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What Are OLAP (Online Analytical Processing) Tools?

Smart Data Collective

One of the most valuable tools available is OLAP. This tool can be great for handing SQL queries and other data queries. Every data scientist needs to understand the benefits that this technology offers. Using OLAP Tools Properly. Several or more cubes are used to separate OLAP databases. see more ).

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Complexity Drives Costs: A Look Inside BYOD and Azure Data Lakes

Jet Global

That stands for “bring your own database,” and it refers to a model in which core ERP data are replicated to a separate standalone database used exclusively for reporting. For more powerful, multidimensional OLAP-style reporting, however, it falls short. OLAP reporting has traditionally relied on a data warehouse.

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RDF-Star: Metadata Complexity Simplified

Ontotext

This is a graph of millions of edges and vertices – in enterprise data management terms it is a giant piece of master/reference data. To handle such scenarios you need a transalytical graph database – a database engine that can deal with both frequent updates (OLTP workload) as well as with graph analytics (OLAP).

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What’s the Difference Between Business Intelligence and Business Analytics?

Sisense

BI lets you apply chosen metrics to potentially huge, unstructured datasets, and covers querying, data mining , online analytical processing ( OLAP ), and reporting as well as business performance monitoring, predictive and prescriptive analytics. Business Analytics is One Part of Business Intelligence.

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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. BI analysts use data analytics, data visualization, and data modeling techniques and technologies to identify trends.

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Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT

AWS Big Data

Many customers migrate their data warehousing workloads to Amazon Redshift and benefit from the rich capabilities it offers, such as the following: Amazon Redshift seamlessly integrates with broader data, analytics, and AI or machine learning (ML) services on AWS , enabling you to choose the right tool for the right job.

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Accelerating revenue growth with real-time analytics: Poshmark’s journey

AWS Big Data

Top line revenue refers to the total value of sales of an organization’s services or products. In this post, we share how Poshmark improved CX and accelerated revenue growth by using a real-time analytics solution. The data from the S3 data lake is used for batch processing and analytics through Amazon EMR and Amazon Redshift.