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Big Data Skill sets that Software Developers will Need in 2020

Smart Data Collective

From the tech industry to retail and finance, big data is encompassing the world as we know it. More organizations rely on big data to help with decision making and to analyze and explore future trends. Big Data Skillsets. They’re looking to hire experienced data analysts, data scientists and data engineers.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with big data platforms such as Hadoop or Apache Spark. Prescriptive analytics: Prescriptive analytics predicts likely outcomes and makes decision recommendations.

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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

Accompanying the massive growth in sensor data (from ubiquitous IoT devices, including location-based and time-based streaming data), there have emerged some special analytics products that are growing in significance, especially in the context of innovation and insights discovery from on-prem enterprise data sources.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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Build an analytics pipeline that is resilient to schema changes using Amazon Redshift Spectrum

AWS Big Data

Conclusion With the emergence of requirements for predictive and prescriptive analytics based on big data, there is a growing demand for data solutions that integrate data from multiple heterogeneous data models with minimal effort.

IoT 94
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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

The following figure shows some of the metrics derived from the study. Strategize based on how your teams explore data, run analyses, wrangle data for downstream requirements, and visualize data at different levels. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics.

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A Guide to Data Analytics in the Travel Industry

Alation

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? How is data analytics used in the travel industry?