Remove Data Analytics Remove Data Lake Remove Online Analytical Processing
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Build a real-time analytics solution with Apache Pinot on AWS

AWS Big Data

Online Analytical Processing (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.

OLAP 99
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TIBCO JasperSoft for BI and Reporting

BizAcuity

TIBCO Jaspersoft offers a complete BI suite that includes reporting, online analytical processing (OLAP), visual analytics , and data integration. The web-scale platform enables users to share interactive dashboards and data from a single page with individuals across the enterprise. Data Security.

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Unlock scalability, cost-efficiency, and faster insights with large-scale data migration to Amazon Redshift

AWS Big Data

The data warehouse is highly business critical with minimal allowable downtime. We can determine the following are needed: An open data format ingestion architecture processing the source dataset and refining the data in the S3 data lake. We hope this post provides you with valuable guidance.

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How OLAP and AI can enable better business

IBM Big Data Hub

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. These advancements further enhanced the performance and scalability of OLAP systems.

OLAP 57
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Master Your Power BI Environment with Tabular Models

Jet Global

Most organizations are looking for sophisticated reporting and analytics, but they have little appetite for managing the highly complicated infrastructure that goes with it. Let’s begin with an overview of how data analytics works for most business applications. This leads to the second option, which is a data warehouse.

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

Presto was able to achieve this level of scalability by completely separating analytical compute from data storage. Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes.

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Deploy real-time analytics with StarTree for managed Apache Pinot on AWS

AWS Big Data

Like Pinot, StarTree addresses the need for a low-latency, high-concurrency, real-time online analytical processing (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.