invisible
Our Services
Our consultants have hands-on experience at all stages of the data management life-cycle allowing us to tailor a service to meet your needs. We work closely with our clients, often on-premise, understanding their processes, practices, and requirements to ensure that we can deliver integrated solutions which really work.
Our approach encompasses a balance of project management, business analysis, and data science, providing our clients with clear expectations and communication. We are known for the following services-
Data Science
Swift DataLab consultants have broad experience in using data to derive insights, model behaviours and predict outcomes. In recent years this field has come to be known as data science. The relatively recent explosion of big data has meant that machine learning approaches are flourishing, with artificial intelligence now rapidly changing the way in which decisions are approached and made; for better and worse. We pride ourselves on providing an honest data science service, tailored to our clients’ needs.
Data Engineering
Data engineering is a specialization that provides data scientists and analysts with the tools, environments, and infrastructure needed to access data and derive their insights. Cloud technologies are transforming the way organizations host and deliver technology services, creating robust, scalable and maintainable platforms for data science. We can deploy scalable cloud-infrastructure capable of processing data-streams that support in-memory machine-learning, enabling real-time predictions and interventions. We can also advise on modern cloud platforms, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud.
Data Integration
Most organisations data systems are highly complex and interdependent. Manual hand-ins and hand-offs between teams need to be coordinated. Data pipelines need to be orchestrated to meet release schedules and service level agreements. Even backing out and rolling back changes can lead to permanent data loss and errors. Balancing IT resources to obtain efficiencies in performance and storage are not often aligned with analysts’ needs, and their actions typically lead to data duplication and silos. We have extensive experience of integrating structured and unstructured data across a range of technology ecosystems. Our data integration consultancy service will support the delivery of an effective enterprise-wide information management workflow, helping our clients get the most out of their data.
Data Quality
Data quality underpins every aspect of data management best practice; from acquisition to disposal and everything in between. All data scientists agree that most time-consuming part of their job is addressing the data quality issues that erode their model accuracy. Data quality control and assurance are critical factors in delivering a successful data management strategy yet are often overlooked and misunderstood. Our data quality service provides clients with the support they need to design, plan and execute a data quality strategy suitable for their data management systems and platforms, through to deployment of tools.
Data Transformation
Raw data is often difficult for analysts to work with as it requires substantial preparation before it can be used to derive valuable, trustworthy insights. The explosion of big data, and the adoption of “data lakes” to hold masses of unstructured data, rather than the more traditional structured “data warehouses” places additional burden on analysts, but also introduces new opportunities. Unkept “data lakes” quickly turn into “data swamps”, and transformation skills are the key to providing filtered, clean, quality data that can be confidently used for modelling and reporting. Swift DataLab has expertise handling large amounts of structured and unstructured data, presenting it to users at the appropriate level of detail for their needs, and helping them understand their data through useful visualizations.
Data Migration
Cloud solutions offer modern, intuitive, feature rich web-applications which are easier to deploy and maintain. However, data migrations are never straightforward. Existing processes are rarely comprehensively documented and managing downstream impacts and stakeholder expectations can be quite a challenge. Successful data migrations encompass several data management disciplines (including Transformation, Data Quality, and Reporting), wrapped around strong stakeholder and project management. Swift DataLab has extensive data migration experience, from moving highly sensitive data to secure cloud infrastructure, to providing platform upgrade assurance.