What value looks like.

Data Visualisation

Automating the data in your business into a format that makes sense to you helps identify trends and movements quickly; providing sufficient time to decide and execute on the most appropriate action. 
Exploring your data with filters, slicers and through different levels of detail provides understanding and insights at all levels of management on a technology and platform that works for you.
By seeing data in real time you can access new opportunities that would often be missed due to an infrequent reporting intervals.

Data Warehousing

Consolidation of data from multiple sources into a business-wide data warehouse creates a consistent and repeatable dataset for visualisations, reporting and analytics. 
The complexity of data in source systems is significantly reduced for the end-user through robust and automated data pipelines; creating a stable and trusted dataset with a single view of your business.

Statutory Report Automation

Regulatory and Statutory reporting is often a repetitive and time consuming activity undertaken by senior members of your team.
By formalising the collection of data from multiple data sources, joining, validating and formatting into the correct format for submission will free up your team’s time to focus on their key deliverables.
Automating the process, with the necessary check-points and reconciliations, will improve consistency of the submission and provide opportunities for focus on value creation.

Single Version of the Truth and Master Data Management

Consolidation and standardisation of similar or overlapping data from multiple systems without the appropriate controls and rules may provide inconsistent and unreliable data.
Designing and automating data pipelines to provide a single and enriched view of your business will provide a trusted data source to make decisions with confidence and clarity.
This approach can be used similarly for enriching customer, vendor, product details, and for standardising business rules and key business measurements.

Data Quality Monitoring

Poor data quality can severely hamper visualisation and analytical projects. 
We can help build a view of your current data quality pain points and provide you with tools to track and monitor the success of improvement initiatives.