Analytics Vidhya

FEBRUARY 25, 2023

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

Data Lakes 178

Data Lakes Analytics Analytics Data Warehouse 178

Data Science Connect

JULY 28, 2023

A recent article on Analytics Insight explores the critical aspect of data engineering for IoT applications. Understanding the intricacies of data engineering empowers data scientists to design robust IoT solutions, harness data effectively, and drive innovation in the ever-expanding landscape of connected devices.

Internet of Things 130

Internet of Things Data Engineer Data Engineering Data Engineering 130

Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. What is data engineering?

Big Data 91

Big Data Big Data Data Engineer Data Engineering 91

Pickl AI

APRIL 6, 2023

Accordingly, one of the most demanding roles is that of Azure Data Engineer Jobs that you might be interested in. The following blog will help you know about the Azure Data Engineering Job Description, salary, and certification course. How to Become an Azure Data Engineer?

Azure 52

Azure Data Engineer Data Engineering Data Engineering 52

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Data Science Blog

MARCH 14, 2023

Von Big Data über Data Science zu AI Einer der Gründe, warum Big Data insbesondere nach der Euphorie wieder aus der Diskussion verschwand, war der Leitspruch “S**t in, s**t out” und die Kernaussage, dass Daten in großen Mengen nicht viel wert seien, wenn die Datenqualität nicht stimme.

Big Data 147

Big Data Big Data Apache Hadoop Data Science 147

IBM Journey to AI blog

DECEMBER 7, 2023

Security and compliance : Ensuring data security and compliance with regulatory requirements in the cloud environment can be complex. Skills and expertise : Transitioning to cloud-based OLAP may require specialized skills and expertise in cloud computing and OLAP technologies.

Data Preparation 72

Data Preparation Database AI AI 72