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How Will The Cloud Impact Data Warehousing Technologies?

Smart Data Collective

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale. The post How Will The Cloud Impact Data Warehousing Technologies?

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What is Data Pipeline? A Detailed Explanation

Smart Data Collective

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

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The Ultimate Guide to Data Warehouse Automation and Tools

Insight Software

This puts tremendous stress on the teams managing data warehouses, and they struggle to keep up with the demand for increasingly advanced analytic requests. To gather and clean data from all internal systems and gain the business insights needed to make smarter decisions, businesses need to invest in data warehouse automation.

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What Are OLAP (Online Analytical Processing) Tools?

Smart Data Collective

Online Analytical Processing (OLAP) is a term that refers to the process of analyzing data online. Data processing and analysis are usually done with a simple spreadsheet, which has data values organized in a row and column structure. The data is processed and modified after it has been extracted.

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5 Best Practices for Extracting, Analyzing, and Visualizing Data

Smart Data Collective

Five Best Practices for Data Analytics. Extracted data must be saved someplace. There are several choices to consider, each with its own set of advantages and disadvantages: Data warehouses are used to store data that has been processed for a specific function from one or more sources. Select a Storage Platform.

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The Best Data Management Tools For Small Businesses

Smart Data Collective

What is data management? Data management can be defined in many ways. Usually the term refers to the practices, techniques and tools that allow access and delivery through different fields and data structures in an organisation. Data transformation. Data analytics and visualisation.

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Article: A Reference Architecture for Fine-Grained Access Management on the Cloud

InfoQ Articles

In this article, we will define a new reference architecture for cloud-native companies that are looking for a simplified access management solution for their cloud resources, from SSH hosts, databases, data warehouses, to message pipelines and cloud storage endpoints. By Manav Mital.