Data Migration Services and Data Cleansing

Overview

Data migration is the process of moving data from one system to another, such as from spreadsheets, legacy systems or a data warehouse into a new platform or a data lakehouse. Bad data doesn't get better when you move it. Duplicates, errors and gaps travel with it, and they undermine your new system, your reporting and your AI from day one.

We clean, standardise and enrich your data before it lands, then put the policies in place to keep it that way. Garbage in, garbage out is a principle every one of our consultants works by.

Who is this for?

Data migration without the mess

You're moving to a new system, such as an ERP, CRM or data platform, and don't trust the data you're bringing with you.

Your data is spread across spreadsheets, databases and legacy systems that don't agree with each other.

Duplicates, errors and gaps are undermining your reporting and decisions.

You've moved to a data lakehouse, but the data in it still needs cleaning before people or AI can use it.

You want to get more value from your data by filling gaps or adding missing information.

What's included?

Clean, enriched data, wherever it needs to go

Data migration services

Planned, low-risk migration from spreadsheets, legacy systems, databases, data warehouses and data lakes into your new system or lakehouse, cleaned and converted along the way. Platform agnostic across Azure, AWS and Google Cloud.

Data cleansing and standardisation

We remove inaccurate, corrupt, duplicate and irrelevant data, fix errors from manual entry, faulty sensors or failed transfers, and correct naming, spelling and labelling. Wherever possible, we automate cleansing so it keeps running after we leave.

Data enrichment and augmentation

We combine your internal data with trusted external sources, such as demographic, geographic, ABS, economic, market and weather data, to create a single source that's more valuable than its parts. Through our third-party data partnerships, we can source the data you need.

Metadata curation

We design the metadata that describes your data, using AI to create and manage it automatically where possible, so people and AI tools can find and understand it.

Data management policies

Ready-made policies, customised to your organisation, covering master data management, data dictionaries, data ownership and stewardship, data sharing, erasure, and privacy aligned to the Privacy Act and Australian Privacy Principles.

Validation before go-live

We validate, sense-check and quality assure the data against the source before cutover, so you know it's complete and correct.

How we deliver it

From messy source to trusted data

Assess and profile

We map your data sources and measure data quality, so you know exactly what needs fixing.

Cleanse and enrich

We fix errors, remove duplicates, fill gaps and agree the rules that keep the data clean.

Migrate and validate

We move the data in planned stages and reconcile it against the source at each step.

Land and hand over

Your data lands in its new system or lakehouse, ready to use, with the quality rules documented for your team.

How we deliver

Data migration services, done in stages

Moving data is one of the riskiest parts of any system change. We plan every migration so nothing is lost, broken or left behind.

Source assessment and mapping

We identify every data source, from spreadsheets and Access databases to SQL Server, Oracle, legacy applications, on-premises data warehouses and data lakes, and map each one to its new home.

Cleanse and transform in flight

Data is cleaned, standardised and converted into the right format as it moves, so problems aren't carried into the new system.

Staged migration with reconciliation

We migrate in planned waves, reconciling record counts and values against the source at every stage.

Cutover and rollback planning

We plan cutover around your business, with a tested rollback plan in case anything needs to be reversed.

Legacy decommissioning

Once the data is verified, we help you retire old systems safely, so you stop paying to maintain them.

We migrate to Azure, AWS, Google Cloud, Databricks and Snowflake, and we're platform agnostic, so we recommend what fits your organisation. Microsoft funding may be available for eligible projects.

FAQs

Data migration and cleansing questions

Do we need a data lakehouse to use this service?

No. We can migrate and clean data into any new system. If you're building a lakehouse, we can clean the data as it lands so it's ready for reporting and AI.

What data sources can you work with?

Spreadsheets, databases, legacy applications, data warehouses and data lakes. If your data lives somewhere, we can usually get it out, clean it and move it.

Can you clean data that's already in our lakehouse?

Yes. Many organisations move data first and find quality problems later. We can profile and clean data already in your lakehouse.

What kinds of data can you use to enrich ours?

Common sources include demographic, geographic, ABS, economic, market and weather data, as well as third-party marketing and behavioural data. We can also augment image, audio and video data for machine learning.

How do you keep data clean after migration?

We automate cleansing where possible and customise our ready-made data management policies, covering master data management, data dictionaries, stewardship and ownership, so quality doesn't drift once the project ends.

How is this different from the AI-Ready Data Layer?

This service makes your data accurate and complete. The AI-Ready Data Layer then adds the business context, access controls and structure AI needs to use it. Clean data comes first.

How do you handle sensitive data during migration?

We work within your security and access requirements throughout, and validate the data at each stage so nothing is lost or exposed.

Data Migration and Data Cleansing