Microstrategy, Inc.

Benjamin Z Li

Jeffrey A Bedell

William Hurwood

Abhimanyu Warikoo

Jun Yuan

Sadanand Sahasrabudhe

Fabrice Martin

Ramkumar Ramachandran

Scott Cappiello

L Douglas Everhart

Michael Jerry Saylor

Luis V Orozco

Stephen Scott Trundle

Rixin Liao

Xinyi Wang

Alex Ye

Steven S Trundle

Ali Alavi

Xun Feng

Glenn J Boysko

Ramprasad Polana

Eduardo Carranza

David B Sherwood

Gang Liang

Wenfeng Li

Daniel Todd Kerzner

Peng Xiao

Yuliyan Kiryakov

Gunther L Brenes

Peter Jerome DiDomenico, Iii

Yi Du

Arturo Oliver

Michael Codini

Ashutosh K Jhaveri

Yuan Ding

Ningning Liu

Kyle N Yost

Terry Berman

Javier Aldrete

Yinong Chen

Hu Yu

Joel Lebrun

Gaurav Rewari

Christopher Von Simson

Arturo Gay

Quoc Cuong Bui

Xiaonan Han

Ilia Baskine

Vladislav Davidovich Lazebnikov

Hanijanto Soewandi

Sanjeev K Bansal

Dyung V Le

Patrick Vinton

Rodolfo Avalos

Barry R Lovalvo

Alejandro Freixas

Raul Gonzalez

Database query analysis technology, in which an input query is received that relates to multiple attribute classes of data records. An index that is descriptive of the data records in data storage is accessed and relative positions in the accessed index for the multiple attribute classes are identified. The accessed index is processed based on more than one of the multiple attribute classes and the identified relative positions, and the processed index is used to identify groups of data records that are included in the data records in the data storage and that share common values for the multiple attribute classes in the input query. Metrics corresponding to the data records included in each of the identified groups of data records are accessed, computations are performed on the accessed metrics, and a report is generated that reflects results of the computations.

Index mechanism for report generation

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

Database report generation technology for handling a single logical query that requires data that is physically located in two different sources. The system uses intelligent push-down joins, which move data from one source to the other and join data within that source. The system dynamically determines which direction to move data depending on how the data is used in a query.

Data source joins

In one implementation, data associated with user identities within an electronic social networking platform is extracted from the electronic social networking platform. A subset of these user identities may have endorsed a particular entity within the electronic social networking platform, and a segment of user identities within this subset may be identified. Content then may be delivered to at least some of the user identities within the segment.

Targeted content delivery

Data associated with user identities within an electronic social networking platform is extracted from the electronic social networking platform. A request is received to filter the user identities based on a specified value for a characteristic. Based on data associated with the user identities that was extracted from the electronic social networking platform, a subset of the user identities is identified who have the specified value for the characteristic. An indication of content to be delivered to the identified subset of user identities is received. As a consequence, the content is delivered to at least some of the user identities within the identified subset of user identities.

A technique for exporting results from a reporting system report in a format type including a datamart, PDF file, flat file, Excel&#x2122; file, HTML file, and XML file or in another relational database management system (RDBMS) format. In one embodiment, the technique is realized through a method and a system for automatically exporting results from a business intelligence, OLAP, or other reporting system. One embodiment of the present invention involves a method of enabling a user to designate a report desired for execution as an export-report. When the report is processed, the report is exported into a datamart or other format and made available for access by the user through one or more different types of user devices. The user may then further manipulate or export the results from the datamart to a file type as desired.

System and method for exporting report results from a reporting system

A business intelligence system comprises a business intelligence interface system that enables users to interface with a business intelligence system and an electronic learning system that delivers electronic learning related to the business intelligence system. The business intelligence interface system enables one or more portions, such as folders of reports, individual reports, metadata or other business intelligence objects, or a report definition, of the business intelligence system for use by a user based on information related to whether the user has engaged in electronic learning associated with the one or more portions. A user may self-provision access by earning a privilege based on reviewing a lesson, passing a test, and/or other activities relative to the business intelligence object. Upon meeting electronic learning criteria, the electronic learning system updates privileges to enable access to the business intelligence object or class of objects.

Integration of e-learning with business intelligence system

A system and method for indexing non-uniquely indexed entries in a report generated with a business intelligence system, such as, for example, an on-line analytical processing (OLAP) system. A dummy index is added to each index element returned in the report. Non-unique index elements receive different dummy indices to distinguish otherwise identical row elements. The dummy index is added to a base template and optionally also to a view template of a report generator of the OLAP system.

Systems and methods for enhanced SQL indices for duplicate row entries

A selection engine for a cooperative processing network, in which databases compute portions of searches and analyses which they may most efficiently compute. A data mining network may contain large scale databases, analytic engines which communicate with the databases, and other resources, each capable of performing or executing certain functions, such as statistical functions. When a user desires to run a specified report against the databases, those functions that can be computed locally in the database are trapped and computed therein, whereas other functions, such as advanced statistical functions, may be distributed to remote analytic engines or other resources in the network. A management module may coordinate the transmission and assembly of the data, including to order dependencies. The management module may contain a selection engine to allocate computations to databases or other resources as a default, to test for load balancing before choosing a compute site, or apply other criteria.

System and method for function selection in analytic processing

Data organization and indexing, in which data that includes information for multiple attribute classes is accessed and redundancy characteristics of the accessed data within each of at least two of the multiple attribute classes are identified. Based on the identified redundancy characteristics, a relative order among the multiple attribute classes of the accessed data is determined and the accessed data is organized based on the determined relative order. The organized data is compressed using run length encoding and an index that is descriptive of the compressed data is generated. The encoded data and the generated index are stored to enable subsequent searching of the encoded data using the generated index.

Data organization and indexing related technology

Growing community of inventors

Great Falls, VA, United States of America

Benjamin Z Li