We develop and deploy enterprise analytics solutions using modern analytics tools that help you discover, interpret, and communicate meaningful patterns in your data. Working with your business stakeholders, we do requirements gathering, data profiling, data modelling, and front-end dashboard development to ensure your BI solution serves your specific needs and brings out the business value. 

If you want to get more out of your existing analytics investments, we can optimise your existing BI platform and toolsets. We will assess your current limitations and create and execute a plan to improve reporting processes and the front-end delivery to ensure you’re taking advantage of everything your BI tool has to offer. 

A well-designed BI solution automates reporting practices and contains visualisations that clearly communicate the business context and meaning within complex data. We will work with you to build intuitive, interactive dashboards and reports that improve data analysis and allow decision makers to quickly understand what's working well and what isn't, and understand what follow-up analyses need to be done to answer business questions. 

We will help you define the analytical platform that suits your current and future business needs best, taking into account your existing investments, your current business requirements and issues around scalability and integration. Modern analytics platforms will allow you to bypass the typical obstacles associated with growing data demands (expensive retooling, complicated integrations, inability to harness new technology etc…) and seamlessly integrate new data sources as needed.

In some cases, it is more suitable to run some if not all of the Analytics and BI services on the cloud to take advantage of modern infrastructure and security services as well as scalability. We will work with you to define the workloads that would benefit from moving to the cloud, develop a strategy for cloud migration and implement the migration in a way that your business is not disrupted but proceeds to the next stage seamlessly. 

We will make sure your data governance program is designed to be adopted. Starting with your organisational readiness, we will help you understand where gaps exist in your processes and people and then create an all-encompassing enablement plan. We specialise in education and training, change management, policies and procedures, and all aspects of organisational readiness.

In addition to ensuring you have the processes, standards, and policies in place to effectively govern data across all stages of the data lifecycle—we specialise in master data management so that your organisation’s most critical data is centralised and trusted.

When it comes to emerging AI software, we take it seriously – adhering to laws and regulations and upholding ethical use of data.

We will help you give meaning and definitions to all the data assets in your organisation through the selection and implementation of data governance tools and utilities, including a data glossary, data dictionary, data catalogue and data lineage. Depending on your analytics maturity, we will help you determine which artefacts are necessary and a practical plan for building and maintaining the overall ecosystem.

When you commit to data governance, you need to know that your efforts are resulting in more strategic decisions driven by higher-quality data. We will work with you to establish data quality rules, define success criteria, implement technology, and automate your processes. We also design data quality programs that establish company-wide rules and procedures to ensure trusted data.

Achieve regulatory compliance without the dread. We’ll help you navigate the complex landscape of regulatory requirements and help you classify, store, and manage your data in compliance with regulations such as GDPR, IFRS, CCPA etc avoiding fines and protecting your reputation.

As more and more organisations become more data-driven, the use of AI increases exponentially. To manage the risk in misuse of models in various business decision making, it is becoming more importance to define AI/ML model governance. AI / ML model governance framework will ensure the quality of the models used and hence resulting in trust worthy decision making and operational effectiveness.

We’ll first determine if you’re ready to make the move by reviewing your current environment—corporate and remote workforces, business needs and priorities, data, regulatory and security concerns, existing on-prem and IT infrastructure, applications, and dependencies. With a firm understanding of your operations and existing assets, we'll recommend the best path forward for your cloud migration. 

Organisations that define a cloud migration strategy and use a roadmap to guide their move to the cloud, experience quicker success with fewer disruptions. After assessing your cloud readiness, we will develop a custom cloud migration plan that includes our recommendations for a deployment model, cloud platform(s), what data and apps to migrate, a security framework, and a prioritisation and migration timeline. 

With this service, we execute the Cloud Migration Plan with you, ensuring a successful transition so that you realize business value and benefits quickly. We’ll accelerate the migration of your data assets and analytics tools to the cloud with minimal downtime for your business. 

As your data and analytics platforms are moved to the cloud, we continually optimise your cloud resources and identify areas for cost savings as your business evolves. 

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We build a secure and flexible data analytics platform leveraging hybrid and multi cloud best practices to build scalable data solutions so as to grow linearly along with your business and promote high quality, relevant, and accessible data. 

Cloud-based, on-premise, and hybrid–we build secure and flexible data architectures that promote the use of high quality, relevant, and accessible data. Built to grow along with your business, a solid data architecture supports your analytics needs, including business intelligence, data science, custom applications, and regulatory reporting. 

We build data warehouses on modern platforms using tried-and-tested techniques to provide a central, governed location for structured and semi-structured data assets. We advise where your data should reside in purpose-built data repositories – data warehouse, data lake, data mart or a combination of all three. 

Get an evaluation of your existing on-premise, Microsoft Azure, GCP or AWS environments for operational excellence, security, reliability, performance efficiency, and cost optimization. We'll provide detailed recommendations and guiding best practices to improve on these five areas and get the most from your investment. 

We will help you select the right data integration tools and techniques for your disparate data and determine where you should integrate your data, such as in a data lake, a persistent staging layer in a data warehouse, or a dimensional warehouse. We will also prioritise which data to integrate—and which to not—to control your costs associated with integrating, transforming, and storing your data.

We design and implement data pipelines that utilise modern tools to automate workflows and testing, standardise and speed up data transformation, remove data engineering bottlenecks, and bring more people in different data roles to the pipeline development process so that your data is ultimately more useful for decision making. 

Your data needs to be cleansed, combined with disparate data, and enhanced with derived business logic to create a trusted business-ready layer in your data warehouse. We help you transform raw data into actionable information using tried-and-tested principles, technologies, and techniques to create robust analytics solutions for end user consumption.

DataMobius has created reusable frameworks for ELT and ETL paradigms which allow you to quickly ingest data to your data estate with consistent naming conventions, auditable processes, and easily understood lineage for the ingestion pipeline. 

We will help you establish realistic standards and thresholds for data quality, determine your best approach to data cleansing (sometimes human intervention makes more sense than expensive technology), optimise your existing cleansing tools, and get buy-in from your organisation to support initiatives that promote data quality. 

We follow a very robust security framework during the end to end data engineering cycle and most importantly conform to all the security standards and requirements as applicable for the period while data is in transit. 

We will work with your business teams to identify analytical use cases that will help you achieve your business goals efficiently. This involves a collaboration of your business knowledge, data and our expertise in Advanced Analytics, ML and AI. 

Adopting use cases is often a large effort on the part of organisations, in terms of personnel, resources, and management commitment. We will work with your business and IT teams in order to create a roadmap of analytical exercises customised to your organisation’s resources and capabilities. 

We will build data products that solve the business use cases. Our experts have experience across industries, data types and technologies, from utilising sensor data, images including satellite imagery, to more traditional behavioural data, from small data to billions of CDR (core data record) / interactions.

One of the biggest hurdles to implementing Advanced Analytics/AI in organisations is the lack of faith in the outcome of the analytical exercises and the ability of the organisation to apply it. We will help you design experiments with clear metrics that will confirm the suitability of the outcomes and estimate the potential impact to your organisation of roll out at scale.