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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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What is a data scientist? A key data analytics role and a lucrative career

CIO Business Intelligence

Data scientists are analytical data experts who use data science to discover insights from massive amounts of structured and unstructured data to help shape or meet specific business needs and goals. Data scientist salary. Semi-structured data falls between the two.

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Learn how to get insights from Azure SQL Database: A sample data analytics project using Global Peace Index data

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. The post Learn how to get insights from Azure SQL Database: A sample data analytics project using Global Peace Index data appeared first on Analytics Vidhya.

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9 most useful functions for PySpark DataFrame

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Spark is a data analytics engine that is mainly used for. The post 9 most useful functions for PySpark DataFrame appeared first on Analytics Vidhya.

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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Both data warehouses and data lakes are used when storing big data. Many people are confused about these two, but the only similarity between them is the high-level principle of data storing. Data Warehouse.

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11 dark secrets of data management

CIO Business Intelligence

Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.

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How Will The Cloud Impact Data Warehousing Technologies?

Smart Data Collective

Data warehouse, also known as a decision support database, refers to a central repository, which holds information derived from one or more data sources, such as transactional systems and relational databases. The data collected in the system may in the form of unstructured, semi-structured, or structured data.