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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

licensed, 100% open-source data table format that helps simplify data processing on large datasets stored in data lakes. Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time.

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Regeneron turns to IT to accelerate drug discovery

CIO Business Intelligence

When Bob McCowan was promoted to CIO at Regeneron Pharmaceuticals in 2018, he had previously run the data center infrastructure for the $81.5 billion company’s scientific, commercial, and manufacturing businesses since joining the company in 2014. It is all about the data. Much of Regeneron’s data, of course, is confidential.

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

BizAcuity

2012: Amazon Redshift, the first of its kind cloud-based data warehouse service comes into existence. Fact: IBM built the world’s first data warehouse in the 1980’s. 2014: Satya Nadella, who is influential behind Microsoft’s cloud market ventures, becomes the CEO of Microsoft. More on Kubernetes soon.

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Use the Amazon Redshift Data API to interact with Amazon Redshift Serverless

AWS Big Data

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. You can unload data in either text or Parquet format.

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What is going on in the world of data and analytics?

Andrew White

I have blogged before (see this from 2014: A Day in the Life of an Analyst” at Gartner’s IT/Expo Symposium – Day 3 ) about the hot topics I discussed with attendees at our Symposia and data and analytics conferences. This ties into the failure of data governance and MDM (see first item in this list). Age maybe against us.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Most of the data management moved to back-end servers, e.g., databases. So we had three tiers providing a separation of concerns: presentation, logic, data. Note that data warehouse (DW) and business intelligence (BI) practices both emerged circa 1990. in lieu of simply landing in a data lake.