Bitmetric has been a Certified TimeXtender Partner since 2016. We help organizations build data platforms they can actually manage themselves, with trusted data for reporting, analytics, Power BI, Microsoft Fabric, Qlik, and AI.
Whether you’re modernizing your data warehouse, migrating reporting platforms, or preparing for AI initiatives, TimeXtender provides a scalable foundation that grows with your business. For example, Nature’s Pride uses TimeXtender as its central data platform, enabling hundreds of data driven decisions every day while saving hundreds of hours annually through automation.
TimeXtender combines four building blocks in a single environment: data integration, data quality, data enrichment, and orchestration. Together they cover the full path from pulling data out of your source systems to delivering governed, documented data for reporting and analytics. Because it all lives in one metadata-driven tool, you avoid stitching four separate products together, and you keep a clear view of what happens to your data along the way.
TimeXtender is a data platform for building and managing data warehouses, data lakes, and data models. It brings data from your different systems together into one trusted environment for reporting, analytics, Power BI, Microsoft Fabric, Qlik, and AI.
Most organizations have data scattered across ERP, CRM, financial systems, databases, cloud services, and spreadsheets. The result is reports that disagree, business logic that is hard to maintain, and a lot of time lost to manual data preparation. TimeXtender automates the integration, modeling, documentation, and governance of that data, so you spend less time building pipelines and more time using the results.
Because everything is governed and documented in one place, the data you deliver is also ready for AI. Models and agents are only as reliable as the data behind them, and a trusted, well structured foundation is what makes AI initiatives work in practice rather than just in a demo.
Build a data infrastructure capable of ingesting, transforming, modeling, and delivering clean, reliable data.
Establishes trust in data and enhances the accuracy of reports. With this, users can take control of their data, ensuring that inaccurate or poor-quality data does not compromise business operations.
Facilitates a comprehensive and cohesive approach to managing, synchronizing, and improving critical business data across diverse systems and departments.
This advanced product automates complex workflows, reducing manual errors and improving operational effectiveness.
Create a single, trusted source of data across your organization. By standardizing definitions, calculations, and business logic, everyone works from the same numbers, reducing confusion and improving confidence in reporting and decision making.
Automate data integration, validation, documentation, and maintenance tasks. This reduces repetitive manual processes, minimizes errors, and allows teams to spend more time generating insights instead of managing data.
Build a robust data foundation that can grow with your organization. As new systems, users, and reporting requirements are added, your data platform remains structured, maintainable, and easy to manage.
Reliable data is the foundation of every successful analytics and AI initiative. By bringing data together in a governed and trusted environment, organizations can support advanced reporting, self service analytics, machine learning, and AI with confidence.
We do more than implement TimeXtender. We help you make decisions that will still make sense three years from now.
The case highlights how Medux used TimeXtender to overcome fragmented data sources, inconsistent business logic, and limited data integration, creating a scalable and trusted data foundation for reporting and analytics.
Nature’s Pride implemented TimeXtender as the foundation of its modern data platform, enabling real time reporting, improved scalability, and a smooth transition to Power BI.
A short call is usually enough to find out. No preparation needed, just bring your questions.
We start by understanding your data landscape, reporting requirements, and business challenges. As part of our TimeXtender consulting approach, we identify opportunities, risks, and the best strategy for a successful implementation.
A successful TimeXtender implementation starts with the right architecture. We design a scalable data platform that supports reporting, analytics, governance, and future growth.
We connect data sources, build data models, and automate integration processes in TimeXtender. Throughout the implementation, we apply proven TimeXtender best practices for performance, maintainability, and governance.
Together with your users, we validate data quality, business logic, and reporting outputs. Before go live, we ensure the solution is fully tested and ready for production use.
We provide practical training for both users and administrators. This helps your team get the most from your TimeXtender environment and confidently manage it moving forward.
Whether you need ongoing support, platform optimization, or assistance with TimeXtender migration projects, our consultants are available to help. We continue to support and enhance your data platform as business requirements evolve.
Yes. TimeXtender is built to integrate data from a wide range of business systems, helping organizations create a single, reliable data foundation without replacing their existing technology. It supports connections to ERP systems, CRM platforms, financial applications, databases, cloud services, data lakes, and many other data sources.
Whether your data is spread across Microsoft Dynamics, SAP, Salesforce, SQL Server, Azure, Excel files, or other systems, TimeXtender can bring it together into a centralized and governed data platform. This allows you to standardize business logic, improve data quality, and create a single source of truth for reporting, analytics, and AI initiatives.
The best approach depends on your current architecture, data landscape, and business goals. Our consultants help you determine how TimeXtender fits into your environment and design a solution that supports both your current needs and future growth.
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.
Yes. Many organizations come to TimeXtender with a data warehouse built on hand-written SQL, SSIS packages, or another ETL tool that has become hard to maintain. TimeXtender can take over that role, with the existing logic rebuilt as metadata-driven models that are documented and easier to change.
The effort depends on how complex and well documented the current solution is. In our experience the transformations themselves are seldom the hard part. The bigger work is reconstructing business logic that was never written down. We map that during the assessment, so there are no surprises later.
A migration is rarely a one-to-one copy. It is a good moment to review which data sources, transformations, and reports are still in use, and to drop what no longer adds value. We usually run the old and new environment side by side for a while, so you can compare results before switching over.
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.
That depends on the expertise and capacity available within your organization. While TimeXtender is designed to simplify data platform development, many organizations choose to work with an implementation partner because the biggest challenges often go beyond the software itself.
Successful projects require decisions about data architecture, data modeling, governance, security, and long term maintenance. These choices can have a significant impact on the performance, scalability, and manageability of your environment as it grows.
An experienced TimeXtender partner can help you avoid common pitfalls, accelerate implementation, and apply proven best practices based on real world experience. The goal is not just to build a platform that works today, but to create a data foundation that remains reliable, scalable, and easy to manage for years to come.
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.
Whether something’s still unclear or you’re ready to take the next step, Barry and Eric are happy to talk it through. Email us, call us, or book a meeting at a time that works for you.