Remove AI Remove Data Models Remove ETL
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Remote Data Science Jobs: 5 High-Demand Roles for Career Growth

Data Science Dojo

Research Data Scientist Description : Research Data Scientists are responsible for creating and testing experimental models and algorithms. According to Google AI, they work on projects that may not have immediate commercial applications but push the boundaries of AI research.

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TigerEye (YC S22) Is Hiring a Full Stack Engineer

Hacker News

About the Role TigerEye is an AI Analyst for everyone in go-to-market. We track the changes in a company’s business to deliver instant, accurate answers to complex questions through a simple app.

professionals

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How AI and ML Can Transform Data Integration

Smart Data Collective

The upsurge of data (with the introduction of non-traditional data sources like streaming data, machine logs, etc.) along with traditional ones challenge old models of data integration. Why is Data Integration a Challenge for Enterprises? How Can AI Transform Data Integration?

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Top ETL Tools: Unveiling the Best Solutions for Data Integration

Pickl AI

Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Choosing the right ETL tool is crucial for smooth data management.

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How Rocket Companies modernized their data science solution on AWS

AWS Machine Learning Blog

With the current housing shortage and affordability concerns, Rocket simplifies the homeownership process through an intuitive and AI-driven experience. Apache Hive was used to provide a tabular interface to data stored in HDFS, and to integrate with Apache Spark SQL. HBase is employed to offer real-time key-based access to data.

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What Are the Best Data Modeling Methodologies & Processes for My Data Lake?

phData

However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. Data modeling plays a pivotal role in defining the structure, relationships, and semantics of data within a data lake. Consistency of data throughout the data lake.

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Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

Key features of cloud analytics solutions include: Data models , Processing applications, and Analytics models. Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence.

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