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A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a datalake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and datalakes can coexist in an organization, complementing each other.
Amazon Redshift is a recommended service for onlineanalyticalprocessing (OLAP) workloads such as cloud data warehouses, data marts, and other analyticaldata stores.
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.
This includes the ETL processes that capture source data, the functional refinement and creation of data products, the aggregation for business metrics, and the consumption from analytics, businessintelligence (BI), and ML. Vijay Bagur is a Sr. Technical Account Manager.
Onlineanalyticalprocessing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. IBM watsonx.data is the next generation OLAP system that can help you make the most of your data.
Microsoft’s launch of the Power BI platform several years ago marked the company’s entrance into an important space within the business applications market. As the Microsoft Dynamics ERP products transition to a cloud-first model, Microsoft has positioned Power BI as the future of businessintelligence for its Dynamics family of products.
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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