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Setting up Data Lake on GCP using Cloud Storage and BigQuery

Analytics Vidhya

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

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Unstructured Data: Examples, Tools, Techniques, and Best Practices

AltexSoft

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

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Data Warehouse vs Data Lake vs Data Lakehouse: Definitions, Similarities, and Differences

Monte Carlo

Modern companies are ingesting, storing, transforming, and leveraging more data to drive more decision-making than ever before. At the same time, 81% of IT leaders say their C-suite has mandated no additional spending or a reduction of cloud costs. For metadata organization, they often use Hive, Amazon Glue, or Databricks.

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Top Data Lake Vendors (Quick Reference Guide)

Monte Carlo

By accommodating various data types, reducing preprocessing overhead, and offering scalability, data lakes have become an essential component of modern data platforms , particularly those serving streaming or machine learning use cases. Google Cloud Platform and/or BigLake Google offers a couple options for building data lakes.

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ETL vs. ELT and the Evolution of Data Integration Techniques

Ascend.io

Today, a good part of the job of a data engineer is to move data from one place to another by creating pipelines that can be either ETL vs. ELT. However, with the advent of cloud-based infrastructure, ETL is changing towards ELT. Second, during transformations, data gets reshaped into some specific form.

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Data Warehousing Guide: Fundamentals & Key Concepts

Monte Carlo

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

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Demystifying Modern Data Platforms

Cloudera

A key area of focus for the symposium this year was the design and deployment of modern data platforms. Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. Ramsey International Modern Data Platform Architecture. What is a data mesh?