Apptio, Inc.

Paul Damien McLachlan

Tavis Dean Elliott

Supin Ko

Eric Yves Theriault

Jay Randolf Gindin

Justin Alexander Friedl

Brian John Bero

Svilen Mihaylov

William Byron Moeller

Embodiments are directed towards for managing data models, including resource allocation forecasting. A main data model may be provided. A delta ratio value based on a difference between modified cloned resource values and their corresponding original resource values in the main data model may be provided. Line items from the cloned data model associated with the one or more modified cloned resource values may be provided. Each of the cloned line items may be modified based on the delta ratio value. The modified cloned line items may be stored in the cloned data model. Reports including report information based on the cloned data model may be provided. The report information may indicate changes that were made to one or more other cloned resource values based on the modifications to the one or more cloned resource values.

Resource allocation forecasting

Various embodiments are directed towards allocating costs for a plurality of cost objects. In at least one of the various embodiments, a source object and a target object in a data model may be determined such that an allocation rule is used to define one or more cost allocations where the costs flows from the source object to the target object. Allocation rules that are part of a recursive allocation rule may be executed on the source object and the target object until a terminal condition is met. The cost value that corresponds to the source object may be modified based on the allocation rule and the generated cost value. This process may continue until a terminal condition is met. After the terminal condition has been met final costs value corresponding to the target object and the source object may be generated and displayed.

Recursive processing of object allocation rules

Embodiments are directed towards intermediate resource allocation tracking in data models. A data model that includes data objects traversed on a path through the data model that follows allocation rules that are included in the data model. If an aspect object is encountered during the traversal, resources from line items of a source data object are associated with line items of the aspect object based on the traversal path. The resources associated with the line items of the aspect object are also available for allocation to other data objects. If a data object, rather than an aspect object, may be encountered during the traversal, resources from line items of a source data object may be allocated to line items of the data object based on another of the allocation rules, the resources allocated to the line items of the data object are unavailable for further allocation.

Intermediate resource allocation tracking in data models

Embodiments are directed towards generating reports for visualizing data models. A RACI engine may obtain RACI information for a user. A report engine may provide metadata associated with a report for visualizing the data model. The report engine may be arranged to provide anchor points in the data model based on the metadata, the RACI information. The report engine may be arranged to provide a report template based on the anchor points, the RACI information, and the metadata such that the report template includes references to data objects selected automatically based on the metadata and the anchor points. The report engine may display a report based on the report template that provides visualizations based on values associated with the data objects.

Report generation based on user responsibility

Embodiments are directed towards normalizing ingested data sets based on fuzzy comparisons to known data sets. Raw data sets that each include raw records may be provided to an ingestion engine. Ingestion rules and known data sets may be provided based on the raw records. The ingestion engine may be employed to iteratively execute the ingestion rules. A comparison of the raw records to the known data sets may be performed. Contents of the raw records may be transformed into model record values and stored in model records. A score value that indicates a confidence level that the model records are correct may be provided. An association of the one or more ingestion rules used to transform the raw record contents into the model record values for each of the one or more model records may be added to a data model.

Normalizing ingested data sets based on fuzzy comparisons to known data sets

Various embodiments are directed towards a platform for rapid development of applications. A data processing application may be generated by applying templates, work streams, change entries, and user modifications to generate data processing applications. In at least one of the various embodiments, the applications may be generated based project initial instructions and by receiving and processing example data in combination with templates, change entries, and work streams. Further, in at least one of the various embodiments, modifications made to the generated applications may be preserved as change entries associated with a work stream. In at least one of the various embodiments, separate applications may be generated based on the work streams and/or change streams of other applications. In at least one of the various embodiments, if a generated application may be modified a new revision number may be associated with the modified version of the application.

Platform for rapid development of applications

Embodiments are directed towards managing data storage and queries within a database system using global dictionaries with universal primitives (UNIPs) to represent non-numeric data within a mixed numeric/non-numeric environment. Common data types are managed within a same global dictionary through dictionaries that are globally used within the database system. At least non-numeric data within mixed data fields may be stored using a UNIP to identify the stored non-numeric data. The UNIP may take advantage of the IEEE-754 standard for floating point data representation by setting a first field within the UNIP to 0x7ff (HEX) to indicate that the data is non-numeric (NaN) and using remaining bits to store typed data, such as a date or unique indirect reference (e.g. a sequence number or file offset to larger piece of data). The UNIP may then replace the data within the database and be used during operations performed on the data.

Global dictionaries using universal primitives

A computation system includes a receiver, a schema generator, and a table generator. The receiver receives operational related data relating to an IT environment of an organization from remote systems. The schema generator organizes the operational related data into at least one class of IT metric-oriented data based on at least one intrinsic characteristic of the operational related data to generate a schema. The operational related data includes data tables corresponding to IT assets of the organization. The table generator processes an input table based on the schema to generate an output table. The input table includes a starting table having one or more columns. The output table identifies a subset of interrelated data included in the starting table.

Operational-related data computation engine

Embodiments are directed towards budgeting and forecasting of information technology and services. In at least one of the various embodiments, financial allocation models may include multiple cost objects and one or more allocation rules. In at least one of the various embodiments, allocation rules may determine how costs associated with cost objects may be allocated to other cost objects. In at least one of the various embodiments, costs corresponding to one or more selected cost objects may be traced within a financial allocation model. Also, costs associated with multiple cost line items from different cost objects may simultaneously traced for efficient cross-referencing of disparate cost line items. Further, in at least one of the various embodiments, a display of the cost traces may be rendered and displayed to provide a visualization of the traced costs.

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Newcastle, WA, United States of America

Paul Damien McLachlan