Example embodiments relate to a system to generate and cause display of a specially configured graphical user interface to receive and present collections of images. According to certain example embodiments, an image analysis system: receives an image file from a client device; generates a hash value based on the image file; performs a comparison of the hash value with a list that comprises a collection of hash values; identifies a match to the hash value among the collection of hash values; assigns a label to the image file in response to identifying the match among the collection of image files from the list; and indexes the image file at a memory location identified by the label assigned to the image file.

An information processing apparatus according to one embodiment includes one or more hardware processors coupled to a memory. The one or more hardware processors acquires pieces of target data of different types. The one or more hardware processors generates element information for each element included in the pieces of the target data. The element information indicates the corresponding element. The one or more hardware processors links, with each other, related pieces of the element information and stores the linked pieces of the element information in a storage device.

A computing device generates a first token for first data content that is associated with a first relationship and a second relationship, and a second token for second data content that is associated with the first relationship and a third relationship, such that the first token and second token are generated based on a frequency of use of data values included in the first and the second data content. The computing device calculates a first similarity score of data values from third data content that is associated with the second relationship and a fourth relationship with data values from fourth data content that is associated with the third relationship and the fourth relationship in response to the first and second token matching. The computing device then performs, in response to the first similarity score satisfying a similarity threshold, a first modification to any of the data content.

A query is received from a client device and a mode is selected to process the query from a set of possible modes. The possible modes include a fast mode and a low-cost mode. If the fast mode is selected, the query is forwarded to a cloud database to retrieve responsive records. If the low-cost mode is selected, the cloud database is queried for index metadata of responsive records and the index metadata is used to retrieve the responsive records from a datastore other than the cloud database. Regardless of the mode selected, the responsive records are provided to the client device.

Performing an operation comprising transforming an input dataset to a predefined format, extracting, from the transformed dataset, a plurality of features describing the transformed dataset, and generating, by a machine learning (ML) algorithm executing on a processor and based on an ML model, a plurality of rules for modifying the transformed dataset to conform with a first data model.

Replicas are selected in a large distributed network, and the roles for these replicas are identified. In one example, a leader is selected from among candidate computing dusters. To make this selection, an activity monitor predicts or monitors the workload of one or more clients. Different activities of the workload are given corresponding weights. The delay in performing requested activities, modified by these weights is found, and the candidate leader with the lowest weighted delay is selected as the leader.

Replicas are selected in a large distributed network, and the roles for these replicas are identified. In one example, a leader is selected from among candidate computing dusters. To make this selection, an activity monitor predicts or monitors the workload of one or more clients. Different activities of the workload are given corresponding weights. The delay in performing requested activities, modified by these weights is found, and the candidate leader with the lowest weighted delay is selected as the leader.

A centralized database identifier repository may identify databases using a unique identifier, or key tag, for each database. Each identified database may include data relating to one or more specific data elements. The repository may include a variety of data elements. Each data element may be associated with one or more database keys. The repository may be a repository of reference pointers. The repository may facilitate data viewing and data retrieval. A requestor may search for a data element using the centralized repository. The repository may retrieve data relating to a specific data element, from all databases identified by unique identifiers, that include data relating to the data element. The databases' unique identifiers may be encrypted tokens.

A computer-implemented method applies insights from a variety of data sources to each of the data sources. The method includes identifying a set of data sources, wherein each of the data sources are associated with a domain. The method includes analyzing documentation for each of the data sources. The method further includes extracting a set of attributes for each data source, and determining a data schema associated with each data source. The method includes mapping each data schema to a common domain schema. The method also includes linking, based on the mapping and on the set of attributes for each data source, common features across each data source. The method includes generating, in response to the linking, a knowledge graph. The method further includes preparing a visual display for a set of domain insights; and forking the set of domain insights into a first data source.

Techniques are provided for unifying filter operators in exchange, transform, load (ETL) plans. Such a technique includes a method that may include receiving, by a computer system, an ETL plan including a split operator and a plurality of filter operators. The may include identifying, by the computer system, that the plurality of filter operators are configured to act on data output by the split operator in the ETL plan. The method may include generating, by the computer system, a unified filter operator using the plurality of filter operators. The method may include generating, by the computer system, an updated ETL plan comprising the unified filter operator providing filtered data to the split operator. The method may also include storing the updated ETL plan in a data store.