Knowledge Hut

MAY 2, 2024

It is surprising to know how much data is generated every minute. Here come the frameworks like Apache Spark and MapReduce to our rescue and help us to get deep insights into this huge amount of structured, unstructured, and semi-structured data and make more sense of it. The demand for Spark is increasing at a very fast pace.

Scala 94

Scala Hadoop Datasets Java 94

Cloudera

NOVEMBER 13, 2020

Apache Impala is synonymous with high-performance processing of extremely large datasets, but what if our data isn’t huge? It turns out that Apache Impala scales down with data just as well as it scales up. Data science experiment result and performance analysis, for example, calculating model lift.

Metadata 144

Metadata Coding SQL Database 144

ProjectPro

NOVEMBER 30, 2021

This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. The crux of all data-driven solutions or business decision-making lies in how well the respective businesses collect, transform, and store data.

Process 52

Process Data Pipeline Data Warehouse AWS 52

Towards Data Science

NOVEMBER 4, 2023

We will discuss how to use this knowledge to power advanced analytics pipelines and operational excellence. Does your DE work well enough to fuel advanced data pipelines and Business intelligence (BI)? Are your data pipelines efficient? In this article, I want to talk about crucial things that affect data engineers.

Data Engineering 87

Data Engineering Data Engineer Engineering BI 87