Two decades inside enterprise data programmes taught us where the tooling falls short. So we engineered our own, and we bring it to every engagement.
Ixia Data Quality AI 2.1
SAP-aware profiling, business-defined rules, fuzzy and semantic duplicate detection, AI-generated recommendations and Power BI executive visibility. Built by Ixia, run on real programmes.
AI applied where it adds real business value, not where it’s fashionable.
Large firms separate strategy from architecture from delivery from testing. Ixia works across those boundaries: the person who understood the business issue can interrogate the source data, design the solution, oversee the transformation logic, prove the reconciliation and stand at cutover.
That combination is unusual, and it is why our programmes hold together under pressure.
Meet the peopleBreadth matters less than depth. These are the platforms we work in daily, grouped by the job they do.
The systems of record we work inside.
Moving and transforming data at programme scale.
Measuring and enforcing what the business defined.
Turning governed data into daily decisions.
SAP, JiVS, Syniti, Microsoft and the other platforms named here belong to their owners. We implement them with depth. Ixia Data Quality AI is ours.
Technology ecosystem
For historical data and legacy decommissioning architectures we work with JiVS, the platform from Data Migration International. The platform is theirs. The migration architecture, data quality, reconciliation and delivery around it are ours.
A habit, not a slogan. Each of these was built because a real programme needed it, drawn from the Ixia archive of decks and whitepapers.
2014 onwards
SAP Information Steward held the data quality rules, but the business could not see failure trends across the enterprise without living inside the tool.
An add-on that extracts rule results from the Information Steward repository via SAP Data Services into SQL Server, giving business users an enterprise view of rules, failures and trends without touching the IS console.
2018
External files entering migration and integration landscapes carried no enforcement: wrong structures and rogue submissions surfaced as load failures.
A control system that manages inbound external files and enforces governance rules before the data reaches SAP Data Services processing, documented as an Ixia whitepaper.
2018
Large IDoc batches transmitted sequentially, and standard parallelism capped out long before the cutover window did.
A workflow pattern that parallelises IDoc transmission beyond the standard limits, cutting transmission time on large batch loads, documented as an Ixia whitepaper.
Retail delivery
Creating and delivering point-of-sale material across promotions involved gaps nobody owned: status lived in inboxes and spreadsheets.
A tracker giving promotion visibility, POS element tracking, workflow management, task status, project roles and stakeholder communication in one place, with reporting on top.
Operational analytics
Competing work requests against a finite consultant pool, prioritised by whoever asked loudest.
Analytics with scoring and ranking logic to prioritise demand, and capacity views across bench, allocations, contractor risk and availability.
Retail delivery
Store locations and operating information were wrong in external location and search data, sending customers to closed doors.
Analysis across addresses, geolocation and operating hours to find and fix location inaccuracies at estate scale. Data quality as a customer-experience outcome, not a score.
Hospitality delivery
Hotel management decisions waited on manual preparation of information scattered across POS, PMS and revenue management systems.
An engineered data product consolidating the source systems into current management information with drill-down, multi-device access and views per management role.
ERP programme delivery
A complex ERP implementation needed one honest view of planned versus actual across streams, including data migration and testing.
PMO reporting built from Microsoft Project data: programme streams, delivery variance, exceptions and risk areas, visible to the people accountable for them.
Bring the architecture diagram you distrust. We will tell you what we would do with it.