Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. In this article, we’ll focus on a data lake vs. data warehouse.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

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 317

Data Science Analytics Analytics Data Warehouse 317

Analytics Vidhya

DECEMBER 26, 2022

This article was published as a part of the Data Science Blogathon. Overview ETL (Extract, Transform, and Load) is a very common technique in data engineering. It involves extracting the operational data from various sources, transforming it into a format suitable for business needs, and loading it into data storage systems.

ETL 306

ETL AWS Data Engineering Data Engineer 306

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 297

ETL Analytics Analytics Data Warehouse 297

Analytics Vidhya

DECEMBER 23, 2022

This article was published as a part of the Data Science Blogathon. Source: [link] Introduction In today’s digital world, data is generated at a swift pace. Data in itself is not useful unless we present it in a meaningful way and derive insights that help in making key business decisions.

Business Intelligence 271

Business Intelligence Business Intelligence Data Science Analytics 271

ODSC - Open Data Science

JUNE 22, 2023

These are called data lakes. What Are Data Lakes? Unlike databases and data warehouses, data lakes can store data in raw and unstructured forms. This feature is important because it allows data lakes to hold a larger amount of data and store it faster.

Data Lakes 98

Data Lakes Data Warehouse Database Data Science 98

Alation

JANUARY 17, 2023

In this article, I will explain the modern data stack in detail, list some benefits, and discuss what the future holds. What Is the Modern Data Stack? The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Mlearning.ai

FEBRUARY 16, 2023

The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. The ultimate need for vast storage spaces manifests in data warehouses: specialized systems that aggregate data coming from numerous sources for centralized management and consistency.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

Alation

JULY 13, 2021

This recent cloud migration applies to all who use data. We have seen the COVID-19 pandemic accelerate the timetable of cloud data migration , as companies evolve from the traditional data warehouse to a data cloud, which can host a cloud computing environment. Fern Halper, Ph.D.

Cloud Data 52

Cloud Data Data Governance Data Warehouse Data Mining 52

Pickl AI

NOVEMBER 4, 2024

The global Big Data and Data Engineering Services market, valued at USD 51,761.6 This article explores the key fundamentals of Data Engineering, highlighting its significance and providing a roadmap for professionals seeking to excel in this vital field. ETL is vital for ensuring data quality and integrity.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Dataconomy

FEBRUARY 23, 2023

Collecting, storing, and processing large datasets Data engineers are also responsible for collecting, storing, and processing large volumes of data. This involves working with various data storage technologies, such as databases and data warehouses, and ensuring that the data is easily accessible and can be analyzed efficiently.

Big Data 91

Big Data Big Data Data Engineering Data Engineer 91

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

ODSC - Open Data Science

JULY 11, 2023

6] Questions for AI About Data Centers To learn more about data centers I began by asking ChatGPT what Chief Transformation Officers should know about them. This interaction is described in my upcoming article in CXOTech Magazine. Next, I asked what a data center typically looks like and how it should be staffed.

Data Lakes 40

Data Lakes AI AI Cloud Computing 40

Dataversity

NOVEMBER 25, 2022

At the same time, many forward-thinking businesses, from startups to large corporations, have implemented a modern cloud analytics stack to use data more efficiently. In this article, we will discuss how a modern […].

Analytics 52

Analytics Analytics Data Warehouse Cloud Computing 52

IBM Journey to AI blog

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

DECEMBER 10, 2024

AI, hybrid cloud, and advanced analytics empower businesses to achieve operational excellence and drive digital transformation. Introduction This article explores Oracles engineered systemsExalytics, Exalogic, and Exadatahighlighting their transformative role in modern IT infrastructure.

Database 52

Database Analytics Analytics Business Intelligence 52

Dataversity

JUNE 2, 2023

If your enterprise is about to undertake a digital transformation (Dx) project, you should understand that these initiatives require a focus on more than the technology itself.

Data Warehouse 52

Data Warehouse Cloud Computing 52