Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

Data Profiling 52

Data Profiling Data Quality Data Governance Data Pipeline 52

Dataversity

DECEMBER 16, 2020

According to IDC, the size of the global datasphere is projected to reach 163 ZB by 2025, leading to the disparate data sources in legacy systems, new system deployments, and the creation of data lakes and data warehouses. Most organizations do not utilize the entirety of the data […].

Data Warehouse 69

Data Warehouse Data Lakes Data Profiling Data Quality 69

Alation

JANUARY 13, 2022

Thoughtworks says data mesh is key to moving beyond a monolithic data lake. Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Thoughtworks says data mesh is key to moving beyond a monolithic data lake 2. Gartner on Data Fabric.

Data Lakes 59

Data Lakes Data Governance Data Quality Data Warehouse 59

The MLOps Blog

JUNE 27, 2023

LakeFS LakeFS is an open-source platform that provides data lake versioning and management capabilities. It sits between the data lake and cloud object storage, allowing you to version and control changes to data lakes at scale. Share features across the organization.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Lakes Data Warehouse Business Intelligence 52

phData

SEPTEMBER 28, 2023

Dataflows allow users to establish source connections and retrieve data, and subsequent data transformations can be conducted using the online Power Query Editor. In this blog, we will provide insights into the process of creating Dataflows and offer guidance on when to choose them to address real-world use cases effectively.

Power BI 78

Power BI Data Preparation Machine Learning Machine Learning 78

The MLOps Blog

MAY 17, 2023

ETL data pipeline architecture | Source: Author Data Discovery: Data can be sourced from various types of systems, such as databases, file systems, APIs, or streaming sources. We also need data profiling i.e. data discovery, to understand if the data is appropriate for ETL.

ETL 59

ETL Data Pipeline ML ML 59