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Data architecture strategy for data quality

IBM Big Data Hub

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

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Enhance data security and governance for Amazon Redshift Spectrum with VPC endpoints

AWS Big Data

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3).

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How FanDuel adopted a modern Amazon Redshift architecture to serve critical business workloads

AWS Big Data

More and more of FanDuel’s community of analysts and business users looked for comprehensive data solutions that centralized the data across the various arms of their business. Their individual, product-specific, and often on-premises data warehouses soon became obsolete.

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Eating the Elephant of Data Strategy

Paul Blogs on BI

If the data is not correct then its garbage in and garbage out, or as I have always said : BIG DATA + BAD DATA = BIG BAD DATA However, when it comes to a good data strategy, it’s not just about the quality of the data, it’s also about the design and functionality of the structure where it is housed.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse. Let’s find out what role each of these components play in the context of C360.

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

AWS Big Data

This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities. Data lakes are more focused around storing and maintaining all the data in an organization in one place.

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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

This could involve anything from learning SQL to buying some textbooks on data warehouses. If you’d like some resources in this area, we have posts on related business intelligence books and business intelligence podcasts you can use to start your research. Business Intelligence Job Roles.