Knowledge Hut

JANUARY 29, 2024

Google DataPrep: A data service provided by Google that explores, cleans, and prepares data, offering a user-friendly approach. Data Wrangler: Another data cleaning and transformation tool, offering flexibility in data preparation.

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 52

Knowledge Hut

JANUARY 30, 2024

Database Queries: When dealing with structured data stored in databases, SQL queries are instrumental for data extraction. SQL queries enable the retrieval of specific data subsets or the aggregation of information from multiple tables. The ETL process encompasses three fundamental stages: 1.

ETL Tools 52

ETL Tools Database-centric Data Mining Raw Data 52

Knowledge Hut

MARCH 28, 2024

Role Level: Intermediate Responsibilities Develop and enforce data governance policies, standards, and procedures in Azure environments. Implement data security measures, access controls, and encryption mechanisms to protect sensitive data. Familiarity with ETL tools and techniques for data integration.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Edureka

JULY 4, 2024

On the other hand, thanks to the Spark component, you can perform data preparation, data engineering, ETL, and machine learning tasks using industry-standard Apache Spark. Advanced Security Features Security is top-notch with Synapse. Is Azure Synapse an ETL tool?

Data Lake 40

Data Lake Pipeline-centric Data Warehouse ETL Tools 40

Edureka

FEBRUARY 7, 2023

Dynamic data masking serves several important functions in data security. It can be set up as a security policy on all SQL Databases in an Azure subscription. It does away with the requirement to import data from an outside source. Export information to Azure Data Lake Store, Azure Blob Storage, or Hadoop.

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

ProjectPro

JANUARY 19, 2022

ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse. Get familiar with popular ETL tools like Xplenty, Stitch, Alooma, etc. Different methods are used to store different types of data. The final step is to publish your work.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

AltexSoft

MARCH 30, 2023

Source: The Data Team’s Guide to the Databricks Lakehouse Platform Integrating with Apache Spark and other analytics engines, Delta Lake supports both batch and stream data processing. Besides that, it’s fully compatible with various data ingestion and ETL tools. Databricks two-plane infrastructure.

Scala 64

Scala Data Lake Machine Learning BI 64