Knowledge Hut

JANUARY 18, 2024

BI developers must use cloud-based platforms to design, prototype, and manage complex data. To pursue a career in BI development, one must have a strong understanding of data mining, data warehouse design, and SQL. Roles and Responsibilities Write data collection and processing procedures.

Data Science 98

Data Science Business Analyst Data Architect ETL Method 98

Knowledge Hut

JUNE 30, 2023

Investigate the difficulties and solutions in developing distributed systems and ensuring data consistency. Learn about data analysis techniques, data integration, serialization, and data pipelines. Key Benefits and Takeaways: Master the fundamentals and techniques of dimensional modeling for data warehouses.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

ProjectPro

JANUARY 27, 2023

Top ETL Business Use Cases for Streamlining Data Management Data Quality - ETL tools can be used for data cleansing, validation, enriching, and standardization before loading the data into a destination like a data lake or data warehouse.

BI 52

BI ETL Tools Retail Healthcare 52

ProjectPro

FEBRUARY 8, 2023

AWS Glue is a widely-used serverless data integration service that uses automated extract, transform, and load ( ETL ) methods to prepare data for analysis. It offers a simple and efficient solution for data processing in organizations. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog.

AWS 98

AWS Scala Metadata Data Lake 98

Knowledge Hut

DECEMBER 21, 2023

What is Data Engineering? Data engineering is the method to collect, process, validate and store data. It involves building and maintaining data pipelines, databases, and data warehouses. The purpose of data engineering is to analyze data and make decisions easier.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Ascend.io

SEPTEMBER 19, 2023

However , the traditional methods of executing ETL are increasingly struggling to meet the escalating demands of today’s data-intensive environments. Transform: Process the data to make it suitable for analysis (this can involve cleaning, aggregating, enriching, and restructuring).

ETL Tools 52

ETL Tools ETL Method Data Engineering Data Engineer 52