Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. This process can encompass a wide range of activities, each aiming to enhance the data’s usability and relevance.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Ascend.io

SEPTEMBER 14, 2023

High Performance Python is inherently efficient and robust, enabling data engineers to handle large datasets with ease: Speed & Reliability: At its core, Python is designed to handle large datasets swiftly , making it ideal for data-intensive tasks. show() So How Much Python Is Required for a Data Engineer?

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

DareData

JULY 5, 2023

Users: Who are users that will interact with your data and what's their technical proficiency? Data Sources: How different are your data sources? Latency: What is the minimum expected latency between data collection and analytics? And what is their format?

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Confluent

FEBRUARY 6, 2019

While all these solutions help data scientists, data engineers and production engineers to work better together, there are underlying challenges within the hidden debts: Data collection (i.e., Apache Kafka and KSQL for data scientists and data engineers. integration) and preprocessing need to run at scale.

Machine Learning 106

Machine Learning Python Kafka Java 106

ProjectPro

APRIL 20, 2017

There are various kinds of hadoop projects that professionals can choose to work on which can be around data collection and aggregation, data processing, data transformation or visualization. The dataset consists of metadata and audio features for 1M contemporary and popular songs.

Hadoop 40

Hadoop Big Data Coding Project 40

ProjectPro

JANUARY 25, 2022

Furthermore, PySpark allows you to interact with Resilient Distributed Datasets (RDDs) in Apache Spark and Python. PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. RDD uses a key to partition data into smaller chunks.

Big Data 52

Big Data Data Process Process Kafka 52

ProjectPro

AUGUST 24, 2021

And if you are aspiring to become a data engineer, you must focus on these skills and practice at least one project around each of them to stand out from other candidates. Explore different types of Data Formats: A data engineer works with various dataset formats like.csv,josn,xlx, etc.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52