Kyndryl, Inc.

Muniyandi Perumal Thevar

Nalini M

Gautam K Bhat

Sarita Lavania

Sudhanva Kulkarni

Thangadurai Muthusamy

Kalpesh Sharma

Veeresh Bushetti

Balasubramanian Manivasagam

Arumugam Sakthimurugan

Shaleen Tongia

Viswanatha Krishnamurthy

A computer-implemented method, according to one embodiment, includes causing a trained artificial intelligence (AI) model to derive data access privilege grants before data is stored in a predetermined database, and segmenting the data according to the data access privilege grants during storage of the data in the predetermined database. Metadata that defines the data access privilege grants is stored with the segments of data. The method further includes receiving, from a first user device, a query requesting data stored in the predetermined database. At least some of the metadata is read to identify a segment of the data associated with a data access privilege grant associated with the query. The method further includes allowing the first user device to access the identified segment of data for fulfilling the query.

Segmenting data according to data access privilege grants during storage of the data in a database

A computer-implemented method, in accordance with one embodiment, includes receiving a taxonomy specifying entities of a business service and levels of said entities. Time series data about the entities is collected and stored. Impactor propagation paths between entities is identified. A territory of a health impact of each entity is also identified. A health score for each of the entities, considering impacts on a health of the entity by at least one other entity, is computed based on the data, the propagation paths, and the territories of the entities. At least one of the health scores is output.

Service health assessment

Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises receiving and storing input data from at least two users; calculating a risk score for each identified risk in the received data based on priority risk factors affecting respectively identified risks; dynamically optimizing a risk analysis of the received input for multiple users within a user interface of a computing device by recalculating risk scores based on the received data and identified risks; and generating a notification for the user interface of the computing device based on the dynamic optimization of the risk analysis of the received input.

Dynamic risk based analysis model

A computer-implemented method, computer system, and computer program product for managing a database are disclosed. Features thereof include selecting data lines for analytics, each data line including original data, and adding, to each of the selected data lines, a set of additional bytes to represent metadata about a corresponding one of the data lines. The features further include receiving a request to receive a first data line, and reading a first set of additional bytes corresponding to the first data line.

Built-in analytics for database management

An intelligent user centric design platform is provided. In implementations, a method includes: receiving, by a computing device, software design input from a user, the software design input including software domain information; sending, by the computing device, questions to the user selected from a database of predetermined questions based on the domain information; receiving, by the computing device, answers to the questions from the user, the answers including text information regarding design requirements of the user; determining, by the computing device, a proposed user-centric design (UCD) diagram by matching the answers to a stored UCD diagram in a repository using a supervised machine learning model; and presenting, by the computing device, the proposed UCD diagram in a user interface, wherein the user interface enables acceptance of the proposed UCD diagram or rejection of the proposed UCD diagram.

Intelligent user centric design platform

Methods, computer program products, and/or systems are provided that perform the following operations: reading lines of code included in a collection of source code; identifying an assigned tag in the collection of source code; identifying a start tag location and an end tag location associated with the assigned tag, wherein the lines of code included between the start tag location and the end tag location identify a code block; processing the code block to generate logging data for the code block based, at least in part, on the assigned tag; and providing the logging data for linking to executable byte code compiled from the collection of source code, wherein the logging data is used to log code data relating to the code block during execution of the executable byte code.

Intelligent logging and automated code documentation

Techniques for data evaluation using machine learning are provided. A textual document is received, and the textual document is parsed using a recurrent neural network (RNN) to extract a plurality of keywords. A first subset of keywords which are known by a user and a second subset of keywords which are unknown by the user are each identified. A summary of the textual document is generated based on the second subset of keywords. The summary is output, comprising: outputting information related to a first keyword of the second subset of keywords and, upon determining that the first keyword is understood by the user, outputting information related to a second keyword of the second subset of keywords.

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Madurai, India

Muniyandi Perumal Thevar