A data processing method, apparatus, and system, a computer device, a readable storage medium, and a computer program product relate to the field of cloud technologies and a blockchain technology, and the method includes: receiving, by using a transceiver component, collection indicator data sent by an edge cluster; performing pre-aggregation processing on the collection indicator data to obtain pre-aggregated indicator data, and sending the pre-aggregated indicator data to a coordinated write component; converting, by the coordinated write component, the pre-aggregated indicator data into conversion indicator data that has a target storage format, and performing merging processing on the conversion indicator data to obtain storage indicator data; writing the storage indicator data into a database component; and writing, by the database component, the storage indicator data into a storage disk.

A computer-implemented method includes a method comprising using at least one hardware processor to: receive a plurality of data from a plurality of data sources; standardize the plurality of data; tag the standardized plurality of data with one or more companies; train a prediction model to predict a metric for each of the one or more companies based on the standardized plurality of data tagged with that company and historical measurements for that company; and apply the prediction model to new data to predict the metric for at least one of the one or more companies.

Disclosed are a method and apparatus for storing data. The method includes: acquiring data to be stored; converting the data to be stored from an initial data type to a target data type, a data length corresponding to the target data type being less than that corresponding to the initial data type; and storing the data to be stored of the target data type to a database. In the method according to the present disclosure, a storage space occupied by the data to be stored in the database is greatly reduced. In addition, the method according to the present disclosure is performed prior to lossy or lossless data compression storage of the data to be stored in the related art. That is, on the basis of a compression ratio when the data to be stored is stored in the related art, the present disclosure further improves a compression effect of the data to be stored by reducing the data length when the data to be stored is stored, and further saves storage resources of the database.

A record processing and storage system operates by: generating a set of pages from a plurality of row data via a plurality of processing core resources, wherein each processing core resource in the plurality of processing core resources generate a corresponding subset of the set of pages, independently from and in parallel with processing of other subsets of the set of pages via other ones of the plurality of processing core resources; facilitating performance of a single storage transaction to store the set of pages; identifying a page set interval based on a plurality of row number intervals of the set of pages; generating, based on completing the single storage transaction, row durability data indicating a least favorably ordered row number of a plurality of row numbers corresponding to the plurality of row data; and transmitting the row durability data to a computing device associated with the plurality of row data.

Apparatuses, systems, and methods are provided for managing events in a Geographic Information System (GIS). A first event may be detected which is associated with a change made via a mapping interface of the GIS. Information associated with the first event may be cached in a memory of a computing device. A second event associated with committing of the change in a database of the GIS may be detected, and in response to detecting the second event, a new event that is a transformation of the first event stored in the memory, the second event or both may be generated.

Disclosed is an approach that applies a fuzzy logic model that may involve fuzzy-matching a plurality of address fields to determine a common physical address, and determining a number of communiques directed to that address with reference to a threshold that may determine an excessive number of communiques. The plurality of address fields may also be fuzzy-matched to information in a fraud-risk database which may comprise a fraud-risk address. One or more matches may be presented to a user who may adjust the views of the various matches, track various trends within the data, and harmonize the various address fields relating to a physical address.

A format conversion engine for Apache Hadoop that converts data from its original format to a database-like format at certain time points for use by a low latency (LL) query engine. The format conversion engine comprises a daemon that is installed on each data node in a Hadoop cluster. The daemon comprises a scheduler and a converter. The scheduler determines when to perform the format conversion and notifies the converter when the time comes. The converter converts data on the data node from its original format to a database-like format for use by the low latency (LL) query engine.

Methods are provided for semantic processing of data files including detecting formats of data embedded in the data files and converting the data to formats compatible with a data analysis tool. The method may comprise determining if the data file comprises signature characteristics associated with a known data format and, if so, determining a set of data manipulation operations associated with the known data format to convert the data file to a compatible format for the data analysis tool. The method may further comprise semantically analyzing components of the data files to assess formatting across a required set of criterions needed by the data analysis tool and determining sets of data manipulation operations to perform to convert the data file to a compatible format.

A system and method may be provided to predict a value of a field of interest about a patient procedure. Data may be received from a health provider. A statistical model or machine learning model may be built based on the data in order to predict the value of the field of interest. In some embodiments, a plurality of models are used to predict different aspects of the procedure and are combined by a main model.

A method of a data manager for a database management system having a primary database and a staging storage includes receiving a request including identifying information for a set of records that have been sent to the database management system for storage, searching the staging storage for the set of records using the identifying information, and storing the set of records into the primary database prior to a scheduled storage for the set of records based on a general process for ingesting records sent to the database management system for storage in the primary database, in response to the request and to the set of records matching the identifying information.