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Five Strategies to Accelerate Data Product Development

Cloudera

As a result, organizations need to evaluate the long term product portfolio strategy and how the data platform needs to be defined to realize that product vision, enabling modularity and extensibility. . 4- Compose Data Experiences Organized around Value Propositions, Not Intermediate Data Outputs.

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The Role of an AI Data Quality Analyst

Monte Carlo

Let’s dive into the responsibilities, skills, challenges, and potential career paths for an AI Data Quality Analyst today. Table of Contents What Does an AI Data Quality Analyst Do? Handling unstructured data Many AI models are fed large amounts of unstructured data, making data quality management complex.

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ThoughtSpot Moving to the Next Orbit: Welcoming Our New CEO, Ketan Karkhanis

ThoughtSpot

With ThoughtSpot Embedded, we are also rapidly adding tech startups and enterprises in our portfolio as they bring our search and AI-driven analytics capabilities into their SaaS apps and other business applications.

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Hadoop vs Spark: Main Big Data Tools Explained

AltexSoft

Main users of Hive are data analysts who work with structured data stored in the HDFS or HBase. Data management and monitoring options. Among solutions facilitation data management are. RDD easily handles both structured and unstructured data. Netflix for near real-time movie recommendations.

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5 Reasons Why ETL Professionals Should Learn Hadoop

ProjectPro

While the initial era of ETL ignited enough sparks and got everyone to sit up, take notice and applaud its capabilities, its usability in the era of Big Data is increasingly coming under the scanner as the CIOs start taking note of its limitations.

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Difference between Pig and Hive-The Two Key Components of Hadoop Ecosystem

ProjectPro

Generally data to be stored in the database is categorized into 3 types namely Structured Data, Semi Structured Data and Unstructured Data. We generally refer to Unstructured Data as “Big Data” and the framework that is used for processing Big Data is popularly known as Hadoop.

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How JPMorgan uses Hadoop to leverage Big Data Analytics?

ProjectPro

Large commercial banks like JPMorgan have millions of customers but can now operate effectively-thanks to big data analytics leveraged on increasing number of unstructured and structured data sets using the open source framework - Hadoop. JP Morgan has massive amounts of data on what its customers spend and earn.

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