Creation of high value data assets from undervalued data
Techniques are disclosed for creating high value data assets from undervalued data. In one example, a method identifies at least one data asset associated with an enterprise which has a lower non-economic valuation score as compared with one or more other data assets associated with the enterprise and is determined to be undervalued. The method then combines the at least one identified data asset with at least one of the one or more other data assets to form a composite data asset, wherein the composite data asset has a higher non-economic valuation score as compared to the at least one identified data asset.
1. A method, comprising:
obtaining, by at least one processing device comprising a processor and a memory, a data asset lineage map comprising a plurality of nodes each associated with a data asset of an enterprise and connectors that represent relationships between the data assets, the data asset lineage map being a hierarchical data structure comprising (i) a set of top-level nodes, (ii) a set of intermediate level nodes and (iii) a set of bottom-level nodes, wherein each data asset associated with a node of the set of top-level nodes, the set of intermediate level nodes and the set of bottom-level nodes having a non-economic valuation score;
identifying, by the at least one processing device, at least one data asset associated with a node of the set of top-level nodes which has a non-economic valuation score below a given threshold score;
removing, by the at least one processing device, the at least one identified data asset from the set of top-level nodes;
re-evaluating, by the at least one processing device, the non-economic valuation score for the data assets associated with (i) the remaining nodes of the set of top-level nodes, (ii) the set of intermediate level nodes and (iii) the set of bottom-level nodes to generate updated non-economic valuation scores;
identifying, by the at least one processing device, based on the re-evaluating step, at least another data asset which has a lower updated non-economic valuation score as compared with one or more other data assets and is determined to be undervalued; and
combining, by the at least one processing device, the at least another identified data asset with at least one of the one or more other data assets to form a composite data asset, wherein the composite data asset has a higher non-economic valuation score as compared to the at least another identified data asset based on the updated non-economic valuation scores.
2. The method of claim 1 , wherein the identifying at least another data asset associated with a node of the set of top-level nodes which has a non-economic valuation score below a given threshold score further comprises identifying one or more data assets that have updated economic valuation scores at or above a given threshold.
3. The method of claim 1 , wherein the non-economic valuation score comprises a business relevance-based score.
4. A system comprising:
one or more processors operatively coupled to one or more memories configured to:
obtain a data asset lineage map comprising a plurality of nodes each associated with a data asset of an enterprise and connectors that represent relationships between the data assets, the data asset lineage map being a hierarchical data structure comprising (i) a set of top-level nodes, (ii) a set of intermediate level nodes and (iii) a set of bottom-level nodes, wherein each data asset associated with a node of the set of top-level nodes, the set of intermediate level nodes and the set of bottom-level nodes having a non-economic valuation score;
identify at least one data asset associated with a node of the set of top-level nodes which has a non-economic valuation score below a given threshold score;
remove the at least one identified data asset associated with a node from the set of top-level nodes;
re-evaluate the non-economic valuation score for the data assets associated with (i) the remaining nodes of the set of top-level nodes, (ii) the set of intermediate level nodes and (iii) the set of bottom-level nodes to generate updated non-economic valuation scores;
identify, based on the re-evaluating, at least another data asset which has a lower updated non-economic valuation score as compared with one or more other data assets and is determined to be undervalued; and
combining the at least another identified data asset with at least one of the one or more other data assets to form a composite data asset, wherein the composite data asset has a higher non-economic valuation score as compared to the at least another identified data asset based on the updated non-economic valuation scores.
5. The system of claim 4 , wherein the identifying at least another data asset associated with a node of the set of top-level nodes which has a non-economic valuation score below a given threshold score further comprises identifying one or more data assets that have updated economic valuation scores at or above a given threshold.
6. The system of claim 4 , wherein the non-economic valuation score comprises a business relevance-based score.
7. An article of manufacture comprising a processor-readable storage medium having encoded therein executable code of one or more software programs, wherein the one or more software programs when executed by one or more processing devices implement the steps of:
obtaining a data asset lineage map comprising a plurality of nodes each associated with a data asset of an enterprise and connectors that represent relationships between the data assets, the data asset lineage map being a hierarchical data structure comprising (i) a set of top-level nodes, (ii) a set of intermediate level nodes and (iii) a set of bottom-level nodes, wherein each data asset associated with a node of the set of top-level nodes, the set of intermediate level nodes and the set of bottom-level nodes having a non-economic valuation score;
identifying at least one data asset associated with a node of the set of top-level nodes which has a non-economic valuation score below a given threshold score;
removing the at least one identified data asset from the set of top-level nodes;
re-evaluating the non-economic valuation score for the data assets associated with (i) the remaining nodes of the set of top-level nodes, (ii) the set of intermediate level nodes and (iii) the set of bottom-level nodes to generate updated non-economic valuation scores;
identifying, based on the re-evaluating step, at least another data asset which has a lower updated non-economic valuation score as compared with one or more other data assets and is determined to be undervalued; and
combining the at least another identified data asset with at least one of the one or more other data assets to form a composite data asset, wherein the composite data asset has a higher non-economic valuation score as compared to the at least another identified data asset based on the updated non-economic valuation scores.
8. The article of claim 7 , wherein the non-economic valuation score comprises a business relevance-based score.
9. The article of claim 7 , wherein the identifying at least another data asset associated with a node of the set of top-level nodes which has a non-economic valuation score below a given threshold score further comprises identifying one or more data assets that have updated economic valuation scores at or above a given threshold.
10. The article of claim 7 , wherein the nodes and connectors each store metadata.
11. The article of claim 7 , wherein at least one node of the set of bottom-level nodes is connected to at least one node of the set of top-level nodes.
12. The article of claim 7 , wherein at least one node of the set of bottom-level nodes is connected to at least one node of the set of intermediate level nodes.
13. The article of claim 7 , wherein at least one node of the set of bottom-level nodes is connected to at least one node of the set of intermediate level nodes which is connected to at least one node of the set of top-level nodes.
14. The system of claim 4 , wherein the nodes and connectors each store metadata.
15. The system of claim 4 , wherein at least one node of the set of bottom-level nodes is connected to at least one node of the set of top-level nodes.
16. The system of claim 4 , wherein at least one node of the set of bottom-level nodes is connected to at least one node of the set of intermediate level nodes.
17. The system of claim 4 , wherein at least one node of the set of bottom-level nodes is connected to at least one node of the set of intermediate level nodes which is connected to at least one node of the set of top-level nodes.
18. The method of claim 1 , wherein at least one node of the set of bottom-level nodes is connected to at least one node of the set of top-level nodes.
19. The method of claim 1 , wherein at least one node of the set of bottom-level nodes is connected to at least one node of the set of intermediate level nodes.
20. The method of claim 1 , wherein at least one node of the set of bottom-level nodes is connected to at least one node of the set of intermediate level nodes which is connected to at least one node of the set of top-level nodes.