Alation

MAY 24, 2022

Prime examples of this in the data catalog include: Trust Flags — Allow the data community to endorse, warn, and deprecate data to signal whether data can or can’t be used. Data Profiling — Statistics such as min, max, mean, and null can be applied to certain columns to understand its shape.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

The MLOps Blog

MARCH 15, 2023

This is a difficult decision at the onset, as the volume of data is a factor of time and keeps varying with time, but an initial estimate can be quickly gauged by analyzing this aspect by running a pilot. Also, the industry best practices suggest performing a quick data profiling to understand the data growth.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Reduce data duplication and fragmentation.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

Dataconomy

JULY 28, 2023

With its user-friendly interface and drag-and-drop functionalities, Tableau enables the creation of interactive data visualizations and dashboards, making it accessible to both technical and non-technical users. Trifacta Trifacta is a data profiling and wrangling tool that stands out with its rich features and ease of use.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

phData

SEPTEMBER 28, 2023

Power BI Dataflows provide vital functionalities that effectively empower users to cleanse and reshape data from various sources. These Dataflows are crucial in fostering consistency and reducing the duplication of repetitive ETL (Extract, Transform, Load) steps, achieved by reusing transformations.

Power BI 78

Power BI Data Preparation Machine Learning Machine Learning 78

phData

AUGUST 17, 2023

They offer a range of features and integrations, so the choice depends on factors like the complexity of your data pipeline, requirements for connections to other services, user interface, and compatibility with any ETL software already in use. Include tasks to ensure data integrity, accuracy, and consistency.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52