Dynamic generation of guided pages
Configuring and automatically populating a columnar, multi-domain business intelligence data structure can support the continuation of a business workflow. Configuring includes ingesting data from a plurality of disparate sources, formatting it according to a standardized schema, and aligning it with workflow-derived data dimensions. This process includes parsing the source data, harmonizing data formats, normalizing strings based on locale-specific language or industry-specific terminology, identifying relevant dimensions, mapping each dimension to a respective column, and populating the data structure accordingly. The resulting alignment ensures that data is organized by dimension in a highly efficient and automated manner to facilitate multi-domain business intelligence operations.
1 . A computer implemented method of configuring and automatically populating a columnar-based multi-domain business intelligence data structure for continuing a workflow of a business with data formatted according to a plurality of disparate data sources so that columns of the columnar-based multi-domain business intelligence data structure automatically align with data dimensions automatically derived from steps in the workflow for a business, the method comprising executing a highly efficient computing engine to improve a hardware processor for:
parsing source data from each of the data sources based on a set of parsing rules associated with each data source;
harmonizing formats of the disparate data sources;
normalizing data strings of the data sources per language of a locale or industry specific jargon associated with the workflow;
determining, by the highly efficient computing engine, one or more workflow-derived dimensions for each of the data sources, the determining including applying a machine-executable semantic knowledge plan comprising computer-readable rules that derive the workflow-derived dimensions from workflow steps of the business, the workflow-derived dimensions being generated through application of machine-interpreted workflow semantics independent of intrinsic data-pattern inference;
assigning each of the one or more workflow-derived dimensions to a respective column of the columnar-based multi-domain business intelligence data structure;
aligning portions of each of the data sources with the one or more workflow-derived dimensions;
configuring, by the highly efficient computing engine, the columnar-based multi-domain business intelligence data structure using the workflow-derived dimensions, the configuring including generating a columnar storage layout arranged to achieve locality-of-reference and support compilation of workflow-derived queries into machine-executable code;
populating within each column of the columnar-based multi-domain business intelligence data structure the portions of the source data sets based on the harmonized formats and normalized data strings that align with a corresponding dimension;
seeding a guided navigation page generation cache by applying queries of the semantic knowledge plan to the columnar-based multi-domain business intelligence data structure;
presenting a first guided navigation page in a graphical user interface allows a user clicking a next page button in the user interface; and
in response to the user clicking the next page button, updating the user interface to display a second guided navigation page, with the first and the second guided navigation pages derived from the cache.
2 . The computer implemented method of claim 1 , wherein determining the one or more workflow-derived dimensions is based on a semantic knowledge plan for a set of guided navigation pages configured for continuing the workflow.
3 . The computer implemented method of claim 2 , wherein the semantic knowledge plan defines data from the data sources that is associated with queries.
4 . The computer implemented method of claim 3 , wherein populating the columnar-based multi-domain business intelligence data structure includes storing data so that data related to a domain of a query is stored proximal to data associated with the query.
5 . The computer implemented method of claim 1 , wherein the columnar-based multi-domain business intelligence data structure is structured for optimized execution, by the highly efficient computing engine, of one or more queries of the columnar-based multi-domain business intelligence data structure.
6 . The computer implemented method of claim 1 , wherein at least one of the one or more dimensions is a core dimension.
7 . The computer implemented method of claim 1 , wherein populating the columnar-based multi-domain business intelligence data structure includes generating pre-calculated summaries for data of at least one of the one or more dimensions.
8 . The computer implemented method of claim 1 , further comprising organizing data from a portion of the data sources into distinct data domains.
9 . The computer implemented method of claim 1 , further comprising configuring a direct tunnel connection between a portion of the sources of data and the columnar-based multi-domain business intelligence data structure.
10 . The computer implemented method of claim 1 , further including synchronizing the cache with one or more remote client devices.
11 . The computer implemented method of claim 1 , wherein the columnar-based multi-domain business intelligence data structure comprises a set of column headers, a string table indexing result string values, and a set of calendars mapped to data in each column.
12 . The computer implemented method of claim 1 , wherein the columnar-based multi-domain business intelligence data structure comprises a de-normalized data set comprising a set of single records that are self-defining.
13 . The computer implemented method of claim 1 , wherein configuring the columnar-based multi-domain business intelligence data structure facilitates rapid access by the highly efficient computing engine to generate a portion of a set of guided pages.
14 . The computer implemented method of claim 1 , wherein configuring the columnar-based multi-domain business intelligence data structure is based on a plurality of model-based data repositories.
15 . A method comprising:
parsing source data from each of a plurality of disparate data sources based on a set of parsing rules associated with each source;
harmonizing formats of the plurality of disparate data sources;
normalizing data strings of the plurality of disparate data sources per language of a locale or industry specific jargon;
determining, by a highly efficient computing engine, one or more workflow-derived dimensions for each of the plurality of disparate data sources that are associated with one or more steps of a workflow for a business, the determining including applying a machine-executable semantic knowledge plan comprising computer-readable rules that derive the workflow-derived dimensions from the one or more steps of the workflow for the business, the workflow-derived dimensions being generated through application of machine-interpreted workflow semantics independent of intrinsic data-pattern inference;
assigning each of the one or more workflow-derived dimensions to a respective column of a columnar-based multi-domain business intelligence data structure;
aligning portions of each of the plurality of disparate data sources with the one or more workflow-derived dimensions;
configuring, by the highly efficient computing engine, the columnar-based multi-domain business intelligence data structure using the workflow-derived dimensions, the configuring including generating a columnar storage layout arranged to achieve locality-of-reference and support compilation of workflow-derived queries into machine-executable code;
populating within a column of the columnar-based multi-domain business intelligence data structure portions of the plurality of disparate data sources based on the harmonized formats and normalized data strings that align with a corresponding dimension, so that one or more of columns of the columnar-based multi-domain business intelligence data structure align with dimensions determined from the workflow for the business;
seeding a guided navigation page generation cache by applying queries of the semantic knowledge plan to the columnar-based multi-domain business intelligence data structure;
presenting a first guided navigation page in a graphical user interface allows a user clicking a next page button in the user interface; and
in response to the user clicking the next page button, updating the user interface to display a second guided navigation page, with the first and the second guided navigation pages derived from the cache.
16 . The method of claim 15 , wherein determining the one or more workflow-derived dimensions is based on a semantic knowledge plan for a set of guided navigation pages configured for continuing the workflow.
17 . The method of claim 16 , wherein the semantic knowledge plan defines data associated with queries.
18 . The method of claim 17 , wherein populating the columnar-based multi-domain business intelligence data structure includes storing data so that data related to a query domain is stored proximal to data associated with the query.
19 . A system for configuring and automatically populating a columnar-based multi-domain business intelligence data structure arranged to achieve locality-of-reference and support compilation of workflow-derived queries into machine-executable code with data formatted according to a plurality of disparate data sources so that columns of the columnar-based multi-domain business intelligence data structure automatically align with data dimensions automatically derived from steps in a workflow for a business, the system comprising a highly efficient computing engine to executing on a hardware processor that:
parses source data from each of the data sources based on a set of parsing rules associated with each source;
harmonizes formats of the disparate data sources;
normalizes data strings of the data sources per language of a locale or industry specific jargon;
determines one or more dimensions for each of the data sources that are associated with the workflow by applying a machine-executable semantic knowledge plan comprising computer-readable rules that derive the one or more dimensions from workflow steps of the business, the dimensions being generated through application of machine-interpreted workflow semantics independent of intrinsic data-pattern inference;
assigns each of the one or more dimensions to a respective column of the columnar-based multi-domain business intelligence data structure;
aligns portions of each of the data sources with the one or more determined dimensions;
populates within a column of the columnar-based multi-domain business intelligence data structure the portions of the source data sets based on the harmonized formats and normalized data strings that align with a corresponding dimension;
seeds a guided navigation page generation cache by applying queries of the semantic knowledge plan to the columnar-based multi-domain business intelligence data structure;
presents a first guided navigation page in a graphical user interface allows a user clicking a next page button in the user interface; and
in response to the user clicking the next page button, updates the user interface to display a second guided navigation page, with the first and the second guided navigation pages derived from the cache.