Smart Data Collective

JULY 9, 2023

By harmonising and standardising data through ETL, businesses can eliminate inconsistencies and achieve a single version of truth for analysis. Improved Data Quality Data quality is paramount when it comes to making accurate business decisions.

Data Warehouse 213

Data Warehouse Data Quality Data Analytics Data Analytics 213

Analysts Corner

JUNE 18, 2023

Python, Java, C#) Familiarity with data modeling and data warehousing concepts Understanding of data quality and data governance principles Experience with big data platforms and technologies (e.g., Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

Astera

MARCH 7, 2024

Primary purpose is to ensure that the data being tested is moving as it’s supposed to. Aims to ensure that all data follows the data model’s predefined rules. Checks for duplications in the loaded data. During data movement and transformation. It reports any invalid data.

Data Warehouse 52

Data Warehouse Data Quality Documentation Data Modelling 52

The Data Administration Newsletter

JUNE 21, 2022

Twenty-five years ago today, I published the first issue of The Data Administration Newsletter. It only took a few months to recognize that there was an audience for an “online” publication focused on data administration. […].

Master Data Management 78

Master Data Management Data Quality Data Modelling Data Governance 78

Astera

JANUARY 2, 2024

Securing Data: Protecting data from unauthorized access or loss is a critical aspect of data management which involves implementing security measures such as encryption, access controls, and regular audits. Organizations must also establish policies and procedures to ensure data quality and compliance.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Astera

FEBRUARY 16, 2024

It facilitates the seamless collection, consolidation, and transformation of data from diverse sources and systems into a unified and standardized format. The advantages of this integration extend beyond mere organization; it significantly improves data quality and accuracy.

Finance 52

Finance Banking Data Quality Artificial Intelligence 52

Cprime

MAY 4, 2023

Key Data Integration Use Cases Let’s focus on the four primary use cases that require various data integration techniques: Data ingestion Data replication Data warehouse automation Big data integration Data Ingestion The data ingestion process involves moving data from a variety of sources to a storage location such as a data warehouse or data lake.

Data Warehouse 52

Data Warehouse Big Data Finance Data Quality 52

Astera

OCTOBER 27, 2023

Practical Tips To Tackle Data Quality During Cloud Migration The cloud offers a host of benefits that on-prem systems don’t. Here are some tips to ensure data quality when taking your data warehouse to the cloud. The added layer of governance enhances the overall data quality management efforts of an organization.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Astera

AUGUST 22, 2023

Grid View: The Grid View presents a dynamic and interactive grid that updates in real time, displaying the transformed data after each operation. It offers an instant preview and feedback on data quality, helping you ensure the accuracy and integrity of your data. Step Into the Future: Take Charge with Astera 10.3!

Innovation 52

Innovation Documentation Data Analytics Data Analytics 52