MIGRATION ESTIMATION WITH PARTIAL DATA

• US 20160092813A1
• Filed: 09/30/2014
• Published: 03/31/2016
• Est. Priority Date: 09/30/2014
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Markley, Matthew A., Parisa, Venkata Vinay, Pfitzmann, Birgit M., Baker, John K., Huang, Yun-Wu
• Granted Patent: US 10,762,456 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/06313 Resource planning in a project environment

Abstract

Access is obtained to raw historic information technology migration data, which data is transformed in accordance with a classification scheme to obtain classified key historic information technology migration data. A statistical model with conditional distributions of the key historic information technology migration data is built. Prior to a new information technology migration project, access is obtained to incomplete data characterizing the new information technology migration project. The statistical model is used to derive data missing from the incomplete data characterizing the new information technology migration project, to obtain derived data. At least one of a migration plan and an estimate for the new information technology migration project is created based on the incomplete data and the derived data.

Claims

1. A method comprising:

obtaining access to raw historic information technology migration data;

transforming said raw historic information technology migration data in accordance with a classification scheme to obtain classified key historic information technology migration data;

building a statistical model with conditional distributions of said key historic information technology migration data;

prior to a new information technology migration project, obtaining access to incomplete data characterizing said new information technology migration project;

using said statistical model to derive data missing from said incomplete data characterizing said new information technology migration project, to obtain derived data; and

creating at least one of a migration plan and an estimate for said new information technology migration project based on said incomplete data and said derived data.

2. The method of claim 1, further comprising deriving said classification scheme according to influence of classes on migration plans, based on at least one existing migration plan with associated real costs.

3. The method of claim 2, wherein said deriving comprises deriving said classification scheme with at least two classes comprising at least two of operating system, software type, hardware type, storage type, criticality, and clusteredness.

4. The method of claim 3, wherein:

said deriving comprises deriving said classification scheme with attributes for each of said at least two classes;

said at least two classes comprise operating system and hardware type;

said attributes for operating system comprise class, name, and version;

said attributes for hardware comprise whether virtualized, platform type, vendor, model, age, and size;

said statistical model comprises conditional probability of whether hardware is virtualized based on operating system class;

said incomplete data comprises operating system per server type without data indicating whether virtualized; and

said derived data comprises whether virtualized per operating system per server type, in accordance with said conditional probability.

5. The method of claim 3, wherein:

said deriving comprises deriving said classification scheme with attributes for each of said at least two classes;

said at least two classes comprise operating system and hardware type;

said attributes for operating system comprise class, name, and version;

said attributes for hardware comprise whether virtualized, platform type, vendor, model, age, and size;

said statistical model comprises conditional probability of operating system class based on whether hardware is virtualized;

said incomplete data comprises data indicating whether virtualized without operating system per server type; and

said derived data comprises operating system per server type, in accordance with said conditional probability.

6. The method of claim 1, further comprising augmenting said statistical model by general constraints.

7. The method of claim 1, wherein said incomplete data comprises first incomplete data, said new information technology migration project comprises a first new information technology migration project, said derived data comprises first derived data, said statistical model comprises a first statistical model, and said at least one of a migration plan and an estimate comprises a first at least one of a migration plan and an estimate, further comprising:

prior to a second new information technology migration project, obtaining access to second incomplete data characterizing said second new information technology migration project;

determining that said second incomplete data do not fit said first statistical model;

building a second statistical model based on said second incomplete data and said classified key historic information technology migration data;

using said second statistical model to derive data missing from said second incomplete data characterizing said second new information technology migration project, to obtain second derived data; and

creating at least one of a migration plan and an estimate for said new information technology migration project based on said incomplete data and said derived data.

8. The method of claim 1, wherein, in said incomplete data, data is missing across multi-dimensions, further comprising filling missing data for some of said dimensions using patterns from said historical data, and using patterns from existing partial data to augment remaining ones of said dimensions with missing data.

9. The method of claim 1, further comprising providing a system, wherein the system comprises distinct software modules, each of the distinct software modules being embodied on a computer-readable storage medium, and wherein the distinct software modules comprise a database access module, a customer data estimation module, and a plan generation engine module;

wherein;

at least said obtaining of said access to said raw historic information technology migration data and said obtaining of said access to said incomplete data characterizing said new information technology migration project are carried out by said database access module executing on at least one hardware processor;

said using of said statistical model to derive said data missing from said incomplete data characterizing said new information technology migration project, to obtain said derived data, is carried out by said customer data estimation module executing on said at least one hardware processor; and

said creating said at least one of a migration plan and an estimate for said new information technology migration project based on said incomplete data and said derived data comprises creating at least said migration plan using said plan generation engine module executing on said at least one hardware processor.

10. An apparatus comprising:

a memory; and

at least one processor, coupled to said memory, and operative to;

obtain access to raw historic information technology migration data;

transform said raw historic information technology migration data in accordance with a classification scheme to obtain classified key historic information technology migration data;

build a statistical model with conditional distributions of said key historic information technology migration data;

prior to a new information technology migration project, obtain access to incomplete data characterizing said new information technology migration project;

use said statistical model to derive data missing from said incomplete data characterizing said new information technology migration project, to obtain derived data; and

create at least one of a migration plan and an estimate for said new information technology migration project based on said incomplete data and said derived data.

11. The apparatus of claim 10, wherein said at least one processor is further operative to derive said classification scheme according to influence of classes on migration plans, based on at least one existing migration plan with associated real costs.

12. The apparatus of claim 11, wherein said deriving comprises deriving said classification scheme with at least two classes comprising at least two of operating system, software type, hardware type, storage type, criticality, and clusteredness.

13. The apparatus of claim 12, wherein:

said deriving comprises deriving said classification scheme with attributes for each of said at least two classes;

said at least two classes comprise operating system and hardware type;

said attributes for operating system comprise class, name, and version;

said attributes for hardware comprise whether virtualized, platform type, vendor, model, age, and size;

said statistical model comprises conditional probability of whether hardware is virtualized based on operating system class;

said incomplete data comprises operating system per server type without data indicating whether virtualized; and

said derived data comprises whether virtualized per operating system per server type, in accordance with said conditional probability.

14. The apparatus of claim 12, wherein:

said deriving comprises deriving said classification scheme with attributes for each of said at least two classes;

said at least two classes comprise operating system and hardware type;

said attributes for operating system comprise class, name, and version;

said attributes for hardware comprise whether virtualized, platform type, vendor, model, age, and size;

said statistical model comprises conditional probability of operating system class based on whether hardware is virtualized;

said incomplete data comprises data indicating whether virtualized without operating system per server type; and

said derived data comprises operating system per server type, in accordance with said conditional probability.

15. The apparatus of claim 10, wherein said at least one processor is further operative to augment said statistical model by general constraints.

16. The apparatus of claim 10, wherein said incomplete data comprises first incomplete data, said new information technology migration project comprises a first new information technology migration project, said derived data comprises first derived data, said statistical model comprises a first statistical model, and said at least one of a migration plan and an estimate comprises a first at least one of a migration plan and an estimate, wherein said at least one processor is further operative to:

prior to a second new information technology migration project, obtain access to second incomplete data characterizing said second new information technology migration project;

determine that said second incomplete data do not fit said first statistical model;

build a second statistical model based on said second incomplete data and said classified key historic information technology migration data;

use said second statistical model to derive data missing from said second incomplete data characterizing said second new information technology migration project, to obtain second derived data; and

create at least one of a migration plan and an estimate for said new information technology migration project based on said incomplete data and said derived data.

17. The apparatus of claim 10, wherein, in said incomplete data, data is missing across multi-dimensions, wherein said at least one processor is further operative to fill missing data for some of said dimensions using patterns from said historical data, and use patterns from existing partial data to augment remaining ones of said dimensions with missing data.

18. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, and wherein the program instructions are executable by a processor to cause the processor to perform a method comprising:

obtaining access to raw historic information technology migration data;

transforming said raw historic information technology migration data in accordance with a classification scheme to obtain classified key historic information technology migration data;

building a statistical model with conditional distributions of said key historic information technology migration data;

prior to a new information technology migration project, obtaining access to incomplete data characterizing said new information technology migration project;

using said statistical model to derive data missing from said incomplete data characterizing said new information technology migration project, to obtain derived data; and

creating at least one of a migration plan and an estimate for said new information technology migration project based on said incomplete data and said derived data.

19. The computer program product of claim 18, wherein the program instructions are further executable by a processor to cause the processor to perform a method further comprising deriving said classification scheme according to influence of classes on migration plans, based on at least one existing migration plan with associated real costs.

20. The computer program product of claim 19, wherein said deriving comprises deriving said classification scheme with at least two classes comprising at least two of operating system, software type, hardware type, storage type, criticality, and clusteredness.