Best IT Management Software for Looker - Page 2

Find and compare the best IT Management software for Looker in 2026

Use the comparison tool below to compare the top IT Management software for Looker on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

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    EZConvertBI Reviews

    EZConvertBI

    Wavicle Data Solutions

    EZConvertBI is an intelligent solution for business intelligence migration that leverages AI to streamline the intricate task of moving dashboards, reports, datasets, and analytics from outdated BI platforms, including Tableau, Qlik, and Power BI, to contemporary, cloud-based environments like Amazon QuickSight, Looker, and Power BI. By utilizing this tool, organizations can achieve migration of BI assets with execution speeds increased by as much as 90% and substantial cost savings, all while ensuring the preservation of visual aesthetics, business logic, SQL queries, extracts, and calculations during the entire process. The solution features an Analyzer component that interfaces with existing BI systems or uploaded workbooks to evaluate complexity, pinpoint duplicate or obsolete dashboards, and produce comprehensive diagnostic reports detailing migration scope, projected costs, and potential impacts. Moreover, its automated conversion engine proficiently maps and transforms dashboards, datasets, and queries into the desired target environment, guaranteeing the maintenance of functionality and the accurate replication of both visuals and underlying logic. This innovative approach not only simplifies the migration process but also empowers businesses to harness the full potential of their data in a modern analytics landscape.
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    Denodo Reviews

    Denodo

    Denodo Technologies

    The fundamental technology that powers contemporary solutions for data integration and management is designed to swiftly link various structured and unstructured data sources. It allows for the comprehensive cataloging of your entire data environment, ensuring that data remains within its original sources and is retrieved as needed, eliminating the requirement for duplicate copies. Users can construct data models tailored to their needs, even when drawing from multiple data sources, while also concealing the intricacies of back-end systems from end users. The virtual model can be securely accessed and utilized through standard SQL alongside other formats such as REST, SOAP, and OData, promoting easy access to diverse data types. It features complete data integration and modeling capabilities, along with an Active Data Catalog that enables self-service for data and metadata exploration and preparation. Furthermore, it incorporates robust data security and governance measures, ensures rapid and intelligent execution of data queries, and provides real-time data delivery in various formats. The system also supports the establishment of data marketplaces and effectively decouples business applications from data systems, paving the way for more informed, data-driven decision-making strategies. This innovative approach enhances the overall agility and responsiveness of organizations in managing their data assets.
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    Dremio Reviews
    Dremio provides lightning-fast queries as well as a self-service semantic layer directly to your data lake storage. No data moving to proprietary data warehouses, and no cubes, aggregation tables, or extracts. Data architects have flexibility and control, while data consumers have self-service. Apache Arrow and Dremio technologies such as Data Reflections, Columnar Cloud Cache(C3), and Predictive Pipelining combine to make it easy to query your data lake storage. An abstraction layer allows IT to apply security and business meaning while allowing analysts and data scientists access data to explore it and create new virtual datasets. Dremio's semantic layers is an integrated searchable catalog that indexes all your metadata so business users can make sense of your data. The semantic layer is made up of virtual datasets and spaces, which are all searchable and indexed.
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