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Big data engineer

Dataconomy

Data collection and storage These engineers design frameworks to collect data from diverse sources and store it in systems like data warehouses and data lakes, ensuring efficient data retrieval and processing.

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Top Big Data Tools Every Data Professional Should Know

Pickl AI

Introduction to Big Data Tools In todays data-driven world, organisations are inundated with vast amounts of information generated from various sources, including social media, IoT devices, transactions, and more. Big Data tools are essential for effectively managing and analysing this wealth of information. Use Cases : Yahoo!

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What is a Hadoop Cluster?

Pickl AI

Machine Learning and Predictive Analytics Hadoop’s distributed processing capabilities make it ideal for training Machine Learning models and running predictive analytics algorithms on large datasets. Software Installation Install the necessary software, including the operating system, Java, and the Hadoop distribution (e.g.,

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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

Collaborating with data scientists, to ensure optimal model performance in real-world applications. With expertise in Python, machine learning algorithms, and cloud platforms, machine learning engineers optimize models for efficiency, scalability, and maintenance. Data Warehousing: Amazon Redshift, Google BigQuery, etc.