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Skills and Tools Every Data Engineer Needs to Tackle Big Data

Sisense

As a company that touts the benefits of a full end-to-end BI solution, we certainly know the value of a data engineer. The data engineer’s job is to extract, clean, and normalize data, clearing the path for data scientists to explore that data and build models. Python and R.

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Best Practice of Using Data Science Competitions Skills to Improve Business Value

DataRobot Blog

Of course, finding a compromise is necessary to a certain degree, but rather than simply compromising, finding the optimal solution within that trade-off is the key to creating maximum business value. As a DataRobot data scientist , I have worked with team members on a variety of projects to improve the business value of our customers.

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Data Engineer vs Data Scientist: What’s the Right Fit for Your Company?

Sisense

That means there’s one Hell of a lot of data running through your organization. Capture it all, analyze it precisely, and interpret it right, and you’ve got a precious resource that could really build your business. So, given the choice, which analytics job title should you choose: A data engineer or a data scientist?

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Smart Factories: Artificial Intelligence and Automation for Reduced OPEX in Manufacturing

DataRobot Blog

These initiatives utilize interconnected devices and automated machines that create a hyperbolic increase in data volumes. This type of growth has stressed legacy data management systems and makes it nearly impossible to implement a profitable data-centered solution. Time-Series Forecasting?—? Factory Monitoring?—?

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Top 10 blog posts to help you transition to data engineering

Insight

The industry demand for Data Engineers is constantly on the rise, and with it more and more software engineers and recent graduates try to enter the field. The biggest hurdle for newcomers lies in understanding the Data Engineering landscape and getting hands-on experience with relevant frameworks.

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5 key areas for tech leaders to watch in 2020

O'Reilly on Data

It’s also the data source for our annual usage study, which examines the most-used topics and the top search terms. [1]. Current signals from usage on the O’Reilly online learning platform reveal: Python is preeminent. Within the data topic, however, ML+AI has gone from 22% of all usage to 26%. Security is surging.

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Data Observability and Monitoring with DataOps

DataKitchen

Data errors impact decision-making. Data errors infringe on work-life balance. Data errors also affect careers. If you have been in the data profession for any length of time, you probably know what it means to face a mob of stakeholders who are angry about inaccurate or late analytics.

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