Transform your raw data into valuable insights.
Big data analytics solutions
We specialize in sifting through massive datasets to uncover patterns and trends that can drive your business forward. Whether you’re looking to enhance customer experiences, optimize operations, or make data-driven strategic decisions, our team of experts is here to help. We use state-of-the-art tools and techniques to analyze your data, providing you with the clarity and foresight needed to stay ahead in today’s competitive landscape.
Our delivery approach
Big Data Analytics solutions, involving generating insights from vast amounts of data, are intrinsically complex in nature. As such they benefit from a standardized project approach, where consistency of execution enables the use of best practices at each stage of the project.
01. Problem Definition
We start by deeply understanding your business goals and objectives, identifying the key indicators of success. This involves detailed stakeholder analysis to ensure all relevant parties are included and their needs addressed. Setting clear, measurable objectives and defining the project scope helps align expectations and provides a solid foundation for the project.
02. Data Inventory and Collection
Not all of the data that’s generated every day is collected or used. We’ll work with your IT and data teams to to catalog existing data sources, assess data quality, and identify data gaps. This phase includes determining what data should be collected, designing and implementing suitable data storage solutions such as Data Lakes or Data Warehouses, and ensuring data is collected efficiently and effectively.
03. Data Cleaning and QA
Our team conducts a thorough data quality assessment and profiling to determine the data’s accuracy, completeness, consistency, and reliability. This step involves identifying and handling missing data, understanding data distributions, and checking correlations among data categories. We also perform data transformation, encryption, and compression as needed to prepare the data for analysis.
04. Data Analysis and Insights Generation
Using a variety of advanced analytics techniques, including statistical modeling, development of algorithms or heuristics, and data mining, we analyze the clean data to extract meaningful insights. Our iterative analysis and feedback loops ensure continuous refinement of models and insights, adapting to new data and changing business conditions.
05. Representation and Visualization
In collaboration with UI experts, we create intuitive visual representations of the processed data and insights. These visualizations are tailored to communicate the analysis clearly to the target users. We engage end-users early and throughout the visualization process to ensure the final product is actionable and meets their needs.
06. User Feedback and Iteration
To ensure continuous improvement, we incorporate user feedback loops throughout the project. This iterative process allows us to refine our solutions based on real-world usage and feedback, ensuring that the final product remains relevant and useful over time.
Our team unit
At Stokedge, we structure our Big Data projects into agile, independent units known as Pods. Each Pod is a self-sufficient team equipped with all the necessary skills to deliver comprehensive Big Data Analytics solutions from start to finish. This model not only enhances agility and responsiveness but also fosters continuous improvement and deep expertise through stable team composition.
Meet the team
UX/UI Designer
The UX/UI Designer transforms complex data insights into intuitive and compelling visualizations. They design dashboards and reports that effectively communicate the analysis to stakeholders, ensuring that the visual representations are user-friendly and actionable. Their work bridges the gap between raw data and its practical application in business contexts.
DevSecOps Engineer (Infra)
The DevSecOps Engineer is in charge of the infrastructure architecture and implementation, ensuring that the systems used for data processing are robust and scalable. They manage the deployment of models and maintain security protocols, continuously monitoring the infrastructure to ensure optimal performance and protection against threats. Their role is vital for maintaining the integrity and security of the data analytics environment.
Domain Expert
We often integrate Domain Experts into our pods to provide specialized knowledge and insights specific to the project’s industry or functional area, such as or retail pricing, or stock management. They ensure that the solutions are tailored to meet the unique challenges and requirements of the specific domain, adding a layer of contextual expertise that enhances the relevance and effectiveness of the project’s outcomes.
Pod Lead
The Pod Lead is responsible for overseeing the entire project, ensuring alignment with the client’s business goals and objectives. They manage project timelines, coordinate the efforts of the team, and serve as the primary point of contact with the client’s management team. The Pod Lead ensures that all client expectations are met, facilitating clear and effective communication throughout the project.
Data Engineer
The Data Engineer handles data collection and integration, designing robust information architectures that support efficient data flow. They ensure the quality of the data through meticulous quality checks and bias assessments, and enforce data policies to maintain compliance and security. Their work forms the backbone of the data pipeline, crucial for subsequent analysis and processing.
Data Analyst
The Data Analyst explores and analyzes the collected data, employing statistical modeling, algorithm development, and data mining techniques to uncover valuable insights. They play a critical role in interpreting the data, developing heuristics and models that translate raw data into actionable business intelligence, thus supporting strategic decision-making.