Microstrategy, Inc.

Yuliyan Kiryakov

Scott Cappiello

Jun Yuan

Xun Feng

Benjamin Z Li

Rixin Liao

Ananya Ojha

Yinong Chen

Shiliang Wang

Bingbing Ji

Disclosed are methods, systems, and computer-readable medium for providing report results. Viscous attributes and non-viscous may be identified. A smart cube may be received and may include viscous values for the viscous attributes. The smart cube may be stored at a local cache. A report associated with an organization may be initiated. A runtime generation of the report may be generated based on initiating the report. The report may call a viscous attribute from the viscous attributes and call a non-viscous attribute from the non-viscous attributes. The runtime generation may be modified to remove the viscous attribute from the runtime generation. A viscous value for the viscous attribute may be retrieved from the smart cube at the local cache. The modified runtime generation may be executed to retrieve a non-viscous value for the non-viscous attribute from a remote database and a report result may be provided.

Lookup and relationship caches for dynamic fetching

Disclosed are methods, systems, and computer-readable medium for providing query results. The query results may be provided more accurately and faster than via distributed tables. Disclosed techniques include receiving a plurality of tables comprising attributes and attribute data, the attribute data comprising attribute forms and attribute related information, identifying attributes and corresponding attribute data from each of the plurality of tables, applying a categorization machine learning model to categorize each attribute data as an attribute form or an attribute related information, generating the lookup table based on the attributes and the corresponding attribute forms, generating the relationship table based on the attributes and the corresponding attribute related information, receiving a query for attribute data, and generating a query response based on at least one of the lookup table or the relationship table.

Systems and methods for providing faster data access using lookup and relationship tables

In one implementation, a query is received that is related to data stored in a database that is implemented in computer memory. Based on the received query, attributes of data stored in the database that are relevant to generating a response to the received query are identified. Information that is indicative of attributes for which values are recorded in different tables included in the database is accessed. Based on having accessed this information, tables included in the database that record values for the attributes identified as being relevant to generating a response to the received query are identified. These tables then are joined to create, within computer memory, a new table that reflects relationships between values of attributes identified as being relevant to generating a response to the received query.

Joining database tables

Dynamic sourcing, in which a data request that is associated with a query is received and a parameter of data needed for satisfaction of the query is identified. Parameter information defining data available in at least one cube stored in a cache is accessed and the parameter is compared with the parameter information. Based on comparison results, it is determined whether one or more cubes in the cache include sufficient data to satisfy the query. In response to a determination that one or more cubes include sufficient data to satisfy the query, a response to the data request is generated by executing the query against the one or more cubes. In response to a determination that the cubes do not include sufficient data to satisfy the query, a response to the data request is generated by executing at least a portion of the query against a database system.

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Arlington, VA, United States of America

Yuliyan Kiryakov