Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data Ensuring data quality and integrity Data quality and integrity are essential for accurate data analysis. Data engineers are responsible for ensuring that the data collected is accurate, consistent, and reliable.

Big Data 91

Big Data Big Data Data Engineer Data Engineering 91

Pickl AI

AUGUST 30, 2024

Summary: This article provides a comprehensive overview of data migration, including its definition, importance, processes, common challenges, and popular tools. By understanding these aspects, organisations can effectively manage data transfers and enhance their data management strategies for improved operational efficiency.

Data Quality 52

Data Quality Data Governance Azure Database 52

Dataversity

DECEMBER 7, 2020

Data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations who seek to empower more and better data-driven decisions and actions throughout their enterprises. These groups want to expand their user base for data discovery, BI, and analytics so that their business […].

Data Warehouse 90

Data Warehouse Business Intelligence Business Intelligence Analytics 90

The MLOps Blog

MAY 17, 2023

Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. Here are some specific reasons why they are important: Data Integration: Organizations can integrate data from various sources using ETL pipelines. I hope this article was useful for you.

ETL 59

ETL Data Pipeline ML ML 59

The MLOps Blog

MARCH 15, 2023

Scalability : A data pipeline is designed to handle large volumes of data, making it possible to process and analyze data in real-time, even as the data grows. Data quality : A data pipeline can help improve the quality of data by automating the process of cleaning and transforming the data.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

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

Dataversity

FEBRUARY 1, 2021

In Part 1 and Part 2 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their […].

Data Warehouse 59

Data Warehouse Business Intelligence Business Intelligence Data Profiling 59

Dataversity

JANUARY 11, 2021

In Part 1 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their user base for […].

Data Warehouse 59

Data Warehouse Business Intelligence Business Intelligence Data Profiling 59

Dataversity

APRIL 22, 2022

In today’s digital world, data is undoubtedly a valuable resource that has the power to transform businesses and industries. As the saying goes, “data is the new oil.” However, in order for data to be truly useful, it needs to be managed effectively.

Data Profiling 52

Data Profiling Data Quality Data Governance Artificial Intelligence 52

Alation

JULY 6, 2021

Automated governance tracks data lineage so users can see data’s origin and transformation. Auto-tracked metrics guide governance efforts, based on insights around data quality and profiling. This empowers leaders to see and refine human processes around data. No Data Leadership. Data Quality.

Data Governance 52

Data Governance Data Quality Data Silos Data Profiling 52