Remove Cost-Benefit Remove Interactive Remove OLAP
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Closing the breach window, from data to action

IBM Big Data Hub

The average cost of a data breach set a new record in 2023 of USD 4.45 Legacy systems and architectures led to unsustainable costs of data ingestion, analysis, and storage, as well as performance issues when searching and analyzing threats across massive datasets.

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

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. The cost and constraints of traditional analytics soon reached their limit, forcing Uber to look elsewhere for a solution.

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The Future of AI in the Enterprise

Jet Global

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

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Goodbye Oracle Discoverer, Hello Next-Generation Reporting

Jet Global

Users who transferred from premier to extended support did not have the benefit of being certified with most new third-party products/versions (such as web browsers and Windows 10), or more new Oracle products. Exploring user- and cost-friendly next-generation reporting alternatives. But does OBIEE stack up?

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Build an Amazon Redshift data warehouse using an Amazon DynamoDB single-table design

AWS Big Data

This approach comes with a heavy computational cost in terms of processing and distributing the data across multiple tables while ensuring the system is ACID-compliant at all times, which can negatively impact performance and scalability. This is inefficient from both a cost and performance perspective.

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Enterprise Reporting: The 2020’s Comprehensive Guide

FineReport

It may offer a range of interactivity, so users can find business problems and make data-driven decisions via the reports. 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. Easy to use.

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Data Model Development Using Jinja

Sisense

The data model facilitates interaction among these groups by reformatting and restructuring data in order to define the relationship among datasets. . Data warehouses provide a consolidated, multidimensional view of data along with online analytical processing ( OLAP ) tools. The benefits of DBT with Jinja.