Data analytics and AI

Data analytics for actionable insights

Every single enterprise has some form of centralised data warehouse. The challenge is to extract insights that your business can trust. This is because the traditional data warehouse uses complex ETL (Extract, Transform and Load), is optimised for batch data and legacy business intelligence and is restricted to only a few users.

  • Do you use multiple systems as data sources for reporting?
  • Do you find that queries result in different results depending on data usage and export?
  • Do your results and analysis lack trust and credibility?
  • Do you struggle to optimise customer programmes, such as loyalty cards and incentives?

Big Data is not just for big companies
Just what is Big Data?

data warehouse and AI-1

What we do

Big Data means big opportunity. To gain insights faster, you need a cloud-based solution that can ingest, process and analyse huge volumes of complex data at scale. You can then reallocate resources from maintaining IT infrastructure to building revenue-generating initiatives and improving your customers’ experiences.

Our data services will help you to:

  • Create a targeted data strategy for your business needs
  • Automate the delivery of data into a data warehouse to simplify operations and bring together siloed data sources, creating a 360-degree “Single Customer View”
  • Protect business data at scale with built-in data protection and governance
  • Provide real-time insights, analysing business events as they unfold
  • Provide a data presentation and visualisation layer via third-party BI solutions and DataStudio
  • Build the foundation for AI, unlocking the predictive power of your data through machine learning models
data warehouse and AI

How we can help

We build a cloud based data warehouse as the single source of truth for all BI applications, increasing trust in any given insight and encouraging data driven decisions by making data and insights accessible to business. The data platform comprises of:

1. Data ingestion and validation

  • Programmatically ingest (batch) and cleanse incoming data
  • and manually ingest data via web app
  • to automate data delivery into the warehouse

2. Data storage

  • Data stored in serverless warehouse
  • Data translated and aligned to an agreed schema
  • Sync to partitioned BigQuery table with lifecycle management

3. Operation and Service Monitoring

  • Simplify data operations and monitoring
  • Make data and insights accessible
  • Dashboard surfacing data metrics

3 ways Google Cloud helps retailers analyse multiple data sources