Remove Clustering Remove Data Governance Remove Data Warehouse
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Data lakes vs. data warehouses: Decoding the data storage debate

Data Science Dojo

When it comes to data, there are two main types: data lakes and data warehouses. What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications. Hadoop systems and data lakes are frequently mentioned together.

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Data Integrity for AI: What’s Old is New Again

Precisely

The goal of this post is to understand how data integrity best practices have been embraced time and time again, no matter the technology underpinning. In the beginning, there was a data warehouse The data warehouse (DW) was an approach to data architecture and structured data management that really hit its stride in the early 1990s.

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Essential data engineering tools for 2023: Empowering for management and analysis

Data Science Dojo

Data engineering tools offer a range of features and functionalities, including data integration, data transformation, data quality management, workflow orchestration, and data visualization. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

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What is a Hadoop Cluster?

Pickl AI

Summary: A Hadoop cluster is a collection of interconnected nodes that work together to store and process large datasets using the Hadoop framework. It utilises the Hadoop Distributed File System (HDFS) and MapReduce for efficient data management, enabling organisations to perform big data analytics and gain valuable insights from their data.

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What is the Snowflake Data Cloud and How Much Does it Cost?

phData

What Components Make up the Snowflake Data Cloud? The main goal of a data mesh structure is to drive: Domain-driven ownership Data as a product Self-service infrastructure Federated governance One of the primary challenges that organizations face is data governance. What is a Cloud Data Warehouse?

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Why Snowflake is the Ideal Platform for Data Vault Modeling

phData

In today’s world, data-driven applications demand more flexibility, scalability, and auditability, which traditional data warehouses and modeling approaches lack. This is where the Snowflake Data Cloud and data vault modeling comes in handy. What is Data Vault Modeling?

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How to modernize data lakes with a data lakehouse architecture

IBM Journey to AI blog

It gained rapid popularity given its support for data transformations, streaming and SQL. But it never co-existed amicably within existing data lake environments. As a result, it often led to additional dedicated compute clusters just to be able to run Spark. Data governance remains an unexplored frontier for this technology.