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Fundamentals of Python Programming for Beginners

Analytics Vidhya

Until the release of NumPy in 2005, Python was considered slow for numeric analysis. Pandas, in 2008, made Python the best language […] The post Fundamentals of Python Programming for Beginners appeared first on Analytics Vidhya. But Numpy changed that.

Analytics 285
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Revolutionising Businesses through AI with Khalifeh Al Jadda

Analytics Vidhya

Before “data science” glimmered, Khalifeh Al Jadda was wrangling web clusters in 2005. But this […] The post Revolutionising Businesses through AI with Khalifeh Al Jadda appeared first on Analytics Vidhya.

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How Data Analytics Is Revolutionizing The Future Of eCommerce In 2020

Smart Data Collective

Data analytics is revolutionizing the future of ecommerce. A growing number of ecommerce platforms have expressed the benefits of data analytics technology and incorporated them into their solutions. Otherwise, you might as well have a circa 2005 static website. How much of a role will big data play in ecommerce?

B2B 135
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Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Apache Iceberg integration is supported by AWS analytics services including Amazon EMR , Amazon Athena , and AWS Glue. Starting with Amazon EMR version 6.5.0,

Data Lake 127
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Announcing the DataOps Cookbook, Third Edition

DataKitchen

They have built data and analytic systems with great hope of success. As an industry, we have a conceptual hole in how we think about data analytic systems. We had the same problem starting in 2005 when we left software development and started to lead data teams. In many ways, they all have the same problems.

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Rethinking ‘Big Data’ — and the rift between business and data ops

CIO Business Intelligence

Still, CIOs should not be too quick to consign the technologies and techniques touted during the honeymoon period (circa 2005-2015) of the Big Data Era to the dust bin of history. Evidently there is value associated with merely inserting data and analytic ambitions into the multiple strategy-making processes at work in any given enterprise.

Big Data 131
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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

Organizations with legacy, on-premises, near-real-time analytics solutions typically rely on self-managed relational databases as their data store for analytics workloads. Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities.