Abstract: Methods, systems and computer program products for determining recommended parameters for use in generating a word embedding model are provided. Aspects include storing a plurality of meaningful test cases. Each meaningful test case includes a test data profile and one or more test model parameters used to create a word embedding model that has been classified as yielding meaningful results. Aspects include receiving a production data set to be used in generating a new word embedding model. The production data set includes data stored in a relational database having a plurality of columns and a plurality of rows. Aspects include generating a data profile associated with the production data set. Aspects include generating a recommendation for one or more production model parameters for use in building a word embedding model based on the data profile associated with the production data set and the plurality of meaningful test cases.

Abstract: Methods, systems and computer program products for updating a word embedding model are provided. Aspects include receiving a first data set comprising a relational database having a plurality of words. Aspects also include generating a word embedding model comprising a plurality of word vectors by training a neural network using unsupervised machine learning based on the first data set. Each word vector of the plurality of word vector corresponds to a unique word of the plurality of words. Aspects also include storing the plurality of word vectors and a representation of a hidden layer of the neural network. Aspects also include receiving a second data set comprising data that has been added to the relational database. Aspects also include updating the word embedding model based on the second data set and the stored representation of the hidden layer of the neural network.

Abstract: A computer-implemented method includes determining how to translate between a primary schema and each of two or more native schemas of two or more cloud providers. The primary schema defines one or more access methods for accessing a plurality of cloud resources of the cloud providers. A request is received for a first cloud resource of the plurality of cloud resources, where the first cloud resource is provided remotely by a first cloud provider, and where the request complies with the primary schema. The request is converted into a translated request in compliance with a first native schema of the first cloud provider. The translated request is submitted to the first cloud provider. A response is received from the first cloud provider. The response includes a cloud resource of the plurality of resources, and the response complies with the first native schema of the cloud provider. The response is returned.

Abstract: Techniques for implementing a streaming transaction in a transaction based data storage system is disclosed. In an embodiment, a server computer system stores a dataset comprising a plurality of files where the dataset comprises a corresponding version number. The server computer system receives a command to modify the dataset and, in response, starts a streaming transaction for the dataset. During the streaming transaction, the server computer system receives a plurality of updates to the dataset, wherein each of the plurality of updates modifies one or more files of the plurality of files. The server computer system executes the plurality of updates in the dataset without modifying the corresponding version number of the dataset. When the server computer system commits the streaming transaction to the dataset, the server computer system increments the corresponding version number of the dataset.

Abstract: Methods, systems and computer program products for determining recommended parameters for use in generating a word embedding model are provided. Aspects include storing a plurality of meaningful test cases. Each meaningful test case includes a test data profile and one or more test model parameters used to create a word embedding model that has been classified as yielding meaningful results. Aspects include receiving a production data set to be used in generating a new word embedding model. The production data set includes data stored in a relational database having a plurality of columns and a plurality of rows. Aspects include generating a data profile associated with the production data set. Aspects include generating a recommendation for one or more production model parameters for use in building a word embedding model based on the data profile associated with the production data set and the plurality of meaningful test cases.

Abstract: Methods, systems and computer program products for updating a word embedding model are provided. Aspects include receiving a first data set comprising a relational database having a plurality of words. Aspects also include generating a word embedding model comprising a plurality of word vectors by training a neural network using unsupervised machine learning based on the first data set. Each word vector of the plurality of word vector corresponds to a unique word of the plurality of words. Aspects also include storing the plurality of word vectors and a representation of a hidden layer of the neural network. Aspects also include receiving a second data set comprising data that has been added to the relational database. Aspects also include updating the word embedding model based on the second data set and the stored representation of the hidden layer of the neural network.

Abstract: A computer-implemented method includes determining how to translate between a primary schema and each of two or more native schemas of two or more cloud providers. The primary schema defines one or more access methods for accessing a plurality of cloud resources of the cloud providers. A request is received for a first cloud resource of the plurality of cloud resources, where the first cloud resource is provided remotely by a first cloud provider, and where the request complies with the primary schema. The request is converted into a translated request in compliance with a first native schema of the first cloud provider. The translated request is submitted to the first cloud provider. A response is received from the first cloud provider. The response includes a cloud resource of the plurality of resources, and the response complies with the first native schema of the cloud provider. The response is returned.

Abstract: The present invention provides a support bracket and method of use of a plurality of support brackets in order to construct a temporary guard railing that is easily assembled and removed. The support bracket comprises a support base, support walls upstanding from the base defining therebetween an upwardly opening socket for receipt of a post, and at least one concrete reinforcement member fixedly attached to and laterally extending at an outward angle from one of the support walls.

Abstract: Replacement of legacy information handling systems at a deployment site is automatically managed in cooperation with an information handling system manufacture site by coordinating the building of replacement information handling systems with appropriate configurations. An asset discovery tool interfaces with the legacy information handling systems through a deployment site network to discover the configurations of the legacy systems and communicates the legacy configurations to the manufacture site. An asset translation engine translates the legacy configurations to replacement configurations for building the replacement information handling systems. The ordering of replacement systems and the translation to the replacement configuration is managed by rules defined through an order tool of the deployment site and may include applications packaged at the deployment site and communicated to the manufacture site for installation on the replacement systems.