Building scalable data infrastructures
Providing actionable insights timely
Data Engineering is the backbone of any analytics infrastructure. We help you select the most scalable tool stack and embed best practices in your processes.
We work with all the top providers of the modern analytics stack. Stitch and Fivetran for data extraction. Snowflake, Redshift, BigQuery and Exasol for analytics warehousing.
We are the creators of the open source data processing and modelling framework SAYN. It is a simple, flexible yet powerful solution to ensure maximum efficiency in your data processes.
The goal of analytics is to democratise the use of data across your organisation and generate actionable insights timely and efficiently.
It starts with data modelling. A process that transforms raw data from multiple sources into meaningful KPIs based on your business logic and stored in your own data warehouse. We help you build an effective data model using SAYN.
We then automate reporting and surface insights with your chosen visualisation tool. We have evaluated many platforms and are experienced in all top reporting tools such as Metabase, Looker, Tableau and MicroStrategy.
Unlock your unique competitive advantage with data science models built on your own customer data. These models can be productionised and integrated into your products and services.
We are experienced in building algorithms on customer lifetime value (CLTV), retention and churn predictions, customer behavioural segmentation, and Natural Language Processing (NLP) models to automate insights from customer text input or feedback.
These models are highly ROI effective when integrated with your product to optimise customer journey, funnel conversions, marketing and CRM strategies.