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

AltexSoft

Data sources In a data lake architecture, the data journey starts at the source. Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined.

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Big Data Analytics: How It Works, Tools, and Real-Life Applications

AltexSoft

And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. This data isn’t just about structured data that resides within relational databases as rows and columns. Data cleansing. whether small or big ?

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15+ Must Have Data Engineer Skills in 2023

Knowledge Hut

Technical Data Engineer Skills 1.Python Python Python is one of the most looked upon and popular programming languages, using which data engineers can create integrations, data pipelines, integrations, automation, and data cleansing and analysis. ETL is central to getting your data where you need it.

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When To Use Internal vs. External Stages in Snowflake

phData: Data Engineering

Snowflake’s ‘staging area’ is a specific storage location where raw files are first loaded before they’re imported into the Snowflake database. Once the data is loaded into Snowflake, it can be further processed and transformed using SQL queries or other tools within the Snowflake environment.

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AWS Instance Types Explained: Learn Series of Each Instances

Edureka

Introduction to AWS Instance Types Amazon Web Services (AWS) offers a diverse range of instance types, each tailored to specific computing needs and optimized for various workloads. In-Memory Caching- Memory-optimized instances are suitable for in-memory caching solutions, enhancing the speed of data access.

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