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analytics & cloud data warehousing

Mero has partnered with Google to provide an efficient cloud-based analytics solution, called Cloud Analytics OnRamp. By utilizing our expertise in SAP and understanding the complexities of moving to a modern architecture, Cloud Analytics OnRamp has been created to rapidly relocate your data into the Google Cloud Analytics Platform, BigQuery using process automation.

Google leads the cloud-based analytics platform market, recently acknowledged as the Leader in Cloud Data Warehousing in the 2021 Forrester Wave. insideBIGDATA has indicated that 60% of mature organisations will move all their analytics to the cloud within the next two years. The benefits are great, but for many businesses, it is not an easy task to plan and execute.

If your organisation is discussing a move to the cloud, partway through the transition or stuck somewhere in between, Cloud Analytics OnRamp is designed for you.

“If anybody knows how to deal with large volumes of data, it’s Google. We feel confident we could not have built the system as securely without the huge amount of experience Mero/CDP brought to us. And we believe we’ve made the right decision with Google Cloud.”

Jeffrey Westcott

IT Manager, Briscoe Group


Cloud Analytics OnRamp platform

Cloud Analytics OnRamp rapidly provides a unified view of all your organisational data, from any SAP, SaaS or on-premise source. Once this view is established, the data and new capabilities are available to drive business value from within the Google Cloud Analytics Platform.

Often organisations struggle with the fragmentation of data when moving data to the cloud. Rather than invest in data virtualization as a temporary operating space, our approach is to deliver over existing source systems, datamarts, and data warehouses, building up the unified business layer in a similar timeframe to the virtualization option. This avoids the fragmentation of your data when you migrate from on-premise to the cloud. From there, a phased remediation/or removal of legacy warehouses can occur.

Cloud Analytics OnRamp establishes a secure and governed cloud analytics foundation that is easily deployable, Mero manages the version updates and support.

On top of this foundation layer, there is also an application layer, using best-in-class tools and standardised migration/automation processes that drive Analytics and Artificial Intelligence to transform your business. The application layer includes landing, transformation and presentation of the SAP (or other) data ingested. Mero can assist with building on top of these data layers, or we can help enable your in-house data engineers to swiftly develop them in a well-governed environment.


key benefits

Develop with high speed, and keep control

Don’t start with a small ungoverned sandpit that grows out of control really fast. Empower your Data Engineers and Data Scientists with leading-edge capability within a well-governed agile framework, using DataOps and DevOps. This includes CI-CD, automated testing and auditing. The cloud foundations are deployed as IAC based on a high security, zero trust model

Quick and easy setup

Our accelerated transition process to the cloud uses a staged methodology, where we create an enhanced series of business views from existing data warehouses and data sources. From there, Cloud Analytics OnRamp turns the business views into the data structures and transformations that are required

Get all sources in and fast

We use pre-built connectors, this allows for connection to other sources, SAP, SaaS, and on-premise, with a click of a button

We know SAP

SAP data extraction is our sweet spot; with many decades of experience in-house, we understand how to turn SAP data into usable business insights


leading tools

Cloud Analytics OnRamp is pre-loaded with everything your Data Engineers, Data Scientists, and Power/End Users need.


  • Juypter Notebooks
  • DBT
  • Google Data Catalogue
  • Google BigQuery
  • Google Cloud Composer (Apache Airflow)
  • Terraform, GitHub
  • Looker or BYO Visualization tool


  • Analytics
  • Dashboarding
  • Data quality/governance
  • Data wrangling
  • Artificial Intelligence
  • Machine Learning
  • Ability to publish analytics models in several formats
Reap the benefits of a

modern architecture

This IDC independent report details the clear value of BigQuery for SAP data, highlighting:


three-year return on investment(ROI)


lower three-year cost of data warehouse operations


more efficient data platform teams


faster delivery of business reports


higher productivity among analytics teams

$22.88 million

in revenue gains per year per organization


higher productivity among line-of-business teams




move to Google BigQuery

Google BigQuery is a serverless, highly scalable, and cost-effective multicloud data warehouse designed for business agility.

  • Democratize insights with a secure and scalable platform with built-in machine learning
  • Power business decisions from data across clouds with a flexible, multicloud analytics solution
  • Run analytics at scale with 26%–34% lower three-year TCO than cloud data warehouse alternatives


ML and predictive modelling with BigQuery ML

BigQuery ML enables data scientists and data analysts to build and operationalise ML models on planet-scale structured or semi-structured data, directly inside BigQuery, using simple SQL—in a fraction of the time. Export BigQuery ML models for online prediction into Vertex AI or your own serving layer

Multicloud data analysis with BigQuery Omni

BigQuery Omni is a flexible, fully managed, multi-cloud analytics solution that allows you to cost-effectively and securely analyse data across clouds such as AWS and Azure. Use standard SQL and BigQuery’s familiar interface to quickly answer questions and share results from a single pane of glass across your datasets

Interactive data analysis with BigQuery BI Engine

BigQuery BI Engine is an in-memory analysis service built into BigQuery that enables users to analyse large and complex datasets interactively with sub-second query response time and high concurrency. BI Engine natively integrates with Google’s Data Studio, and now in preview, to LookerConnected Sheets, and all of Google’s BI partners solutions via ODBC/JDBC

Geospatial analysis with BigQuery GIS

BigQuery GIS uniquely combines the serverless architecture of BigQuery with native support for geospatial analysis, so you can augment your analytics workflows with location intelligence. Simplify your analyses, see spatial data in fresh ways, and unlock entirely new lines of business with support for arbitrary points, lines, polygons, and multi-polygons in common geospatial data formats


Briscoe Group: unlocking retail data insights with on-prem data piped to cloud analytics

By connecting its on-premise data warehouse with BigQuery, Briscoe Group is achieving fast, automated daily data reporting in under 3 minutes while creating the potential for new insights to drive its business.


  • Daily manual sales reports are now automated with 75% time saved
  • Manual sellthrough reports that were prone to human error now run under automation in less than 3 minutes
  • Data is now combined from multiple sources to create new analytics offerings and improved business intelligence
  • All improvements achieved while maintaining highest standards of data integrity, security, and privacy

Briscoe Group (BGP) is a pioneer of the New Zealand retail landscape. Running close to 90 stores across three brands and a strong online presence, BGP is a well regarded mainstay for shoppers across the nation.

In 2008, BGP adopted an on-premise SAP business warehouse, which underpins its retail and supply chain operations to this day. But as the company began considerations around an improved data strategy, BGP saw a need to extract the raw data into a dedicated data service that could unlock new analytics opportunities.

“We wanted more flexibility, more agility, and the ability to bring together a range of external data feeds. We also wanted the ability to experiment, which would be a challenge to do inside a traditional, on-premise data warehouse.” says Jeffrey Westcott, IT Manager at BGP.

Having a long-term technical partnership with Mero/CDP Group, BGP explored its options to develop a hybrid model where it would maintain its on-premise warehouse while building a new data platform in the cloud.

Want to know more? Chat with us about getting started with Cloud Analytics OnRamp