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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

2) MLOps became the expected norm in machine learning and data science projects. MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase.

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A step-by-step guide to setting up a data governance program

IBM Big Data Hub

The primary goal of any data governance program is to deliver against prioritized business objectives and unlock the value of your data across your organization. Realize that a data governance program cannot exist on its own – it must solve business problems and deliver outcomes.

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My top learning and pondering moments at Splunk.conf22

Rocket-Powered Data Science

Observability is a business strategy: what you monitor, why you monitor it, what you intend to learn from it, how it will be used, and how it will contribute to business objectives and mission success. The key difference is this: monitoring is what you do, and observability is why you do it.

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Which workloads are best suited for cloud vs. on-premises or edge?

CIO Business Intelligence

Enterprises driving toward data-first modernization need to determine the optimal multicloud strategy, starting with which applications and data are best suited to migrate to cloud and what should remain in the core and at the edge. A hybrid approach is clearly established as the optimal operating model of choice.

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Which Workloads Belong On-Premises as Part of Hybrid IT

CIO Business Intelligence

Enterprises driving toward data-first modernization need to determine the optimal multicloud strategy, starting with which applications and data are best suited to migrate to cloud and what should remain in the core and at the edge. A hybrid approach is clearly established as the optimal operating model of choice.

IT 83
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Bringing an AI Product to Market

O'Reilly on Data

You must detect when the model has become stale, and retrain it as necessary. The Marketing team built the first model, but because it was from marketing, the model optimized for CTR and lead conversion. Data Exploration and Experimentation. Modeling and Evaluation.

Marketing 361
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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.