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Here’s Why Automation For Data Lakes Could Be Important

Smart Data Collective

Data Lakes are among the most complex and sophisticated data storage and processing facilities we have available to us today as human beings. Analytics Magazine notes that data lakes are among the most useful tools that an enterprise may have at its disposal when aiming to compete with competitors via innovation.

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

AWS Big Data

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

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Understanding Data Entities in Microsoft Dynamics 365

Jet Global

In the future, customers will be able to deploy Data Entities and replicate transactional tables in an Azure Data Lake. Jet Analytics provides a pre-built data warehouse , OLAP cubes , and tabular models with a platform for non-technical users to easily create their own reports in Excel or Power BI.

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What is Business Intelligence Consulting

BizAcuity

Data governance and security measures are critical components of data strategy. KPI Analysis: the process of evaluating the performance of an organization using a set of measurable metrics infrastructure: refers to the hardware, software, and other key resources that are used to manage, maintain and analyze data within an organization.

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What is Business Intelligence Consulting

BizAcuity

Data governance and security measures are critical components of data strategy. KPI Analysis: the process of evaluating the performance of an organization using a set of measurable metrics infrastructure: refers to the hardware, software, and other key resources that are used to manage, maintain and analyze data within an organization.

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

Uber understood that digital superiority required the capture of all their transactional data, not just a sampling. They stood up a file-based data lake alongside their analytical database. Because much of the work done on their data lake is exploratory in nature, many users want to execute untested queries on petabytes of data.

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