MicroStrategy Delivers Critical Capabilities for the Intelligent Enterprise | MicroStrategy
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MicroStrategy Delivers Critical Capabilities for the Intelligent Enterprise

MicroStrategy recently produced a comprehensive video for Gartner that details how our platform delivers the full spectrum of analytics for our customers. It highlights the critical capabilities that Gartner focuses on for its analyses in its annual Magic Quadrant—capabilities that help make every enterprise a more Intelligent Enterprise.

As Gartner indicated in its 2018 Critical Capabilities for Analytics and Business Intelligence Platforms, MicroStrategy has among the highest product ratings of any vendor in the 2018 research note, and it earned the highest score of any vendor in this study for scalability.

The video below shows how MicroStrategy delivers for our customers. Sections outlined in the video include:

  • BI Platform Administration, Security, and Architecture: Enable platform security, user administration, auditing platform access and usage, and ensure high availability and disaster recovery
  • Data Source Connectivity and Ingestion: Connect to structured and unstructured data contained within various types of storage platforms (relational and nonrelational), both on-premises and in the cloud
  • Cloud BI: Platform-as-a-service and analytics-application-as-a-service capabilities for building, deploying, and managing analytics and analytics applications in the cloud, based on data both in the cloud and on-premises
  • Self-Contained Data Storage and Loading: Access, integrate, transform, and load data into a self-contained performance engine that can index data, manage data loads, and refresh scheduling
  • Self-Service Data Preparation: "Drag and drop" user-driven data combinations of different sources and create analytics models like user-defined measures, sets, groups, and hierarchies. Advanced capabilities include machine-learning-enabled semantic autodiscovery, intelligent joins, intelligent profiling, hierarchy generation, data lineage, and data blending on varied data sources, including multi-structured data
  • Metadata Management: Leverage a common semantic model and metadata, providing a robust and centralized way for administrators to search, capture, store, reuse, and publish metadata objects such as dimensions, hierarchies, measures, and KPIs. They also report layout objects, parameters, and more. Administrators should be able to promote a business-user-defined data mashup and metadata to the SOR metadata
  • Scalability and Model Complexity: The degree to which the in-memory engine or in-database architecture handles high volumes of data, complex data models, performance optimization and large user deployments
  • Advanced Analytics for Citizen Data Scientists: Easily access advanced analytics capabilities that are self-contained within the platform through menu-driven options or the import and integration of externally developed models
  • Augmented Data Discovery: Automatically find, visualize, and narrate important findings such as correlations, exceptions, clusters, links, and predictions in data relevant to users without building models or writing algorithms. Users explore data via visualizations, natural-language-generated narration, search, and natural-language query (NLQ) technologies
  • Interactive Visual Exploration: Explore data via an array of visualization options that go beyond those of basic pie, bar, and line charts to include heat and tree maps, geographic maps, scatter plots, and other special-purpose visuals. These tools enable users to analyze and manipulate data by interacting directly with a visual representation of it to display as percentages, bins, and groups
  • Analytics Dashboards: Create highly interactive dashboards and content with visual exploration and embedded advanced and geospatial analytics to be consumed by others
  • Mobile Exploration and Authoring: Develop and deliver content to mobile devices in a publishing and/or interactive mode, and take advantage of mobile devices' native capabilities, such as touchscreen, camera, and location awareness
  • Embed Analytic Content: SDKs, APIs, and open standards for creating and modifying analytics content, visualizations, and applications, and embedding them into a business process and/or an application or portal. These capabilities can reside outside the application, reusing the analytics infrastructure, but must be easily and seamlessly accessible from inside the application without forcing users to switch between systems. The capabilities for integrating analytics and BI with the application architecture will enable users to choose where in the business process the analytics should be embedded
  • Publish, Share, and Collaborate: Capabilities that allow users to publish, deploy, and operationalize analytics content through various output types and distribution methods, with support for content search, scheduling, and alerts. These capabilities enable users to share, discuss, and track information, analysis, analytic content, and decisions via discussion threads, chat, and annotations

Read a complimentary copy of Gartner’s 2018 Critical Capabilities Report for Analytics and Business Intelligence, to see how the MicroStrategy platform received the highest overall score in multiple use cases.

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