Data Operations

Data is King, yes, but is your data warehouse optimised to support your AI initiatives? Our DataOps team has the expertise to consult, implement, support and train the design, architecture and build of modern data and analytics platforms.

About Data Ops

About Data Ops

About Data Ops

DataOps references improvements to the quality and delivery of premium data analytics. DataOps breaks down barriers between data development and IT operations to reduce cycle time and ensure data analytics is implemented. DataOps synchronizes heterogeneous activities, including data sourcing, data prep, data cleansing, data loading, data testing, deployment, analysis, and science.

Our analytics project approach enables your whole organisation to get the most out of your data and realise true business value.

How it works

How it works

1

Define your strategy & roadmap

This is the most important step in any analytics journey. Let us help you assess and document the vision and goals of your organisation’s data strategy. Defining the strategy and roadmap ensures your highest-value analytics projects go the right direction and don’t run over budget.

2

Design & build the platform

Our DataOps team starts by assessing your data landscape and capacities against your requirements. We then design the cloud architecture, build the environments and implement everything from cloud resources to automation, monitoring, governance, security and disaster recovery plans.

3

Engineer your data

Data engineering is the cornerstone of modern data warehouse. It is an aspect of data science that our team is experienced in. We focus on the best practical applications of data collection, automation and interpretation to prepare your business for big data analytics.

4

Leverage data analytics

We build self-service reports and dashboards for your team to analyse big data and gain valuable insights. When done right, machine learning algorithms consume the data engineered seamlessly and your data platform becomes a solid foundation to launch AI initiatives straight away.

5

Support & training

We are committed to supporting your team during your organisation’s analytics journey. Support and training are provided at every level to keep the project within budget and service agreements. By training your employees, you can bring support and development roles back into your business.

How it works

1

Define your strategy & roadmap

This is the most important step in any analytics journey. Let us help you assess and document the vision and goals of your organisation’s data strategy. Defining the strategy and roadmap ensures your highest-value analytics projects go the right direction and don’t run over budget.

2

Design & build the platform

Our DataOps team starts by assessing your data landscape and capacities against your requirements. We then design the cloud architecture, build the environments and implement everything from cloud resources to automation, monitoring, governance, security and disaster recovery plans.

3

Engineer your data

Data engineering is the cornerstone of modern data warehouse. It is an aspect of data science that our team is experienced in. We focus on the best practical applications of data collection, automation and interpretation to prepare your business for big data analytics.

4

Leverage data analytics

We build self-service reports and dashboards for your team to analyse big data and gain valuable insights. When done right, machine learning algorithms consume the data engineered seamlessly and your data platform becomes a solid foundation to launch AI initiatives straight away.

5

Support & training

We are committed to supporting your team during your organisation’s analytics journey. Support and training are provided at every level to keep the project within budget and service agreements. By training your employees, you can bring support and development roles back into your business.

Superpower your AI projects

Superpower your AI projects

Superpower your AI projects

Increase speed & quality

Adopting a modern data warehouse approach increases the quality and speed of delivering analytics to the business. Your insights are accurate and easily accessible.

Improved collaboration

Leverage Data Lakes and a Data Catalog to actively drive improved collaboration across teams, enable automated discovery and sharing of datasets more easily.

Predictive analytics

Leverage your analytics investment and step up to the next level with predictive forecasting and prescriptive decision making. Steer the business now to stay competitive in the future.

Enhanced machine learning

Enhance ML with DataOps so you’re set for success with reliable big data processing and feature stores that support quick and reliable re-use of analytics across the business.

Increase speed & quality

Adopting a modern data warehouse approach increases the quality and speed of delivering analytics to the business. Your insights are accurate and easily accessible.

Improved collaboration

Leverage Data Lakes and a Data Catalog to actively drive improved collaboration across teams, enable automated discovery and sharing of datasets more easily.

Predictive analytics

Leverage your analytics investment and step up to the next level with predictive forecasting and prescriptive decision making. Steer the business now to stay competitive in the future.

Enhanced machine learning

Enhance ML with DataOps so you’re set for success with reliable big data processing and feature stores that support quick and reliable re-use of analytics across the business.