ProjectPro

DECEMBER 7, 2021

A pipeline may include filtering, normalizing, and data consolidation to provide desired data. In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. Step 2- Internal Data transformation at LakeHouse.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

JANUARY 19, 2024

With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. In data science, we use various tools, processes, and algorithms to extract insights from structured and unstructured data. Importance: Efficient organization and retrieval of data.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Ascend.io

DECEMBER 14, 2022

How ETL Became Outdated The ETL process (extract, transform, and load) is a data consolidation technique in which data is extracted from one source, transformed, and then loaded into a target destination. We won’t dive into the origins of ETL , but it’s important to understand its surroundings. This is when ELT came in.

Data Integration 52

Data Integration Raw Data Data Consolidation Data Warehouse 52

Monte Carlo

FEBRUARY 15, 2023

Finally, where and how the data pipeline broke isn’t always obvious. Monte Carlo solves these problems with our our data observability platform that uses machine learning to help detect, resolve and prevent bad data. Data can be loaded in batches or can be streamed in near real-time.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

AltexSoft

NOVEMBER 23, 2021

In simple terms, data remains in original sources while users can access and analyze it virtually via special middleware. Before we get into more detail, let’s determine how data virtualization is different from another, more common data integration technique — data consolidation. Connection layer.

Process 69

Process Data Lake Metadata Data Warehouse 69