Remove Cost-Benefit Remove Dashboards Remove OLAP Remove Statistics
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How to Build a Performant Data Warehouse in Redshift

Sisense

OLTP vs OLAP. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing). An OLAP database is best for situations where you read from the database more often than you write to it. OLAP databases excel at queries that require large table scans (e.g.

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What Is Embedded Analytics?

Jet Global

These benefits provide a 360-degree feedback loop. In this new era, users expect to reap the benefits of analytics in every application that they touch. Their dashboards were visually stunning. In turn, end users were thrilled with the bells and whistles of charts, graphs, and dashboards. The market has since evolved.

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Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT

AWS Big Data

The decoupled compute and storage architecture of Amazon Redshift enables you to build highly scalable, resilient, and cost-effective workloads. You don’t need to worry about workloads such as ETL (extract, transform, and load), dashboards, ad-hoc queries, and so on interfering with each other. You can also run predictions using SQL.

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Enterprise Reporting: The 2020’s Comprehensive Guide

FineReport

Data analysis is mainly about extracting data from the data warehouse and analyzing it with the analysis methods such as query, OLAP, data mining, and data visualization to form the data conclusion. FineReport provides three reporting modes: general report, aggregation report, and dashboard. FineReport Architecture. From FineReport.

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What is business intelligence? Transforming data into business insights

CIO Business Intelligence

BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business. Benefits of BI BI helps business decision-makers get the information they need to make informed decisions.

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

Presto’s cost-based query optimizer, dynamic filtering and extensibility through user-defined functions make it a versatile tool in Uber’s analytics arsenal. The cost and constraints of traditional analytics soon reached their limit, forcing Uber to look elsewhere for a solution.

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