CyberCX has released its annual Digital Forensics and Incident Response Year in Review Report for 2023 



CyberCX Serverless Data Platform

Build and deploy your data platform in days, not months


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Becoming data-driven

“Data-driven decisions are based on evidence, not guesswork, so businesses can be more confident in their choices. This leads to better products and services, which, in turn, attracts more customers.” (Forbes) 

For organisations to survive and thrive in today’s technological world, they need to rely on data. Accurate data can help to make the right decisions in the right timeframe, but while useful data is everywhere, it also has different formats, quality, and owners. These are only some of the challenges that organisations face on their data journey. CyberCX’s data team brings a wealth of knowledge and expertise – helping to significantly accelerate the data journey.


What is CyberCX Serverless Data Platform?

We understand that the business requirements of our customers are unique, but a lot of the underlying technical elements required are very similar. 

That understanding put us on the path of continuous innovation and improvement, where we designed a platform that helps our customers to become data-driven – unlocking and future-proofing an organisations’ progress.

Some of the specifics of our serverless data platform include: 

  • Scalable data lake storage 
  • Unified data governance 
  • Serverless – pay for what you use 
  • Fully automated DevOps provisioning and CI/CD 
  • AWS managed services – no licensing 
  • Cost-effective 

Benefits of CyberCX Serverless Data Platform

Bring data together

Generate insights

Make decisions

Clean and transform


Customer value:

  • Time to market: 10-15 days for the deployment of the foundation of the platform to production
  • Fully automated DevOps provisioning and CI/CD 
  • Scalable data lakes storage 
  • Unified data governance 
  • Highly modular platform, configurable for various business scenarios 
  • We work closely with the customer data engineering team (if required) to help with knowledge sharing 
  • We work in an agile way and deliver value in a continuous manner with regular demo sessions

Engagement process

We have a number of engagement options


1. Data Driven Everything Workshop – In collaboration with the customer and AWS, we will conduct a workshop to showcase the capabilities of our data platform and show what is possible. This session will also help us to understand customers specific requirements and define what success means to them.

Duration: 1 day (Optional)

2. Data Discovery and Exploration – Our data team along with the customer SMEs, will engage in a series of sessions to identify the datasets that need to be ingested into the data platform. We will prioritise the ingestion process based on their importance.

Duration: 2-3 days (Optional)

3. Base platform provisioning – Our data team will architect and build the data platform within the customer’s AWS environment (dev/test/prod) including the ingestion process for the identified data sets (max 2 datasets to start with). In the case that a customer needs a provisioning of the Control Tower, it would require an additional 4-5 days.

Duration: 15 days.

4. Further customisation – Once the base platform is established, we will continue working on the next set of business requirements. Throughout the engagement, we will maintain close collaboration with the customer’s team. If the customer has an in-house data engineering capability, we will onboard them onto the platform, enabling them to actively contribute to the development and facilitating a smooth handover in the future. 

If a customer lacks internal development capabilities, our CCX data team can independently handle the ongoing development work. 

Business use cases


Our platform is designed to be highly scalable and modular which allows the implementation of virtually any business scenario. 

1. Generic purpose Data Platform – various sources are ingested, transformed, cleaned, enriched and used for reporting, predictive analytics, ML etc. 

This use-case is usually most popular among the smaller organisations and those that are just starting out on their data journey. 


2. Specific use-case based Data Lake like the generic purpose data lake, this case is shaped around very specific business requirements such as the Customer360 lake. 

Many organisations have come to the realisation that understanding their customer is a must. Reasons include improving customer retention, success of the product/service, and shaping of new products. There are many direct and indirect ways that customers interact with organisations (eg. sales, contact centre, marketing platforms, social media, and events). 

The abundance of data sources can make it a difficult task for organisations to have a clear and holistic view. This is where the Customer360 Data Lake can help significantly. 


In this case we have a very specific set of data sources that focus on customer data. 

We also have GenAI integrated into our solution, where we can ask simple questions through Chatbots, SMS, etc. and receive a cohesive answer based on the aggregated data. 

Sustainability lake

The subject of sustainability has been close to the top of our minds and with every individual doing what they can, it would be good to understand what the effect of that effort could look like on a large scale. 

ESG (Environmental, Social and Governance) regulations are being implemented at the government level with organisations beginning to see requirements coming through which they need to comply with. In the future, we expect that organisations will be measured by these sets of metrics.

As an example, the data required for environmental metrics would be highly diverse: waste management, water usage, carbon footprint etc. 

A Data Lake is the perfect place to bring corresponding data together and apply calculations to obtain required metrics.



3. Data mesh in this case multiple different lakes are combined between themselves and act as a data producers/consumers.


4. Existing Data Lake migration into the Serverless Platform

Some organisations are already running data platforms on Hadoop, Snowflake etc. however they are looking to migrate because of either performance or cost reasons into the Serverless Platform.


Case study

Palmerston North City Council: PNCC has a great vision of making the city more aware of itself and also to democratize the access to data. We use the CyberCX data platform to help with achieving our goals.

ClassicGroup: Classic Group is on the mission to reimagine the construction business and use data to guide their decisions. We use the CyberCX data platform to bring together information from different parts of the business and produce valuable insights. 

2degrees: 2degreees were looking to improve performance of a number of key reports used by the business. We helped them to migrate the underlying data into the cloud and used the CyberCX data platform to streamline the processing which resulted in a significant reduction in the time it took to generate reports.

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