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In computing, a pipeline or data pipeline [1] is a set of data processing elements connected in series, where the output of one element is the input of the next one. The elements of a pipeline are often executed in parallel or in time-sliced fashion. Some amount of buffer storage is often inserted between elements. Computer-related pipelines ...
The two view outputs may be joined before presentation. The rise of lambda architecture is correlated with the growth of big data, real-time analytics, and the drive to mitigate the latencies of map-reduce. [1] Lambda architecture depends on a data model with an append-only, immutable data source that serves as a system of record.
The architecture for the analytics pipeline shall also consider where to cleanse and enrich data [10] as well as how to conform dimensions. [1] Some of the benefits of an ELT process include speed and the ability to more easily handle both unstructured and structured data.
[1] [2] Since the data is not processed on entry to the data lake, the query and schema do not need to be defined a priori (although often the schema will be available during load since many data sources are extracts from databases or similar structured data systems and hence have an associated schema). ELT is a data pipeline model. [3] [4]
In computing, multiple instruction, single data (MISD) is a type of parallel computing architecture where many functional units perform different operations on the same data. Pipeline architectures belong to this type, though a purist might say that the data is different after processing by each stage in the pipeline.
Azure Data Explorer can ingest 200 MB per second per node. [14] Data Ingestion methods are pipelines and connectors to common services like Azure Event Grid or Azure Event Hub, [21] or programmatic ingestion using SDKs. Data visualization can be achieved using their native dashboard offering, or with tools like Power BI [21] [22] or Grafana ...
In software engineering, a pipeline consists of a chain of processing elements (processes, threads, coroutines, functions, etc.), arranged so that the output of each element is the input of the next. The concept is analogous to a physical pipeline .
Progress DataDirect Hybrid Data Pipeline [36] can expose any cloud, big data or relational data sources as OData end points; Socrata exposes an OData API. Microsoft Azure exposes an OData API. Oracle Analytics Cloud can connect to an OData API; SAP NetWeaver Gateway [37] provides OData access to SAP Business Suite and SAP Business Warehouse.