TimeXtender Data Integration

TimeXtender Data Integration is a metadata driven platform that automates the process of ingesting, preparing and delivering trusted data. It reduces the need for manual ETL development by managing data pipelines, transformations and business rules from a single platform. The result is a scalable data foundation for reporting, analytics and AI.

TimeXtender sits as a layer above your storage platform rather than replacing it. You design your ingestion, transformations, and data models once in TimeXtender, and it generates the underlying code and deploys to the platform you choose. Microsoft Fabric is one of those targets, alongside Azure SQL, SQL Server, Snowflake, and others.

For Power BI, TimeXtender builds the semantic models your reports run on. On Fabric it supports Direct Lake mode, so reports can read straight from the data in OneLake without a separate import step. The practical benefit is that your business logic and definitions live in one place, which keeps figures consistent across every report regardless of which tool consumes them.

Because the logic is separated from the storage layer, you are not locked into a single platform. If you move from Azure SQL to Fabric later, the models move with you. In our experience that flexibility matters most for organizations that are still deciding how far to go with Fabric.

For many organisations, yes. TimeXtender automates much of the work traditionally handled by ETL tools, including data ingestion, transformations, scheduling and metadata management. Instead of maintaining large amounts of custom code, your team manages the platform through metadata, making it easier to maintain and adapt as your business evolves.

TimeXtender is metadata driven, and that has a direct security consequence: it builds and deploys the code, but it does not need access to or control over your actual data. Your data stays in your own storage platform, whether that is SQL Server, Azure, Microsoft Fabric, or Snowflake, under your own access policies.

Within that platform you can define database roles and restrict access at object level (views, schemas, tables, and columns) and at row level (specific data within a table), so people only see what they are supposed to see. Because all business rules, transformations, and models are stored as metadata, you also get documentation and data lineage automatically. You can trace any field back to its source and assess the impact of a change before you make it, which is also what keeps definitions consistent across reports.

For compliance, TimeXtender supports requirements such as GDPR, HIPAA, and SOX, alongside your own internal standards. One honest caveat: tooling supports governance, it does not create it. Naming conventions, ownership, and approval processes still need to be decided by your team. We help set that up during implementation.

TimeXtender supports more than 250 data sources, including Microsoft SQL Server, Microsoft Fabric, SAP, Business Central, Salesforce, cloud applications, REST APIs, spreadsheets and many other databases and business systems. New sources can be added without rebuilding your entire data platform.

The timeline depends on the size and complexity of your data environment. A relatively straightforward implementation with a limited number of data sources and reporting requirements can often be completed within a few weeks. More complex projects involving multiple systems, large data volumes, advanced business logic, or extensive reporting needs may take several months.

The overall duration is influenced by factors such as the number of data sources, the quality and structure of the existing data, integration requirements, governance needs, and the scope of the project. Organizations that are also modernizing their data architecture or preparing for initiatives such as Power BI, Microsoft Fabric, or AI typically require additional planning and implementation time.

During the initial assessment phase, we work with you to define the scope, priorities, and roadmap, providing a realistic timeline based on your specific environment and business objectives.

Three things drive it: the number and complexity of your data sources, the amount of transformation and business logic that has to be built, and the scope beyond core integration, such as data quality, master data management, and the storage platform you deploy to. A few clean sources feeding a handful of reports is a very different project from a dozen systems with poorly documented logic.

There are two separate cost components. The TimeXtender license depends on the products you use and is worth scoping early. The implementation effort is usually the larger variable. To be honest about where the time goes: the software reduces build time, but the implementation cost is driven less by TimeXtender itself and more by the state of your existing data and how clearly your business logic is defined. Undocumented logic is the most common reason a project runs longer than expected.

Yes. Whether your TimeXtender environment was built by your own team, another partner, or has grown organically over the years, we can help you get more out of it.

We work on performance optimization, architecture reviews, troubleshooting, platform upgrades, governance, and ongoing maintenance. Often the bigger win is simplification: removing data flows nobody uses anymore, cleaning up logic that has become hard to follow, and cutting the manual steps that creep in over time. We can also prepare your environment for a move to Power BI, Microsoft Fabric, or AI initiatives.

If your environment has become hard to manage, is slowing down, or no longer fits what the business needs, we start with an assessment and give you concrete recommendations, in order of impact. The aim is a platform that stays stable and easy to manage as your organization grows, not one that needs a rebuild in two years.