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

AWS Big Data

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

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What Whirlpool’s CIO does to make its digital business models run end to end

CIO Business Intelligence

Brown recently spoke with CIO Leadership Live host Maryfran Johnson about advancing product features via sensor data, accelerating digital twin strategies, reinventing supply chain dynamics and more. On the enterprise data strategy: I am a self-admitted data geek. The two are extremely important.

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Who to Follow in 2019 for Big Data, Data Governance and GDPR Advice

erwin

With this in mind, the erwin team has compiled a list of the most valuable data governance, GDPR and Big data blogs and news sources for data management and data governance best practice advice from around the web. Top 7 Data Governance, GDPR and Big Data Blogs and News Sources from Around the Web. . —

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Public or On-Prem? Telco giants are optimizing the network with the Hybrid Cloud

Cloudera

The hybrid cloud gives organizations the agility they desire, particularly when thinking about the need to process data quickly and efficiently across several different environments. . Telco industry executives Jinsoo Jang of LG Uplus and Patrick de Vries of KPN spoke at a Modern Data Architecture for Telco lunch, hosted by Cloudera.

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Empowering data-driven excellence: How the Bluestone Data Platform embraced data mesh for success

AWS Big Data

Four-layered data lake and data warehouse architecture – The architecture comprises four layers, including the analytical layer, which houses purpose-built facts and dimension datasets that are hosted in Amazon Redshift. This enables data-driven decision-making across the organization.

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How to build a successful AI strategy

IBM Big Data Hub

Determine the tools and support needed and organize them based on what’s most crucial for the project, specifically: Data: Make a data strategy by determining if new or existing data or datasets will be required to effectively fuel the AI solution. Establish a data governance framework to manage data effectively.

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How Amazon Finance Automation built a data mesh to support distributed data ownership and centralize governance

AWS Big Data

In this post, we discuss how the Amazon Finance Automation team used AWS Lake Formation and the AWS Glue Data Catalog to build a data mesh architecture that simplified data governance at scale and provided seamless data access for analytics, AI, and machine learning (ML) use cases.

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