Precisely

JANUARY 17, 2023

Data Volume, Variety, and Velocity Raise the Bar Corporate IT landscapes are larger and more complex than ever. Cloud computing offers some advantages in terms of scalability and elasticity, yet it has also led to higher-than-ever volumes of data. As they do so, access to traditional and modern data sources is required.

Data Quality 97

Data Quality Machine Learning Machine Learning Data Silos 97

Pickl AI

OCTOBER 6, 2024

This phase is crucial for enhancing data quality and preparing it for analysis. Transformation involves various activities that help convert raw data into a format suitable for reporting and analytics. Normalisation: Standardising data formats and structures, ensuring consistency across various data sources.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52

Alation

OCTOBER 12, 2021

In enterprises especially, which typically collect vast amounts of data, analysts often struggle to find, understand, and trust data for analytics reporting. Immense volume leads to data silos, and a holistic view of the business becomes more difficult to achieve. Evaluate and monitor data quality.

Analytics 52

Analytics Analytics Data Governance DataOps 52