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Now, instead of making a direct call to the underlying database to retrieve information, a report must query a so-called “data entity” instead. Each data entity provides an abstract representation of businessobjects within the database, such as, customers, general ledger accounts, or purchase orders. DataLakes.
This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities. A data hub contains data at multiple levels of granularity and is often not integrated. Data repositories represent the hub.
OnlineAnalyticalProcessing (OLAP) is crucial in modern data-driven apps, acting as an abstraction layer connecting raw data to users for efficient analysis. It organizes data into user-friendly structures, aligning with shared business definitions, ensuring users can analyze data with ease despite changes.
The data warehouse is highly business critical with minimal allowable downtime. A successful migration can be accomplished through proactive planning, continuous monitoring, and performance fine-tuning, thereby aligning with and delivering on businessobjectives. Vijay Bagur is a Sr. Technical Account Manager.
Like Pinot, StarTree addresses the need for a low-latency, high-concurrency, real-time onlineanalyticalprocessing (OLAP) solution. In addition, StarTree offers a managed experience for real-time and batch Pinot workloads, offering enhanced security, automated data ingestion, tiered storage, and off-heap upserts.
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