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Biggest Trends in Data Visualization Taking Shape in 2022

Smart Data Collective

There are countless examples of big data transforming many different industries. It can be used for something as visual as reducing traffic jams, to personalizing products and services, to improving the experience in multiplayer video games. We would like to talk about data visualization and its role in the big data movement.

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5 Best Practices for Extracting, Analyzing, and Visualizing Data

Smart Data Collective

However, computerization in the digital age creates massive volumes of data, which has resulted in the formation of several industries, all of which rely on data and its ever-increasing relevance. Data analytics and visualization help with many such use cases. It is the time of big data. Select a Storage Platform.

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Why Game Studios Should Exploit Visual Analytics | BizAcuity

BizAcuity

Inability to get player level data from the operators. It does not make sense for most casino suppliers to opt for integrated data solutions like data warehouses or data lakes which are expensive to build and maintain. Evolution from MS Excel to Visual Reporting. Modern Visual Analytics Tools.

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7 Factors to Consider When Deploying a Modern Data Estate

Dataversity

The abilities of an organization towards capturing, storing, and analyzing data; searching, sharing, transferring, visualizing, querying, and updating data; and meeting compliance and regulations are mandatory for any sustainable organization. For example, most data warehouses […].

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Azure SQL Data Warehouse and Power BI

BI Insight

Without a doubt cloud computing is going to change the future of data analytics and data visualisation very significantly. Microsoft Azure SQL Data Warehouse recently released for public preview. The post Azure SQL Data Warehouse and Power BI appeared first on BI Insight.

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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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Data Warehouse, Data Lake, Data Mart, Data Hub: A Definition of Terms!

ElegantJ BI

In the second of these two articles entitled, ‘Factors and Considerations Involved in Choosing a Data Management Solution’, we discuss the various factors and considerations that a business should include when it is ready to choose a data management solution. Think of a Data Mart as a ‘subject’ or ‘concept’ oriented data repository.