Remove Customer Analytics Remove Data Lake Remove Machine Learning Remove Structured Data
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Building Robust Data Pipelines: 9 Fundamentals and Best Practices to Follow

Alation

Data is a valuable resource, especially in the world of business. A McKinsey survey found that companies that use customer analytics intensively are 19 times higher to achieve above-average profitability. But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines.

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Building Robust Data Pipelines: 9 Fundamentals and Best Practices to Follow

Alation

Data is a valuable resource, especially in the world of business. A McKinsey survey found that companies that use customer analytics intensively are 19 times higher to achieve above-average profitability. But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines.

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

AWS Big Data

This can be achieved using AWS Entity Resolution , which enables using rules and machine learning (ML) techniques to match records and resolve identities. Alternatively, you can build identity graphs using Amazon Neptune for a single unified view of your customers.

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Doing a 180 on Customer 360 – The Preferred Path to Customer Insights

Cloudera

The abundant growth of data, maturation of machine algorithms, and future regulatory compliance demands from the European Union’s General Data Protection Regulation (GDPR) will shift the landscape for creating a single source of the truth for customer data. Learn More.