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Navigating the Evolution of D365 Finance & Supply Chain Management Data Export Solutions

Organizations increasingly rely on data-driven decision making, which makes the choice of a data export solution for Dynamics 365 Finance and Supply Chain Management (D365 F&SCM) crucial to business success. Microsoft’s recent announcement about the deprecation of Export to Data Lake by February 15th, 2025, marks a significant shift in their data strategy. This change presents organizations with an opportunity to reevaluate their data architecture and consider modern, more efficient solutions.

Understanding the Available Solutions

Export to Data Lake: The Legacy Approach and Its Technical Limitations

Export to Data Lake has served as the traditional solution for organizations needing to export data from D365 F&SCM, but its technical architecture presents several significant challenges that impact both performance and operational efficiency. At the core of these limitations is the solution’s reliance on CSV file format for data export.

The CSV format, while familiar and widely supported, creates substantial operational challenges. Organizations frequently encounter poor query performance when attempting to directly consume these files, leading to increased processing times and reduced analytical efficiency. Additionally, the format is prone to read/write contention issues, which can impact data accessibility and reliability.

To address these inherent limitations, organizations typically implement a complex data transformation layer. This involves using Azure Data Factory to periodically ingest the raw CSV data and convert it into a more suitable format within a SQL Azure Database or Azure data warehouse. While this approach helps mitigate the immediate performance issues, it introduces additional complexity and cost to the data pipeline.

The implementation process requires multiple tools and software licenses, creating a complex web of dependencies that teams must maintain. System configuration demands substantial effort, and organizations must invest considerable resources in building and validating data pipelines. The solution also requires ongoing governance, management, and monitoring, along with comprehensive user training programs.

From a cost perspective, organizations must consider both initial setup and operational expenses. The setup phase involves multiple software licenses, system configuration costs, and investments in pipeline development and validation. Operational costs include Azure storage and IO charges, Synapse Analytics fees for SQL serverless queries, Azure Data Factory processing costs, and expenses related to maintaining staging environments. Additionally, organizations must account for Power BI capacity and storage costs for their reporting needs.

The maintenance of these intermediate data stores creates a cascade of operational challenges. Organizations must dedicate resources to managing the transformation processes, monitoring data synchronization, and ensuring data consistency across multiple storage locations. This additional layer not only increases operational costs but also introduces potential points of failure in the data pipeline.

Fabric Link represents Microsoft’s vision for a streamlined, modern data export solution. This approach significantly simplifies the data export process by integrating directly with the Power Platform ecosystem. Organizations benefit from a straightforward configuration experience and a consumption-based pricing model that aligns costs with actual usage.

A key advantage of Fabric Link is the elimination of ETL pipelines for Dataverse data, reducing technical complexity and maintenance requirements. The solution also offers impressive data compression capabilities, which can significantly reduce storage costs and improve query performance.

The cost structure of Fabric Link reflects its modern architecture. Initial setup costs are primarily centered around Fabric capacity purchases, with minimal configuration complexity and pipeline setup requirements. Operational costs include Dataverse storage charges, with potential overages priced at $40/GB. However, the solution’s compression capabilities (typically reducing data size by 5-8 times) help mitigate these costs. The pay-as-you-go consumption model provides better cost predictability and control.

Synapse Link for Dataverse offers a middle ground between traditional data lake approaches and modern cloud solutions. This option provides organizations with flexible data refresh capabilities while maintaining simplified configuration within the Power Platform ecosystem.

The solution eliminates the need for ETL pipelines when exporting Dataverse data but requires a Spark pool for converting data to Parquet format. This requirement introduces variable costs based on refresh frequency and data volume. For small to medium data changes, organizations can expect monthly costs ranging from $600 to $2,000 for hourly refreshes, or $1,200 to $4,100 for 15-minute refreshes. Larger data volumes increase these costs to $1,200-$2,500 for hourly refreshes or $2,500-$8,300 for 15-minute refreshes.

The Parquet format conversion provides significant benefits for analytical workloads, potentially reducing the need for additional data aggregation. Like Fabric Link, Synapse Link for Dataverse benefits from data compression, typically reducing data size by one-third to one-sixth of the original, leading to lower query and reporting costs.

Technical Evolution and Business Impact

The transition from Export to Data Lake to modern solutions represents more than just a change in technology—it marks a fundamental shift in how organizations can approach their data architecture. The elimination of intermediate data transformation requirements and the move to optimized data formats enables organizations to:

  1. Streamline their data pipelines by removing unnecessary transformation steps
  2. Reduce operational complexity through simplified architecture
  3. Improve query performance with formats designed for analytical workloads
  4. Lower total cost of ownership by eliminating redundant data stores

Both Fabric Link and Synapse Link for Dataverse represent significant advancements in addressing the technical limitations of Export to Data Lake. These modern solutions eliminate the need for intermediate data transformation layers through their native support for optimized data formats.

Synapse Link for Dataverse, in particular, exports data directly in Delta or Parquet format, providing several immediate benefits. These formats are designed for analytical workloads, offering superior query performance without the need for additional transformation steps. The elimination of read/write contention issues and the reduced need for maintaining separate data stores for performance optimization translate into both operational efficiency and cost savings.

Making the Right Choice

The selection of a data export solution should be guided by several key factors. Organizations must evaluate their data refresh requirements, considering whether real-time data access is necessary or if batch processing suffices. Technical capabilities within the organization play a crucial role, as each solution demands different levels of expertise and ongoing maintenance.

For organizations currently using Export to Data Lake, the impending deprecation requires immediate action. Those with extensive Azure service investments and strong data engineering capabilities might find Synapse Link for Dataverse a natural evolution, particularly if they require flexible refresh rates and optimized analytics performance.

Organizations prioritizing simplicity and predictable costs might gravitate toward Fabric Link. This solution particularly suits teams seeking to minimize technical overhead while maintaining robust data export capabilities. The consumption-based pricing model and impressive compression capabilities make it especially attractive for organizations with moderate data volumes.

Synapse Link for Dataverse presents a compelling option for organizations requiring granular control over refresh rates and those working with varying data volumes. The solution’s Parquet format optimization makes it particularly suitable for analytics-heavy workloads, though organizations must carefully consider the cost implications of their chosen refresh rates.

Planning for the Future

As organizations plan their migration strategy, several key considerations emerge. The February 2025 deprecation deadline for Export to Data Lake creates a clear timeline for action. Organizations should begin by thoroughly assessing their current data volumes, documenting existing integration points, and evaluating internal technical capabilities.

The migration process presents an opportunity to modernize data architecture while optimizing costs and improving efficiency. Organizations should consider their growth trajectory, future analytical needs, and desired level of technical complexity when selecting their new solution.

Whether choosing Fabric Link or Synapse Link for Dataverse, organizations must prepare for a shift in how they manage and access their data. This includes planning for potential training needs, updating data governance policies, and adjusting operational processes to align with the new solution’s capabilities.

The evolution of D365 F&SCM data export solutions reflects the broader transformation in enterprise data management. By carefully evaluating their needs and choosing the appropriate solution, organizations can position themselves for improved data accessibility, reduced maintenance overhead, and enhanced analytical capabilities in the years ahead.

Ready to Navigate the Future of D365 F&SCM Data Export Solutions?

At Sikich, we specialize in guiding organizations through complex transitions like the deprecation of Export to Data Lake. As a top Microsoft partner and award-winning consulting firm, we bring unparalleled expertise to help you modernize your data architecture, streamline processes, and achieve cost-efficient analytics.

Whether you’re exploring Fabric Link, Synapse Link for Dataverse, or another data solution, our team is here to help you evaluate your options, craft a migration strategy, and implement the solution that best fits your business needs.

Don’t wait until the February 2025 deadline—contact Sikich today to prepare for the future and unlock the full potential of your data.

This publication contains general information only and Sikich is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or any other professional advice or services. This publication is not a substitute for such professional advice or services, nor should you use it as a basis for any decision, action or omission that may affect you or your business. Before making any decision, taking any action or omitting an action that may affect you or your business, you should consult a qualified professional advisor. In addition, this publication may contain certain content generated by an artificial intelligence (AI) language model. You acknowledge that Sikich shall not be responsible for any loss sustained by you or any person who relies on this publication.

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