Pickl AI

APRIL 6, 2023

Consequently, here is an overview of the essential requirements that you need to have to get a job as an Azure Data Engineer. In-depth knowledge of distributed systems like Hadoop and Spart, along with computing platforms like Azure and AWS. Which service would you use to create Data Warehouse in Azure?

Azure 52

Azure Data Engineering Data Engineer Data Engineering 52

Analytics Vidhya

FEBRUARY 6, 2023

Introduction The demand for data to feed machine learning models, data science research, and time-sensitive insights is higher than ever thus, processing the data becomes complex. To make these processes efficient, data pipelines are necessary.

Data Pipeline 261

Data Pipeline Data Engineering Data Engineer Data Engineering 261

Alation

DECEMBER 14, 2021

Alation recently attended AWS re:invent 2021 … in person! AWS Keynote: “Still Early Days” for Cloud. Adam Selipsky, CEO of AWS, brought this energy in his opening keynote, welcoming a packed room and looking back on the progress of AWS. Cloud accounts for less than 5% of global IT spending , according to estimates.

AWS 52

AWS Data Lakes Data Warehouse Machine Learning 52

Analytics Vidhya

DECEMBER 31, 2022

This article was published as a part of the Data Science Blogathon. Introduction Data sharing has become so easy today, and we can share the details with just a few clicks. The post How to Encrypt and Decrypt the Data in PySpark? These details can get leaked if the […].

Data Science 269

Data Science Analytics Analytics Data Warehouse 269

Analytics Vidhya

FEBRUARY 4, 2023

Introduction This article will explain the difference between ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) when data transformation occurs. In ETL, data is extracted from multiple locations to meet the requirements of the target data file and then placed into the file.

ETL 231

ETL Analytics Analytics Data Warehouse 231

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 167

Data Lakes Analytics Analytics Data Warehouse 167

AWS Machine Learning Blog

JULY 17, 2023

With cloud computing, as compute power and data became more available, machine learning (ML) is now making an impact across every industry and is a core part of every business and industry. Amazon Redshift is a fully managed, fast, secure, and scalable cloud data warehouse.

Clustering 67

Clustering AWS ML ML 67

Precisely

JANUARY 25, 2024

Many organizations adopt a long-term approach, leveraging the relative strengths of both mainframe and cloud systems. This integrated strategy keeps a wide range of IT options open, blending the reliability of mainframes with the innovation of cloud computing.

Data Governance 69

Data Governance Database Cloud Data Data Lakes 69

phData

MAY 25, 2023

Snowflake is a cloud computing–based data cloud company that provides data warehousing services that are far more scalable and flexible than traditional data warehousing products. On the other hand, Snowflake wants to drive as much storage and compute onto their platform as possible too.

Power BI 84

Power BI Analytics Analytics Azure 84