Remove 2022 Remove Metadata Remove Optimization Remove Unstructured Data
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Optimize data layout by bucketing with Amazon Athena and AWS Glue to accelerate downstream queries

AWS Big Data

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

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What is a data architect? Skills, salaries, and how to become a data framework master

CIO Business Intelligence

According to Dataversity , good data architects have a solid understanding of the cloud, databases, and the applications and programs used by those databases. They understand data modeling, including conceptualization and database optimization, and demonstrate a commitment to continuing education. Are data architects in demand?

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Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

Data Lake 117
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Backtesting index rebalancing arbitrage with Amazon EMR and Apache Iceberg

AWS Big Data

Backtesting is a process used in quantitative finance to evaluate trading strategies using historical data. This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance.

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Choosing an open table format for your transactional data lake on AWS

AWS Big Data

Despite these capabilities, data lakes are not databases, and object storage does not provide support for ACID processing semantics, which you may require to effectively optimize and manage your data at scale across hundreds or thousands of users using a multitude of different technologies.

Data Lake 113
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The Modern Data Lakehouse: An Architectural Innovation

Cloudera

Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. Imagine independently discovering rich new business insights from both structured and unstructured data working together, without having to beg for data sets to be made available.

Metadata 102
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Better Analytics Through AI: Our Take on Gartner’s AI Trends

Sisense

Gartner: “Within the current pandemic context, AI techniques such as machine learning (ML), optimization and natural language processing (NLP) are providing vital insights and predictions about the spread of the virus and the effectiveness and impact of countermeasures. Trend 5: Augmented data management. Trend 6: Cloud is a given.

Analytics 112