Abstract: A system for maintaining consistency of a data value using a probability includes an interface and a processor. The interface is configured to receive a data value for storing. The processor is configured to store the data value in a data element of a data structure and determine, using an adaptive filter, a probability of certainty associated with the data value. The probability of certainty associated with the data value depends on a time since the data value was updated. The adaptive filter provides as output the probability of certainty and store the probability of certainty associated with the data value in the data structure.

Abstract: Examples described herein provide a computer-implemented method that includes defining a key performance indicator associated with a non-instrumented object of a processing system. The method further includes determining a current anomaly level of the key performance indicator for an instrumented object having a relationship with the non-instrumented object. The method further includes assigning an anomaly level to the non-instrumented object based on the current anomaly level.

Abstract: A non-transitory computer-readable storage medium storing a transmission support program that causes at least one computer to execute a process, the process includes generating a management identifier of a message in response to reception of the message; returning the management identifier to a transmitter of the message; when receiving the management identifier and lists of personal identifiers of individuals who have attributes according to conditions regarding the attributes, from each of a plurality of companies that holds information on the attributes of the individuals, based on reception of the conditions and the management identifier from the transmitter, specifying the personal identifiers that are duplicate between the lists that have the management identifier that is common; and transmitting the specified personal identifiers and the received message.

Abstract: A processor may identify a plurality of data sets subject to upcoming update processing in a next update cycle. For each of the plurality of data sets, the processor may determine a probability that data included in the data set has changed since a most recent update processing. The processor may exclude a first subset of the plurality of data sets having respective probabilities below a threshold value from the upcoming update processing until the respective probabilities are determined again in a subsequent update cycle. The processor may perform the upcoming update processing on the plurality of the data sets not included in the first subset, where the upcoming update processing may include obtaining updated data from at least one external data source.

Abstract: A method for confirming configuration of a new current genesis block in a blockchain configured to enable pruning before the new current genesis block includes: receiving, by a blockchain node in a blockchain network, a genesis response message from another node in the network, the message including a configuration value and an ordinal value; identifying a plurality of standard blocks in the blockchain added subsequent to an earlier genesis block that includes a number preceding the ordinal value; aggregating smart contract state changes from each of the identified plurality of standard blocks; and validating the configuration value included in the received genesis response message based on the aggregated smart contract state changes. The aggregating of smart contract states can be done by the processor of the blockchain node configuring the new current genesis block, or by another blockchain node.

Abstract: Maintaining, for each target key in a key-value computer database, a signature policy; creating a transaction candidate in the database based on a transaction context submitted to the database by a first user, the transaction candidate comprising: a key, a value comprising a transaction content and a signature of the first user, and a signors list of additional one or more users who are required to co-sign the transaction candidate before the transaction candidate is committed in the database as a transaction, wherein the signors list is automatically computed based on the signature policies of the one or more target keys; collecting a signature for the transaction candidate from at least one of the additional one or more users, according to the signors list; verifying that all signatures required by the signors list have been collected; and in response to the verification, committing the transaction content of the transaction candidate.

Abstract: A transaction processing method and apparatus, a computer device, and a storage medium, improve transaction processing efficiency. When read and write operations of a target transaction are executed, a concurrent transaction of a target transaction can be obtained and used to determine whether a data anomaly exists based on read-write sets of the concurrent transaction and the target transaction. The read-write sets of the concurrent transaction and the target transaction can be merged to commit the target transaction. In this way, various data anomalies can be comprehensively detected, and data state consistency is ensured. The transaction processing method does not rely completely on locking technology nor on dependency graph technology, thereby preventing system concurrency from being limited, improving querying speed and modification speed of data, and improving transaction processing efficiency.

Abstract: Methods, non-transitory computer-readable media, and query verification apparatuses are disclosed that receive a result vector, an index to the result vector, a range proof, and an inner product proof from a prover device after providing a query vector to the prover device. The prover device hosts a vector database with rows and columns. Second and third commitments to a distance vector and a random linear combination vector, respectively, are generated based on a first commitment to the rows. The range proof is checked using the second commitment and the inner product proof is checked using the third commitment and a generator used to generate the first commitment and identified based on the index. The result vector is returned after confirming that it is one of the rows and each of the rows is as far from the query vector as the result vector based on the check of the proofs.

Abstract: Provided is a system, method, and apparatus for generating analytics with structured query files. The method includes the steps of generating at least one graphical user interface configured to receive query parameters from a user for querying transaction data, generating a request file based on the query parameters, the request file including a request definition object and a segment object, processing the request file to query at least one transactional database based at least partially on the request file, and generating a response file including transaction data based on a return from the query of the at least one database, the response file structured based on the request definition object from the request file.

Abstract: Techniques for generating an interactive visualization tool for building nested queries are disclosed. The interactive nested query visualization tool allows a user to observe, analyze, and modify query characteristics and attributes of a set of nested queries. A system displays an interactive visual depiction of a set of nested queries. Visual representations of the nested queries are positioned relative to each other based on the relationships between the nested queries. The system displays, simultaneously with the set of nested queries, editable fields for a selected query. The system modifies a functionality of a user interface based on which of the nested queries is selected.

Abstract: Systems and methods are described for generation of a query using a non-textual input. For example, the query can be generated using a point and click input. A selection of a data source can be identified and an initial query can be automatically generated based on the selection of the data source. A graphical user interface can be displayed and populated with one or more selectable parameters based on the initial query. A selection of the one or more selectable parameters can be received as a non-textual input and a query can be automatically generated based on the selection. For example, a query for execution by a data intake and query system can be generated based on the selection. The query can be provided to the data intake and query system. The data intake and query system may then execute the query on a set of data.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and data-driven control systems and algorithms based on graph-based data arrangements, and, more specifically, to a computing platform configured to receive and analyze datasets to implement a data model with which to identify relevant data catalog data derived from graph-based data arrangements, whereby a processor may be configured to cause implementation of subsets of programmatic executable instructions based on relevant data catalog data, at least one example of which generates a concept interface portion adapted to an associated concept, among other things. In some examples, a method may include identifying attributes associated with data values linked to a conceptual entity, determining criteria data of a targeted application, selecting programmatic executable instructions based on the criteria data, and extracting data from a graph data arrangement as a function of the attributes, among other things.

Abstract: Systems and methods for automatically detecting search queries from software documents to validate component searches are provided. An example method includes receiving a number of documents, parsing a number of documents to extract a number of sentences, mapping each of the number of sentences to a number of sections, filtering the number of sentences, consolidating the number of sections and the number of filtered sentences into a summary, partitioning the summary into a first number of sentences, replacing one or more of the number of sentences with one or more paraphrase sentences generated by a machine learning model to generate a second number of sentences, and generating a number of search queries based on the second number of sentences.

Abstract: In a computer embodiment, in a polyglot database management system (DBMS) that contains a guest language runtime environment, a database buffer is configured that the guest language runtime environment does not manage. In the polyglot DBMS, logic that is defined in a guest language is invoked to retrieve, into the database buffer, a value stored in a database in the polyglot DBMS. Compiling the logic causes semantic analyzing the logic to detect that usage of the retrieved value cannot occur after the retrieved value is overwritten in the database buffer. When detecting that such usage of the retrieved value cannot occur, the logic is executed without, after the retrieved value is overwritten in the database buffer, retaining a copy of the retrieved value in a memory region that the guest language runtime environment manages.

Abstract: Techniques are disclosed relating to managing data objects. A computer system may access a first application comprising a set of functions and may execute a second application to facilitate execution of the first application. The first application may be written in a different programming language than the second application. The second application may manage, on behalf of the first application, memory resources of data objects that are defined within ones of the set of functions of the first application. The second application may establish, for the data objects, ownership information that indicates which ones of the functions are utilizing the data objects. The ownership information may be usable to determine, upon completion of a function of the set of functions, whether a given one of the data objects can be deallocated based on whether the given data object is being utilized by another function.

Abstract: A method includes parsing, by at least one hardware processor, a query to determine query comments and query code associated with the query. A query execution plan is generated based on the query code. Query execution using the query code is performed at a first computing node associated with a query processing pipeline. A detection is made that the query comments are indicative of a software bug in the query code based on analysis of the query comments. The detection is performed at a second computing node associated with a query analysis pipeline. A notification of the software bug and a result of the query execution is output.

Abstract: A server system provided according to an aspect of the present disclosure provides a shared connection pool to parallel execution entities accessing database instances of a distributed database when processing requests. A shared connection pool implies that each pool connection of the connection pool may be used for serving different execution entities requiring access to different database instances. In an embodiment, the database instances correspond to shards together implementing a distributed database, and the parallel execution entities correspond to threads.

Abstract: Systems for dynamic data reorganization and query optimization are provided. In some aspects, a database query may be received and evaluated to determine whether it meets one or more criteria. If the database query meets the one or more criteria, the query may be executed and the output of the executed database may be transmitted to the user device. If the database query does not meet the one or more criteria, data associated with the database query may be dynamically modified and/or reorganized (e.g., using machine learning). Modified data may be generated based on the dynamically modified and/or reorganized data. The modified data may be stored in an optimized query cache. An updated query may be generated based on the modified data and stored in the optimized query cache. The updated query may be executed and an output of the executed updated query may be transmitted to the user device.

Abstract: An embodiment for identifying and processing poly-process natural language queries may include receiving a natural language query. The embodiment may also automatically identify a bridge entity in the received natural language query. The embodiment may also automatically determine whether the received natural language query is a poly-process query. The embodiment may further include, in response to identifying that the received natural language query is the poly-process query, automatically generating sub-queries for each process in the poly-process query and generate results for each sub-query. The embodiment may also automatically combining the results of each sub-query using the bridge entity to output a combined result. The embodiment may further include automatically generating a modified sub-query for post-processing of the combined result. The embodiment may also automatically process the modified sub-query to generate a final query result for the received natural language query.

Abstract: Index management for non-relational database systems may be automatically performed. Performance of queries to a non-relational database may be evaluated to determine whether to create or remove an additional index. An additional index may be automatically created to store a subset of data projected from the non-relational database to utilize when performing a query to the non-relational database instead of accessing data in the non-relational database.

Abstract: A method for processing a plurality of queries is provided according to embodiments of the present disclosure. In this method, based on a plurality of queries and an execution plan for the plurality of quires, a plurality of record identification (ID) numbers can be stored into a pool in a numerical order. Each of the plurality of record ID numbers can identify a data record in a database. Then, the execution plan can be performed to batch a plurality of data records corresponding to the plurality of record ID numbers in the database based on a distribution of the plurality of record ID numbers in the pool.

Abstract: Techniques to efficiently assign available workers to executing multiple graph queries concurrently on a distributed graph database are disclosed. The techniques comprise a runtime engine assigning multiple workers to executing portions of multiple graph queries, each worker in each assignment asynchronously executing a portion of a graph query within a parallel-while construct that includes return statements at different locations, and the runtime engine reassigning a worker to executing another portion of the same or a different graph query to optimize the overall performance of all workers.

Abstract: Techniques and systems can receive a query identifying a name linked to performance data of a computer system and a location of the performance data. The name linked to the performance data of the computer system and the location of the performance data can be communicated to a first computer-implemented system. The first computer-implemented system can include identifying data derived from the name and the location of the performance data. Identifying data derived from the name and the location of the performance data can be received from the first computer-implemented system. The identifying data derived from the name and the location of the performance data can be used to retrieve the performance data. The performance data can be hosted by a second computer-implemented system that is different than the first computer-implemented system.

Abstract: A method may include receiving a definition of a table user-defined function (TUDF) in a graph query language. The table user-defined function may be created based on the definition. For example, the creation of the table user-defined function may include checking and compiling the definition to generate executable code associated with the table user-defined function. Upon receiving a query including a relational query language statement invoking the table user-defined function, such as a structured query language select statement, the query may be executed on at least a portion of a graph data stored in a database. The executing of the query may include calling the executable code to execute the table user-defined function included in the relational query language statement. Related systems and computer program products are also provided.

Abstract: Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising detecting a real close of books (COB) of a data transport, the real COB associated with a set of raw events transmitted over the data transport, flushing a stream processor in response to detecting the real COB, and retrieving a set of processed events from a distributed file system after the flushing is complete. A fact COB computation is then performed on the set of processed events and the set of raw events, the fact COB computation outputting a number of missing events, each missing event representing a raw event that is not present in the set of processed events. The processed events are then certified upon determining that the number of missing events is below a threshold.

Abstract: Disclosed is a method for processing a query related to a plurality of partitions included in a plurality of tables having different partition information, which is performed by a computing device including one or more processors. The method includes acquiring the plurality of partitions for processing the query. The method includes acquiring global partition indexes for encompassing the acquired partitions and acquiring local partition indexes corresponding to the acquired partitions, respectively. The method includes processing the query at least partially based on the global partition indexes and the local partition indexes.

Abstract: A method for comparing a first and a second databases to determine whether an individual is represented by both an element of the first database and an element of the second database, wherein said elements are biometric data, including the implementation of the steps applying a classification model for each element of each database so as to construct a set of first and second bins of the respective first and second databases, each bin bringing together similar elements, each first bin being associated with a second bin; comparing the elements from the first database for at least one pair of an associated first bin and second bin belonging to said first bin with the elements from the second database belonging to said second bin, at least one of the first and the second databases then being encrypted homomorphically.

Abstract: Systems and methods for configuring data stream filtering are disclosed. In one embodiment, a method for data stream processing comprises receiving an incoming dataset stream at a data stream processing environment, wherein the dataset stream comprises a data stream; configuring with a streaming data filter configuration tool, one or more filter parameters for a data filter that receives the data stream; computing with the streaming data filter configuration tool, one or more filter statistics estimates based on the filter parameters, wherein the filter statistics estimates are computed from sample elements of a representative sample of the data stream retrieved from a representative sample data store; outputting to a workstation user interface the filter statistics estimates; and configuring the data filter to apply the filter parameters to the data stream in response to an instruction from the workstation user interface.

Abstract: System (100) comprising several edge computing devices (ECD), each one comprising a sensor (S), a memory (M), a Central Processing Unit, CPU and a digital communication interface (IF) allowing digital communication digitally across a network (NW). The invention is characterised in that each device is arranged with a respective interpreting software function, arranged to interpret computer code, received via said interface and stored in said memory, according to a query language having a predetermined syntax; in that said syntax is arranged to define queries the results of which are streams of data; in that each device is arranged to produce a result to at least one query and to communicate said result via said interface, in that said syntax allows said query to be defined in terms of a calculation to be performed based on a measured value from said sensor, and in that the device in question is arranged to perform, as a part of said interpretation, said calculation. The invention also relates to a method.

Abstract: Provided are systems, methods, and computer-program products for a contextual connection system. In various implementations, the system can receive data corresponding to an interaction between a first node and a second node. The system can use an interaction history to associate the first node with a subset of other nodes. The system can receive input corresponding to a search, where the search is associated with the third node. The search requests a list of nodes, where nodes in the list of nodes are likely to accept a connection request from the third node. The system can determine similarity between the third node and the second node. Determining the similarity can further include using the similarity and a result of searching to identify the context associated with the first node. The system can add the first node to the list of nodes, and respond to the search with the list of nodes.

Abstract: This application relates to systems and methods for providing search results based on a primary intent. In some examples, a disclosed system includes a memory resource storing instructions; and one or more processors coupled to the memory resource. The one or more processors are configured to execute the instructions to: receive, from a user, a search query including a plurality of words, identify a plurality of intention terms from the words of the search query, compute, for each of the plurality of intention terms, a compatibility score between the intention term and a query context associated with the intention term, determine, from the plurality of intention terms, a primary intention term having a maximum compatibility score among the plurality of intention terms, and generate, based on the primary intention term, a set of intent-based search results in response to the search query, the set of intent-based search results identifying a set of items associated with the primary intention term.

Abstract: A computing system generates a default view of content items associated with a user account. The default view is representative of an underlying hierarchical structure of the content items associated with the user account. The computing system receives a request to transition from the default view to a modified view of the content items. The computing system ranks the content items based on a predicted likelihood of the user interacting with the particular content item. The computing system identifies the subset of content items for the modified view based on the ranking. The computing system generates the modified view based on the identified subset of the content items. The modified view maintains the underlying hierarchical structure of the content items associated with the user account. The computing system provides the modified view to the user associated with the user account for display.

Abstract: Techniques and tools are described for producing time-series data using faceted search based on document creation time. For example, index information can be created from events (e.g., by adding meta-data and indexing the events as documents). In addition, index information can be created that maps document creation time to time ranges. Search queries can then be executed (e.g., comprising ad-hoc filters to filter on the meta-data), and search results can be faceted on the time ranges to produce time-series data. The time-series data can be graphed to display trends of activity (e.g., trends of events based on user activity).

Abstract: An online system may generate numerous search records in response to searches requested by users. The online system may use a specific way to sample the historical search records to reduce biases in sampling. For example, the online system retrieves historical query records associated with an item query engine. The set of historical query records includes a plurality of search phrases. A historical query record is associated with a search phrase and a list of items returned by the item query engine. The online system determines the search frequencies for the search phrases. The online system stratifies the historical query records into a plurality of bins according to the search frequencies of the search phrases. The online system samples the historical query records from the plurality of bins to collect a representative set of historical query records and outputs the representative set of historical query records for rating.

Abstract: A method for discovering causality from data includes acquiring to-be-processed data, and obtaining a covariance matrix of the to-be-processed data; determining a first target column in the covariance matrix, taking the number of columns of the first target column as a first place in a rearrangement sequence, and obtaining a first upper triangular matrix according to the first target column; determining a position of the number of columns of the covariance matrix other than the first target column except the first place in the rearrangement sequence according to the first target column and the first upper triangular matrix, and obtaining an upper triangular matrix in each position determination; obtaining an adjacency matrix according to an upper triangular matrix and a rearrangement sequence obtained in final position determination; and generating directed acyclic graph (DAG) by using the adjacency matrix, and taking the DAG as causality discovery result of the to-be-processed data.

Abstract: Data is processed in a distributed computing environment with at least one server and a plurality of clients comprising at least a first client and a second client. The first client sends a first request to the server to obtain result data, receives raw data from the server as a response to the first request, processes the raw data to obtain the result data and stores the result data, and sends the result data to the second client in response to receiving a third request to obtain the result data from the second client.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a system may include an atomized workflow loader configured to receive an atomized dataset to load into a data store, and to determine resource requirements data to describe at least one resource requirement. The atomized workflow loader may be further configured to select a data store type based on a resource requirement, and perform a load operation of the atomized dataset as a function of the data store type.

Abstract: Intelligent query routing may be performed across shards of a scalable database table. A router of a database system may receive an access request directed to one or more database tables. The router may evaluate the access request with respect to metadata obtained for the database tables to determine an assignment distribution of computing resources of the database system to data that can satisfy the access request. The router can select planning locations to perform the access request based on the assignment distribution of the computing resources. The router can cause the access request to be performed according to planning at the selected planning locations.

Abstract: The disclosure includes methods and systems that perform operations of identifying a behavior of a metric, where the metric is associated with a node of included within a nodal graph displayed on a graphical user interface. Additionally, a root cause of the behavior is determined through automated, computerized analytics, which may include execution of a search query associated with the node, and a notification of the root cause may be provided via the graphical user interface. Additionally, the graphical user interface may be configured to receive user input that results in the generation of a nodal graph, where the user input includes placement of nodes on a display screen and edges representing a connection between two nodes, where the edges may represent a dependency between the nodes.

Abstract: In one embodiment, a method includes, by one or more computing devices, receiving, from a client system of a first user of an online social network, a text post inputted by the first user, parsing the text post to identify a query associated with the text post, sending, to the client system, instructions for presenting a confirmation prompt requesting confirmation of the identified query from the first user, receiving, from the client system, a confirmation of the identified query from the first user, generating, in response to receiving the confirmation, a recommendation list responsive to the query, wherein the recommendation list comprises references to one or more objects referenced in one or more prior comments associated with one or more prior posts of the online social network associated with the query, and sending, to the client system, instructions for presenting the recommendation list to the first user.

Abstract: 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.

Abstract: A data manager receives a first data layout from a data source and classifies the first data layout as corresponding to a first data domain. The data manager compares the first data layout with one or more existing data layouts that are already classified as corresponding to the first data domain and detects that at least one attribute and corresponding dataset of the first data layout matches with a second attribute and corresponding second dataset from an existing data layout. Data manager generates a second data layout corresponding to the first data layout, wherein the second data layout is a copy of the first data layout with the at least one attribute and the corresponding dataset from the first data layout replaced by the second attribute and the second dataset from the first existing data layout. Data manager loads a data warehouse from the second data layout.

Abstract: Techniques are described with respect to processing a federated query. An associated computer-implemented method includes compiling a query received from a client computing system to generate a query statement and a query access plan. The query access plan incorporates a modified database access application programming interface (API) that supports data serialization. The method further includes executing the query access plan to transmit the query statement to a remote database system. The method further includes fetching a query result set from the remote database system including serialized binary large object (BLOB) data. The method further includes deserializing the serialized BLOB data of the query result set and populating an in-memory data structure with deserialized query results. In an embodiment, the method further includes transmitting the deserialized query results to the client computing system.

Abstract: An embodiment for analyzing and tracking data flow to determine proper schemas for unstructured data. The embodiment may automatically use a sidecar to collect schema discovery rules during conversion of raw data to unstructured data. The embodiment may automatically generate multiple schemas for different tenants using the collected schema discovery rules. The embodiment may automatically use ETL to export unstructured data to SQL databases with the generated multiple schemas for the different tenants. The embodiment may automatically monitor usage data of the SQL databases and collect the usage data. The embodiment may automatically optimize schema discovery using the collected usage data. The embodiment may automatically discover schemas with hot usage and apply the discovered schemas with hot usage to other tenants for consumption and further monitoring.

Abstract: A computer-readable non-transitory physical storage medium having stored thereon machine-executable code for electronically facilitating contact between mutually interested entities, said machine-executable code to be executed by a microprocessor, said machine executable code which when executed by said microprocessor causes the microprocessor to perform operations including suggesting to a first user other users that first user may be interested in, where the suggested other users are filtered based on their location, causing a device to display a graphical user interface (GUI) for the first user to input a rating of the first user's level of interest in one or more respects in at least one other user, accepting the first user's level of interest rating via the GUI while not displaying the first user's rating to the at least one other user, and electronically notifying a pair of users that have rated each other above a threshold level.

Abstract: Systems and methods are provided for collecting and sharing digital experience information. A system for collecting and distributing digital experience information may comprise a digital experience application that may be configured to host a plurality of micro-applications, a first micro-application being able to be configured to detect application events and application states; a connector that may be configured to receive information corresponding to detected application events and application states and belonging to a category; an event backbone that may be configured to route the information received by the connector based on the category; a database that may be configured to store the received information; wherein the event backbone may be further configured to send information to the connector from the event backbone and the database based on one or more criteria; and wherein a second micro-application may be configured to receive information belonging to the category from the connector.

Abstract: The present disclosure relates to blockchain-based data processing methods and devices to achieve balance between a service need and system resource consumption. In one example method, an amount of service data processed by consensus in a blockchain in a specified time period is monitored. A determination is made as to whether the monitored amount of processed service data in the specified time period is less than a specified first threshold or more than a specified second threshold. In response to determining that the monitored amount of processed service data in the specified time period is less than the specified first threshold or more than the specified second threshold, a block generation time for the blockchain is dynamically adjusted. A new block in the blockchain is then dynamically adjusted based on the adjusted block generation time.

Abstract: Systems and methods include detection of changes to data of a plurality of source objects of a source system, replicating the data changes to corresponding ones of the plurality of target objects, and, during the detection of changes to data and the replication of the data changes: detecting a first change to a first source object, identifying a first maintenance event based on the detected first change; determining a first one or more solutions to resolve the first maintenance event; presenting the first maintenance event and the first one or more solutions to resolve the first maintenance event to a user; receiving an indication from the user of a first solution of the first one or more solutions to resolve the first maintenance event; and, in response to the indication, executing the first solution.

Abstract: An employee data replication system receives a request to replicate employee data hosted by a host system. At least one of: a live date corresponding to when the employee data is to be live on the enterprise system or a selection of one or more applications to be used on the enterprise system is identified. A cutoff date for the employee data is calculated based on one or more of the live date and the selection of one or more applications, the cutoff date indicating an oldest date for which the employee data is to be replicated to the enterprise system. Employee data is replicated from the host system to the enterprise system based on the cutoff date, and an indication is provided that the replication has completed.

Abstract: Disclosed are a method and system for propagating data changes in a hierarchy of dataset models in which each dataset model comprises an analytic and one or more parent datasets, including a primordial dataset. The analytic is executed to instantiate a first instance of the data model. After a change in a primordial dataset, each instance of a dataset model that descends from the primordial dataset is invalidated, and the analytic is re-executed to create a second instance of the data model. Analytical results may be displayed. The first dataset model may include a metric in which the definition of the metric comprises metadata of the dataset model. Metric values may be stored in a first cache, re-computed on a new instance of the dataset model, and stored in a second cache.