Abstract: Storing and/or accessing data in a transactional database, with use of the following technique: (i) selecting a set of base tables in a transactional database; and (ii) creating a factless materialized query table, having maximum sparsity, for the set of base tables. The set of base tables includes at least two base tables. The set of base tables includes a set of keys including at least two distinct primary keys. The factless materialized query table includes one record associated with each record in the set of base tables. Each record in the materialized query table includes a value for every primary key in the set of base tables.

Abstract: A storage system graphical user interface (GUI) renders indication of a plurality of selected storage systems. Selection is received of selected storage systems from the rendered indication of selected storage systems and a determination is made of performance metrics common to the selected storage systems. A performance metric GUI enabling selection of the determined performance metrics common to the selected storage systems is generated. In response to user selection of at least one selected performance metric of the determined performance metrics in the performance metric GUI, determination is made of performance metric values for the at least one of the selected performance metrics for the selected storage systems. A computer renderable visualization providing a visual comparison for each of the at least one selected performance metric of the determined performance metric values is generated for the selected storage systems.

Abstract: Storing and/or accessing data in a transactional database, with use of the following technique: (i) selecting a set of base tables in a transactional database; and (ii) creating a factless materialized query table, having maximum sparsity, for the set of base tables. The set of base tables includes at least two base tables. The set of base tables includes a set of keys including at least two distinct primary keys. The factless materialized query table includes one record associated with each record in the set of base tables. Each record in the materialized query table includes a value for every primary key in the set of base tables.

Abstract: Alert conditions datasets are created from historic data taken from actual incidents for which the alert condition datasets are to indicate during future operations. A networked computers system including various devices is monitored for alert conditions associated with one, or more, of the devices. The severity of an alert is based on the number of alert conditions met for a given alert conditions dataset.

Abstract: Storing and/or accessing data in a transactional database, with use of the following technique: (i) selecting a set of base tables in a transactional database; and (ii) creating a factless materialized query table, having maximum sparsity, for the set of base tables. The set of base tables includes at least two base tables. The set of base tables includes a set of keys including at least two distinct primary keys. The factless materialized query table includes one record associated with each record in the set of base tables. Each record in the materialized query table includes a value for every primary key in the set of base tables.

Abstract: Storing and/or accessing data in a transactional database, with use of the following technique: (i) selecting a set of base tables in a transactional database; and (ii) creating a factless materialized query table, having maximum sparsity, for the set of base tables. The set of base tables includes at least two base tables. The set of base tables includes a set of keys including at least two distinct primary keys. The factless materialized query table includes one record associated with each record in the set of base tables. Each record in the materialized query table includes a value for every primary key in the set of base tables.

Abstract: Storing and/or accessing data in a transactional database, with use of the following technique: (i) selecting a set of base tables in a transactional database; and (ii) creating a factless materialized query table, having maximum sparsity, for the set of base tables. The set of base tables includes at least two base tables. The set of base tables includes a set of keys including at least two distinct primary keys. The factless materialized query table includes one record associated with each record in the set of base tables. Each record in the materialized query table includes a value for every primary key in the set of base tables.

Abstract: Storing and/or accessing data in a transactional database, with use of the following technique: (i) selecting a set of base tables in a transactional database; and (ii) creating a factless materialized query table, having maximum sparsity, for the set of base tables. The set of base tables includes at least two base tables. The set of base tables includes a set of keys including at least two distinct primary keys. The factless materialized query table includes one record associated with each record in the set of base tables. Each record in the materialized query table includes a value for every primary key in the set of base tables.

Abstract: Alert conditions datasets are created from historic data taken from actual incidents for which the alert condition datasets are to indicate during future operations. A networked computers system including various devices is monitored for alert conditions associated with one, or more, of the devices. The severity of an alert is based on the number of alert conditions met for a given alert conditions dataset.

Abstract: Alert conditions datasets are created from historic data taken from actual incidents for which the alert condition datasets are to indicate during future operations. A networked computers system including various devices is monitored for alert conditions associated with one, or more, of the devices. The severity of an alert is based on the number of alert conditions met for a given alert conditions dataset.

Abstract: Alert conditions datasets are created from historic data taken from actual incidents for which the alert condition datasets are to indicate during future operations. A networked computers system including various devices is monitored for alert conditions associated with one, or more, of the devices. The severity of an alert is based on the number of alert conditions met for a given alert conditions dataset.

Abstract: Alert conditions datasets are created from historic data taken from actual incidents for which the alert condition datasets are to indicate during future operations. A networked computers system including various devices is monitored for alert conditions associated with one, or more, of the devices. The severity of an alert is based on the number of alert conditions met for a given alert conditions dataset.

Abstract: Alert conditions datasets are created from historic data taken from actual incidents for which the alert condition datasets are to indicate during future operations. A networked computers system including various devices is monitored for alert conditions associated with one, or more, of the devices. The severity of an alert is based on the number of alert conditions met for a given alert conditions dataset.

Abstract: A storage system graphical user interface (GUI) renders indication of a plurality of selected storage systems. Selection is received of selected storage systems from the rendered indication of selected storage systems and a determination is made of performance metrics common to the selected storage systems. A performance metric GUI enabling selection of the determined performance metrics common to the selected storage systems is generated. In response to user selection of at least one selected performance metric of the determined performance metrics in the performance metric GUI, determination is made of performance metric values for the at least one of the selected performance metrics for the selected storage systems. A computer renderable visualization providing a visual comparison for each of the at least one selected performance metric of the determined performance metric values is generated for the selected storage systems.

Abstract: Storing and/or accessing data in a transactional database, with use of the following technique: (i) selecting a set of base tables in a transactional database; and (ii) creating a factless materialized query table, having maximum sparsity, for the set of base tables. The set of base tables includes at least two base tables. The set of base tables includes a set of keys including at least two distinct primary keys. The factless materialized query table includes one record associated with each record in the set of base tables. Each record in the materialized query table includes a value for every primary key in the set of base tables.

Abstract: Storing and/or accessing data in a transactional database, with use of the following technique: (i) selecting a set of base tables in a transactional database; and (ii) creating a factless materialized query table, having maximum sparsity, for the set of base tables. The set of base tables includes at least two base tables. The set of base tables includes a set of keys including at least two distinct primary keys. The factless materialized query table includes one record associated with each record in the set of base tables. Each record in the materialized query table includes a value for every primary key in the set of base tables.