerce using our services and solutions:
Enhanced decision-making
Optimized inventory management
Customer segmentation for
targeted marketing
Efficient supply chain management
Personalized customer experiences
Fraud detection and prevention
Predictive analytics for
future planning
Competitive advantage
Boost Work Efficiency and Accuracy with Expert Machine Learning Support.
Get in Touch Now!
Cases of Using Artificial Intelligence and Machine Learning
Check out a few case studies that show why VOLTERA will meet your business needs.
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What Data Science technologies do we use?
Pandas
SciPy
TensorFlow
Numpy
ADTK
DBscan
G. AutoML
Keras
MLFlow
Natural L. AI
NLTK
OpenCV
Pillow
PyOD
PyTorch
FB Prophet
SageMaker
Scikit-learn
SpaCy
XGBoost
YOLO
Steps
Towards Good Development
These data engineering development stages ensure that solutions are well-designed, thoroughly tested, and aligned with business objectives.
Step 1 of 7
Initial Project Assessment
and Definition
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.
Step 2 of 7
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.
Step 3 of 7
Tech Design and Backlog Planning
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.
Step 4 of 7
Development Based on Sprints
Development takes place in iterative cycles known as sprints. During each sprint, the development team tackles tasks from the backlog. The team focuses on coding, testing, and integrating the components. At the end of each sprint, a functional part of the solution is ready for review.
Step 5 of 7
Project Wide QA
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.
Step 6 of 7
Deployment and Rollout
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.
Step 7 of 7
Support and Continuous Improvement
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.
