Knowledge Hut

NOVEMBER 28, 2023

Data engineers design, manage, test, maintain, store, and work on the data infrastructure that allows easy access to structured and unstructured data. Data engineers need to work with large amounts of data and maintain the architectures used in various data science projects. Technical Data Engineer Skills 1.Python

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

phData: Data Engineering

AUGUST 4, 2023

Snowflake hides user data objects and makes them accessible only through SQL queries through the compute layer. It handles the metadata related to these objects, access control configurations, and query optimization statistics. Exporting Data: Snowflake can export data into other systems’ file formats through an internal stage.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

AltexSoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Aggregation. Enrichment.

Process 52

Process Building Raw Data Data Lake 52

ProjectPro

JANUARY 31, 2023

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. Data Processing: This is the final step in deploying a big data model. How to avoid the same.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

AUGUST 24, 2021

Data Sourcing: Building pipelines to source data from different company data warehouses is fundamental to the responsibilities of a data engineer. So, work on projects that guide you on how to build end-to-end ETL/ELT data pipelines. to accumulate data over a given period for better analysis.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

phData: Data Engineering

JULY 18, 2023

First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse. Central Source of Truth for Analytics A Cloud Data Warehouse (CDW) is a type of database that provides analytical data processing and storage capabilities within a cloud-based infrastructure.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

ProjectPro

OCTOBER 20, 2021

Having multiple data integration routes helps optimize the operational as well as analytical use of data. Experimentation in production Big Data Data Warehouse for core ETL tasks Direct data pipelines Tiered Data Lake 4. 29) What is the difference between MLOps and DevOps?

Machine Learning 52

Machine Learning Algorithm Government Data Science 52