Ascend.io

AUGUST 31, 2023

Performance: Because the data is transformed and normalized before it is loaded , data warehouse engines can leverage the predefined schema structure to tune the use of compute resources with sophisticated indexing functions, and quickly respond to complex analytical queries from business analysts and reports.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Knowledge Hut

JANUARY 29, 2024

In today's data-driven world, where information reigns supreme, businesses rely on data to guide their decisions and strategies. However, the sheer volume and complexity of raw data from various sources can often resemble a chaotic jigsaw puzzle. What are the six steps of data wrangling?

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 52

Databand.ai

AUGUST 30, 2023

These tools play a vital role in data preparation, which involves cleaning, transforming and enriching raw data before it can be used for analysis or machine learning models. There are several types of data testing tools. This is part of a series of articles about data quality.

Data Cleanse 52

Data Cleanse Data Pipeline Datasets Data Validation 52

Databand.ai

JUNE 14, 2023

During ingestion: Test your data as it enters your system to identify any issues with the source or format early in the process. After transformation: After processing or transforming raw data into a more usable format, test again to ensure that these processes have not introduced errors or inconsistencies.

Amazon Web Services 52

Amazon Web Services Datasets High Quality Data ETL Tools 52

Databand.ai

JULY 19, 2023

The Transform Phase During this phase, the data is prepared for analysis. This preparation can involve various operations such as cleaning, filtering, aggregating, and summarizing the data. The goal of the transformation is to convert the raw data into a format that’s easy to analyze and interpret.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Ascend.io

SEPTEMBER 19, 2023

Automated ETL Before unraveling the nuances that set traditional and automated ETL apart, it’s paramount to ground ourselves in the basics of the traditional ETL process. ETL stands for: Extract: Retrieve raw data from various sources.

ETL Tools 52

ETL Tools ETL Method Utilities Data Engineering 52

ProjectPro

NOVEMBER 30, 2021

Now that we have understood how much significant role data plays, it opens the way to a set of more questions like How do we acquire or extract raw data from the source? How do we transform this data to get valuable insights from it? Where do we finally store or load the transformed data?

Process 52

Process Data Pipeline Data Warehouse AWS 52