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Top 14 Must-Read Data Science Books You Need On Your Desk

datapine

Big data is at the foundation of all the megatrends that are happening.” – Chris Lynch, big data expert. We live in a world saturated with data. Zettabytes of data are floating around in our digital universe, just waiting to be analyzed and explored, according to AnalyticsWeek. At present, around 2.7

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Alternative Cloud Hosted Data Science Environments

KDnuggets

Over the years new alternative providers have risen to provided a solitary data science environment hosted on the cloud for data scientist to analyze, host and share their work.

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The DataOps Vendor Landscape, 2021

DataKitchen

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix.

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10 Big Data Examples Showing The Great Value of Smart Analytics In Real Life At Restaurants, Bars, and Casinos

datapine

“You can have data without information, but you cannot have information without data.” – Daniel Keys Moran. When you think of big data, you usually think of applications related to banking, healthcare analytics , or manufacturing. However, the usage of data analytics isn’t limited to only these fields. Discover 10.

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Deciphering The Seldom Discussed Differences Between Data Mining and Data Science

Smart Data Collective

Unfortunately, despite the growing interest in big data careers, many people don’t know how to pursue them properly. You should learn what a big data career looks like , which involves knowing the differences between different data processes. What is Data Science? Where to Use Data Science?

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Top Benefits of Using Docker for Data Science

Smart Data Collective

If you are a Data Scientist or Big Data Engineer, you probably find the Data Science environment configuration painful. If this is your case, you should consider using Docker for your day-to-day Data tasks. In this post, we will see how Docker can create a meaningful impact in your Data Science project.

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The future of data: A 5-pillar approach to modern data management

CIO Business Intelligence

The proposed model illustrates the data management practice through five functional pillars: Data platform; data engineering; analytics and reporting; data science and AI; and data governance. The higher the criticality and sensitivity to data downtime, the more engineering and automation are needed.