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Delivering Low-latency Analytics Products for Business Success

Rocket-Powered Data Science

I recently saw an informal online survey that asked users what types of data (tabular; text; images; or “other”) are being used in their organization’s analytics applications. The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data.

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

Cloudera

While these types of systems are critical for managing internal operational processes, they are typically not effective for consolidating customer information at the rapid pace of business change. Structured data from operational data stores now provides a small slice of the overall data needed to improve customer experience.

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Six Strategies for Advancing Customer Knowledge: Bringing Data Together

Cloudera

Cloudera and TDWI have recently partnered to outline key attributes to success for implementing customer insight solutions. These are the solutions that help us better capture customer data (across systems and touchpoints), open up that data to advanced analytics, and build data products that deliver insights and actions to customers.

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How Cloudera Data Flow Enables Successful Data Mesh Architectures

Cloudera

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

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