June 2025 Summaries

AI's effectiveness in transforming business operations relies heavily on the quality and integration of data, which often resides across disparate sources such as legacy databases, APIs, and various file types. Fivetran's Connector SDK addresses this challenge by providing a Python-based framework for building custom data connectors, enabling seamless data ingestion into platforms like Snowflake, Databricks, or BigQuery. This tool simplifies complex integration tasks, allowing teams to focus on AI model development by automating orchestration, monitoring, and scaling within the Fivetran managed service. The SDK facilitates the creation of production-grade data pipelines without the overhead of managing traditional infrastructure, thus supporting agile AI development and enhancing collaboration between data engineers and scientists. By ensuring comprehensive data integration, businesses can improve the accuracy and performance of AI systems, ultimately turning data engineering into a competitive advantage.

AI holds significant promise for enhancing business outcomes, but its successful implementation hinges on aligning AI with decision-making, data readiness, and human expertise. Many organizations struggle with fragmented systems and incomplete data, leading to decisions based on flawed assumptions rather than reliable insights. Tim Veil from Two Bear Capital emphasizes the importance of centralizing data into everyday workflows to improve decision-making. Off-the-shelf tools often lack the flexibility to integrate diverse systems, necessitating custom solutions like the Fivetran Connector SDK to consolidate data effectively. Successful AI adoption involves a human-centered approach, treating AI as a tool to augment human capabilities rather than replace them, ensuring ethical and accurate outcomes. Establishing a strong data foundation with integrated systems positions companies to leverage AI effectively and transition from assumption-driven to data-driven decision-making, enhancing both speed and accuracy.

SAP's complex ecosystem often presents challenges for enterprises seeking to centralize data, particularly when integrating SAP with non-SAP sources for comprehensive analytics. This issue is compounded by restrictive licensing and limited compatibility, which can hinder data access and create vendor lock-in. However, the EU Data Act, effective from September 2025, aims to mitigate these issues by granting businesses new rights to access and switch their data providers without needing approval. In response to these challenges, many global companies, such as LVMH, Cemex, Pitney Bowes, and Adragos Pharma, have turned to Fivetran for seamless SAP data integration. Fivetran's platform allows these companies to automate data replication and integration from SAP and other sources, facilitating real-time insights and decision-making without the burdens of custom pipelines or engineering resources. For instance, LVMH can now access real-time SAP insights across its brands, Cemex has reduced SAP processing times significantly, Pitney Bowes has improved logistics and customer satisfaction, and Adragos Pharma has streamlined data management to support its acquisition strategy. Through Fivetran, enterprises can modernize their data strategies, enabling advanced analytics and AI initiatives while maintaining security and compliance.

C-suite technology leaders are increasingly responsible for driving enterprise-wide innovation by crafting data strategies that enable AI and smarter business decisions. A survey by Fivetran and Forbes Insights of 500 U.S.-based tech leaders reveals that managing data complexity, integration, and security are primary challenges as organizations deal with over 50 data sources. To overcome these hurdles, leaders are investing in modern data integration platforms to ensure operational efficiency and AI scalability, with nearly half planning to spend $500,000 or more on integration infrastructure next year. High-quality, proprietary data is crucial for training large language models, but obstacles like fragmented systems and skills gaps persist. As AI initiatives grow, governance and security become essential, with technology leaders prioritizing data privacy and compliance over innovation. The evolving role of tech leaders involves balancing innovation with accountability and trust as they shape enterprise-wide data strategies to support AI and infrastructure convergence.

SAP customers face challenges with data access and interoperability due to SAP's evolving business strategy, licensing models, and ecosystem architecture that can limit business agility by restricting data movement. Despite these constraints, customers have options for managing their data without compromising compliance or performance, as ERP data is valuable when combined with other data sources. SAP ECC, a longstanding ERP system, is reaching end-of-life, pushing customers towards SAP S/4HANA and SAP RISE, which present their own challenges, such as expensive licensing, migration costs, and reduced control over cloud infrastructure. Fivetran offers a solution by simplifying data replication from SAP systems and over 700 other sources to modern data warehouses and lakes, enhancing analytics, AI, and machine learning initiatives. Using standard SAP NetWeaver methods, Fivetran ensures secure and efficient data integration without relying on SAP middleware, enabling businesses to unlock valuable insights and maintain control over their data while avoiding costly workarounds. An IDC study highlights that Fivetran customers experience significant productivity gains and cost savings, allowing them to drive value from their ERP investments and innovate more rapidly.

For large enterprises across diverse industries like engineering, pharmaceuticals, and global manufacturing, accessing real-time data is crucial for operational efficiency and profitability, as poor data quality can lead to significant financial losses. Companies such as Autodesk, Envision Pharma, and Cemex have embraced Fivetran to centralize their data, enabling real-time analytics that empower teams to act swiftly and achieve measurable outcomes. Autodesk enhanced its design and manufacturing outcomes by automating data ingestion, allowing over 13,000 engineers to make quicker and more informed decisions. Envision Pharma accelerated its research and compliance processes by creating a unified data source, significantly reducing time-to-market for new therapies. Cemex transformed its supply chain operations with real-time visibility across its facilities, improving resource utilization and sustainability. These enterprises demonstrate how modernizing data infrastructure with Fivetran can lead to faster insights, improved collaboration, and smarter decision-making, giving them a competitive edge in their respective fields.

SAP's ERP systems are integral to the operations of over 430,000 enterprises globally, including the majority of the world's largest companies, by managing essential processes such as finance and inventory. Despite the potential value of SAP data for comprehensive organizational insights, SAP's ecosystem remains closed, limiting customers' ability to access and integrate their data with third-party platforms. This approach, characterized by proprietary data solutions and costly licensing, restricts customer choice and complicates data strategy implementation. Notably, SAP's Datasphere, intended as a central hub for data integration, lacks the cost-effectiveness, flexibility, and interoperability of modern platforms like Snowflake and Databricks. Recent SAP policies have further narrowed data extraction options, pushing customers towards SAP-certified solutions and cloud services like RISE with SAP, which often result in higher costs and less flexibility. As enterprises seek to modernize their data stacks, solutions like Fivetran offer an alternative by promoting data integration and reducing vendor lock-in, allowing organizations to optimize their data architecture beyond SAP's confines.

SAP ERP systems are integral to operations for many of the world's largest companies, managing essential processes such as finance and customer relationship management. However, SAP's approach to data management is increasingly restrictive, limiting customers' ability to extract and utilize data outside of SAP's ecosystem. SAP's Datasphere, a proprietary data warehouse, faces criticism for high costs, limited scalability, and restricted interoperability compared to modern platforms like Databricks and Snowflake. Despite these challenges, solutions like Fivetran enable businesses to extract SAP data efficiently, allowing integration with other data sources and enhancing analytics capabilities. Notable companies such as LVMH and Cemex have successfully used Fivetran to automate data integration, thereby gaining real-time insights without vendor lock-in. This series explores how SAP's ecosystem constraints can impede data access and what enterprises can do to overcome these barriers.

Fivetran's Connector SDK is a tool designed to help data teams access and analyze insights from various data sources without the need for DIY coding, infrastructure setup, or complex replication logic. The SDK enables users to build custom connectors for unique systems, fill gaps in prebuilt connectors, customize data movement, and quickly integrate internal APIs into their data stack. With over 180 customers replicating from 450+ different sources, the Connector SDK has proven its value in streamlining data integrations, reducing infrastructure costs, and accelerating time to insight.

Enterprises are adopting advanced tools to support real-time analytics, machine learning (ML), and artificial intelligence (AI) to turn data into actionable insights quickly. Platforms like Fivetran and Databricks are helping organizations automate data integration, centralize analytics, and power scalable, AI-driven decision-making. Companies such as Condé Nast, National Australia Bank, and Red Ventures are leading the way by streamlining operations, optimizing decisions, and unlocking new growth opportunities with Fivetran and Databricks. By using these platforms, they're delivering personalized experiences, enhancing customer engagement, and achieving operational excellence. Key results include seamless ingestion of data into a centralized analytics platform, elimination of manual scripts, faster generation of revenue-driving insights, and improved operational efficiency. These organizations are setting the pace for what's possible with AI and real-time data, transforming how they operate, serve customers, and scale.

The EU Data Act grants European Union (EU) customers the right to access their data or switch providers upon notice without requiring approval. This law aims to eliminate long-standing vendor lock-in challenges, empowering enterprises to regain control of their data and drive innovation without being constrained by legacy platforms. Key rights include the right to retrieve exportable data and digital assets during the contract term, the right to switch providers without being obstructed by contractual or technical barriers, and the right to functional equivalence at the new provider. The law also requires providers to make good faith efforts to enable secure, timely switching and data portability. Enterprises must review their contracts, procurement playbooks, and governance processes to prepare for the EU Data Act's implementation in September 2025. The law formalizes a principle that customers have long championed: your data — whether generated, uploaded, or operational — is yours to control.

Retailers face a challenge in integrating diverse data sources from supply chains, customer interactions, and operational systems, creating barriers to deriving insights, optimizing operations, and delivering seamless customer experiences. To navigate this complexity, retailers must prioritize flexible, scalable data integration strategies that allow them to harmonize disparate sources without disrupting existing workflows. This can be achieved by adopting modular, adaptable architectures that can evolve with new technologies, customer engagement channels, and business needs. Retailers should focus engineering efforts on creating unique, strategic value, prioritizing custom development for capabilities that are either unsolvable or create a distinct competitive advantage. By outsourcing non-differentiated technical tasks and layering industry-specific customizations on top of proven platforms, businesses can drive efficiency while still creating unique competitive advantages, ensuring they stay agile, scalable, and ahead of the curve.

The Fivetran Connector SDK is now generally available, enabling organizations to replicate data from any source system, application, API, database, or file with custom Python-based connectors. The SDK empowers teams to create production-ready connectors without managing infrastructure, allowing them to focus on delivering business value instead of maintaining brittle data pipelines. With the SDK, users can build custom connectors for internal tools and niche systems, custom APIs, schema extensions, and compliance customization, among other use cases. The Connector SDK offers granular control over data movement, enabling precise control over what data is extracted and delivered to destinations. It also allows for easy schema mapping and sync scheduling, meets enterprise security and governance requirements, and supports cloud-native execution with Python-based flexibility. The SDK can be used to build connectors in under an hour, making it a strategic advantage for data leaders and practitioners who want to deliver analytics faster and more efficiently.