Remove Cloud Remove Data Ingestion Remove ETL Tools Remove Unstructured Data
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Why Modernizing the First Mile of the Data Pipeline Can Accelerate all Analytics

Cloudera

Every enterprise is trying to collect and analyze data to get better insights into their business. Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis.

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Top 10 Azure Data Engineer Job Opportunities in 2024 [Career Options]

Knowledge Hut

Azure Data Engineer Career Demands & Benefits Azure has become one of the most powerful platforms in the industry, where Microsoft offers a variety of data services and analytics tools. As a result, organizations are looking to capitalize on cloud-based data solutions.

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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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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

ELT choice: In data warehouses, Extract and Transform processes usually occur before data is loaded into the warehouse. Many organizations also deploy data marts , which are dedicated storage repositories for specific business lines or workgroups. Unstructured data sources.

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Tips to Build a Robust Data Lake Infrastructure

DareData

We've seen this happen in dozens of our customers: data lakes serve as catalysts that empower analytical capabilities. If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. And what is the reason for that?

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The Good and the Bad of Databricks Lakehouse Platform

AltexSoft

Databricks architecture Databricks provides an ecosystem of tools and services covering the entire analytics process — from data ingestion to training and deploying machine learning models. Besides that, it’s fully compatible with various data ingestion and ETL tools. Delta Lake integrations.

Scala 64
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Apache Spark Use Cases & Applications

Knowledge Hut

Spark is being used in more than 1000 organizations who have built huge clusters for batch processing, stream processing, building warehouses, building data analytics engine and also predictive analytics platforms using many of the above features of Spark. If not, it has to be used with some cloud-based data platform.

Scala 52