Infor Data Lake Verified Customer Reviews (2026)

Effectively overseeing the complex operations of enterprise manufacturers and distributors is vital for achieving business expansion. Infor M3 shines as a cloud-based ERP system specifically designed for the manufacturing and distribution sectors, leveraging advanced technologies to improve user interaction and provide comprehensive analytics across diverse industries, regions, and locations. In addition to Infor M3, the CloudSuite™ industry solutions deliver exceptional capabilities for various fields, including chemicals, distribution, equipment, fashion, food and beverage, and industrial manufacturing. To stay ahead of the competition, it is imperative to be agile and adaptive. The newest functionalities offer improved data-driven insights and streamlined workflows, enabling you to make quick, informed decisions and take necessary actions without delay. By adopting these innovations, businesses can significantly boost their operational efficiency and responsiveness, ensuring they thrive in the fast-paced market environment. This commitment to modernization not only fosters growth but also cultivates a culture of continuous improvement.

AnalyticsCreator helps Microsoft data teams turn governed design into deployable data solutions without introducing a proprietary runtime layer. Teams use AnalyticsCreator to define warehouse structures, transformation logic, historisation rules, relationships and dependencies in a central model. From that model, the application can generate native implementation assets for technologies such as SQL Server, SSIS, Azure Data Factory, Microsoft Fabric and Power BI. The approach is designed for organisations that want to standardise how data warehouses and data products are engineered while keeping full control of the resulting code and project artefacts. Generated outputs can be integrated into existing Git, Azure DevOps and CI/CD workflows for versioning, review and controlled deployment across environments. AnalyticsCreator supports dimensional, 3NF and hybrid modelling as well as common engineering patterns including delta loading, Slowly Changing Dimensions, snapshots and historisation. Documentation, lineage and dependency information are maintained alongside the project design, making it easier to assess the impact of proposed changes and keep implementation aligned with the underlying model. The AnalyticsCreator Governed Control Model provides the foundation for this process by keeping business meaning, technical structures and implementation logic connected. Design Intelligence builds on that context by making governed project metadata, lineage, dependencies and design rules available to authorised AI tools and agents. Typical use cases include modernising SQL Server and SSIS estates, building Microsoft Fabric solutions, standardising Power BI delivery and creating repeatable data warehouse and data product engineering processes.

Lentiq provides a collaborative data lake service that empowers small teams to achieve remarkable outcomes. This platform enables users to quickly perform data science, machine learning, and data analysis on their preferred cloud infrastructure. With Lentiq, teams can easily ingest data in real-time, process and cleanse it, and share their insights with minimal effort. Additionally, it supports the creation, training, and internal sharing of models, fostering an environment where data teams can innovate and collaborate without constraints. Data lakes are adaptable environments for storage and processing, featuring capabilities like machine learning, ETL, and schema-on-read querying. For those exploring the field of data science, leveraging a data lake is crucial for success. In an era defined by the decline of large, centralized data lakes post-Hadoop, Lentiq introduces a novel concept of data pools—interconnected mini-data lakes spanning various clouds—that function together to create a secure, stable, and efficient platform for data science activities. This fresh approach significantly boosts the agility and productivity of data-driven initiatives, making it an essential tool for modern data teams. By embracing this innovative model, organizations can stay ahead in the ever-evolving landscape of data management.