Remove Data Warehouse Remove Events Remove Interactive Remove OLAP
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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

Decision support systems definition A decision support system (DSS) is an interactive information system that analyzes large volumes of data for informing business decisions. A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. DSS software system.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. Data lakes are more focused around storing and maintaining all the data in an organization in one place.

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What Role Does Data Mining Play for Business Intelligence?

Jet Global

Data drives everything in the business world, from manufacturing to supply chain logistics to retail sales to customer experience to post-sale marketing and beyond, data holds the secrets to making processes more efficient, production costs cheaper, profit margins higher and marketing campaigns more effective.

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Why Business Intelligence is Top of Mind for CFOs for 2022

Jet Global

The term “ business intelligence ” (BI) has been in common use for several decades now, referring initially to the OLAP systems that drew largely upon pre-processed information stored in data warehouses. Sales and customer service interactions are tracked in CRM.

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Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT

AWS Big Data

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. Modern analytics is much wider than SQL-based data warehousing. You can get faster insights without spending valuable time managing your data warehouse.

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Closing the breach window, from data to action

IBM Big Data Hub

The list of challenges is long: cloud attack surface sprawl, complex application environments, information overload from disparate tools, noise from false positives and low-risk events, just to name a few. You get near real-time visibility and insights from your ingested data.

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Data Model Development Using Jinja

Sisense

The primary aim when building a model is to transform complex, raw, real-world data into a coherent picture that can be used to answer likely questions from the business. . Designers, engineers, and analysts see data in different ways. Data warehouses have become intensely important in the modern business world.