Remove 2011 Remove Data Analytics Remove Data Lake Remove Testing
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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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Accomplish Agile Business Intelligence & Analytics For Your Business

datapine

Therefore, we will walk you through this beginner’s guide on agile business intelligence and analytics to help you understand how they work and the methodology behind them. Your Chance: Want to test an agile business intelligence solution? What Is Agile Analytics And BI? Agile Business Intelligence & Analytics Methodology.

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Unlock The Power of Your Data With These 19 Big Data & Data Analytics Books

datapine

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Essential Big Data And Data Analytics Insights. million searches per day and 1.2

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How The Cloud Made ‘Data-Driven Culture’ Possible | Part 1

BizAcuity

2011: IBM enters the cloud market with IBM SmartCloud. Google launches BigQuery, its own data warehousing tool and Microsoft introduces Azure SQL Data Warehouse and Azure Data Lake Store. AWS rolls out SageMaker, designed to build, train, test and deploy machine learning (ML) models. To be continued.