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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

In at least one way, it was not different, and that was in the continued development of innovations that are inspired by data. This steady march of data-driven innovation has been a consistent characteristic of each year for at least the past decade.

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The unreasonable importance of data preparation

O'Reilly on Data

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. Why is high-quality and accessible data foundational?

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The road to Software 2.0

O'Reilly on Data

Nor are building data pipelines and deploying ML systems well understood. That doesn’t mean we aren’t seeing tools to automate various aspects of software engineering and data science. Those tools are starting to appear, particularly for building deep learning models. and Matroid. and Matroid.

Software 329
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Comprehensive data management for AI: The next-gen data management engine that will drive AI to new heights

CIO Business Intelligence

All industries and modern applications are undergoing rapid transformation powered by advances in accelerated computing, deep learning, and artificial intelligence. The next phase of this transformation requires an intelligent data infrastructure that can bring AI closer to enterprise data.

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Solving the Data Daze – Analytics at the Speed of Business Questions

Rocket-Powered Data Science

Data is more than just another digital asset of the modern enterprise. So, what happens when the data flows are not quarterly, or monthly, or even daily, but streaming in real-time? Well, it soon became clear that the real problem was the reverse: how can we have our business move at the speed of our data?

Analytics 167
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5 Current Trends in Big Data for 2022 and Beyond

Smart Data Collective

The world of big data is constantly changing and evolving, and 2021 is no different. As we look ahead to 2022, there are four key trends that organizations should be aware of when it comes to big data: cloud computing, artificial intelligence, automated streaming analytics, and edge computing. Advancements in data storage techniques.

Big Data 145
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What you need to know about product management for AI

O'Reilly on Data

A PM for AI needs to do everything a traditional PM does, but they also need an operational understanding of machine learning software development along with a realistic view of its capabilities and limitations. AI products are automated systems that collect and learn from data to make user-facing decisions.