Some aspects are directed to systems for providing access to data. An example includes a computer system implementing a data access framework for providing data to one or more predictive models. The system is configured to receive at least one asset definition comprising an asset identifier for at least one asset associated with at least one data source, receive at least one data lens definition comprising a data lens identifier and a logical model identifier, the logical model identifier identifying at least one portion of a logical system model, access a first datastore to retrieve asset information extracted from the at least one data source, determine, using the logical model identifier, a portion of the logical system model associated with the retrieved asset information, format the retrieved asset information for storage in a second datastore corresponding to the logical system model, and store the formatted retrieved asset information in the second datastore.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer system implementing a data access framework for providing data to one or more predictive models, the system configured to: receive at least one asset definition comprising an asset identifier for at least one asset associated with at least one data source; receive at least one data lens definition comprising a data lens identifier and a logical model identifier, the logical model identifier identifying at least one portion of a logical system model; access a first datastore to retrieve asset information extracted from the at least one asset; determine, using the logical model identifier, a portion of the logical system model associated with the retrieved asset information; format the retrieved asset information for storage in a second datastore corresponding to the logical system model; and enable access to the formatted retrieved asset information via the second datastore. 2. The computer system of claim 1, wherein the at least one asset definition further comprises an asset type, wherein the at least one data lens definition is a plurality of data lens definitions, and wherein one of the plurality of data lens definitions is selected for association with the at least one asset definition based at least in part on the asset type. 3. The computer system of claim 1, wherein the asset definition further comprises at least one address within the first datastore indicating the location of the asset information extracted from the at least one asset. 4. The computer system of claim 1, further configured to initialize an extractor in response to receiving the at least one asset definition, wherein the extractor is configured to communicate with the asset to extract data from the at least one data source and store the extracted data in the first datastore. 5. The computer system of claim 4, wherein the extractor is selected from a plurality of extractors based on the at least one asset definition. 6. The computer system of claim 1, further configured to initialize a data lens in response to receiving the at least one data lens definition, wherein the data lens provides an endpoint for accessing a portion of the logical system model corresponding to the logical model identifier. 7. The computer system of claim 6, wherein the data lens provides access to only the portion of the logical system model corresponding to the logical model identifier. 8. The computer system of claim 6, wherein the data lens definition further comprises at least one access permission, and wherein access to the portion of the logical system model provided by the data lens is limited based on the at least one access permission. 9. The computer system of claim 6, wherein the initialized data lens provides access to the portion of the logical system model to one or more predictive models. 10. The computer system of claim 1, wherein enabling access to the formatted retrieved asset information comprises caching the formatted retrieved asset information in a graph database queryable by a data lens associated with the data lens definition. 11. The computer system of claim 1, wherein enabling access to the formatted retrieved asset information comprises enabling a pass-through of the second datastore to the retrieved asset information stored in the first datastore in response to receiving a query at a data lens associated with the data lens definition. 12. A method for implementing a data access framework to providing data to one or more predictive models, the method comprising: receiving at least one asset definition comprising an asset identifier for at least one asset associated with at least one data source; receiving at least one data lens definition comprising a data lens identifier and a logical model identifier, the logical model identifier identifying at least one portion of a logical system model; accessing a first datastore to retrieve asset information extracted from the at least one asset; determining, using the logical model identifier, a portion of the logical system model associated with the retrieved asset information; formatting the retrieved asset information for storage in a second datastore corresponding to the logical system model; and enabling access to the formatted retrieved asset information via the second datastore. 13. The method of claim 12, wherein the at least one asset definition further comprises an asset type, wherein the at least one data lens definition is a plurality of data lens definitions, and wherein one of the plurality of data lens definitions is selected for association with the at least one asset definition based at least in part on the asset type. 14. The method of claim 12, wherein the asset definition further comprises at least one address within the first datastore indicating the location of the asset information extracted from the at least one asset. 15. The method of claim 12, further comprising initializing an extractor in response to receiving the at least one asset definition, wherein the extractor is configured to communicate with the asset to extract data from the at least one data source and store the extracted data in the first datastore. 16. The method of claim 15, wherein the extractor is selected from a plurality of extractors based on the at least one asset definition. 17. The method of claim 12, further comprising initializing a data lens in response to receiving the at least one data lens definition, wherein the data lens provides an endpoint for accessing a portion of the logical system model corresponding to the logical model identifier. 18. The method of claim 17, wherein the data lens provides access to only the portion of the logical system model corresponding to the logical model identifier. 19. The method of claim 17, wherein the data lens definition further comprises at least one access permission, and wherein access to the portion of the logical system model provided by the data lens is limited based on the at least one access permission. 20. A non-transitory computer readable storage medium comprising instructions that, when executed by a processor, configure the processor to: receive at least one asset definition comprising an asset identifier for at least one asset associated with at least one data source; receive at least one data lens definition comprising a data lens identifier and a logical model identifier, the logical model identifier identifying at least one portion of a logical system model; access a first datastore to retrieve asset information extracted from the at least one asset; determine, using the logical model identifier, a portion of the logical system model associated with the retrieved asset information; format the retrieved asset information for storage in a second datastore corresponding to the logical system model; and enable access to the formatted retrieved asset information via the second datastore.