Astera

AUGUST 16, 2024

Let’s look at some reasons data migration projects fail: Risk of Data Integrity Loss Data quality maintenance is crucial to a smooth data migration process, especially when dealing with large volumes of data. Astera does all the heavy lifting involved in a data migration.

Digital Transformation 52

Digital Transformation Planning Government Cloud Computing 52

Astera

MAY 25, 2023

However, businesses can also leverage data integration and management tools to enhance their security posture. How is big data secured? Big data is extremely valuable, but also vulnerable. Protecting big data requires a multi-faceted approach to security. Access Control Controlling access to sensitive data is key.

Big Data 40

Big Data Data Security Monitoring Data Quality 40

Cprime

MAY 4, 2023

Data Warehouse Automation The data warehouse automation process accelerates the availability of analytics-ready data by automating the data warehouse lifecycle—from data modeling and real-time ingestion to data marts and governance.

Data Warehouse 52

Data Warehouse Big Data Finance Data Quality 52

Astera

DECEMBER 21, 2022

What’s more, modern data warehouses come with access control features to ensure that the data required for business intelligence is only visible to relevant personnel. With a visual, intuitive interface, Astera DW Builder is a cloud data warehousing solution that has been designed to simplify the process of DWH implementation.

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 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

The BAWorld

NOVEMBER 22, 2021

Completeness is a data quality dimension and measures the existence of required data attributes in the source in data analytics terms, checks that the data includes what is expected and nothing is missing. Consistency is a data quality dimension and tells us how reliable the data is in data analytics terms.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98

Astera

JANUARY 12, 2024

It was developed by Dan Linstedt and has gained popularity as a method for building scalable, adaptable, and maintainable data warehouses. Self-Serve Data Infrastructure as a Platform: A shared data infrastructure empowers users to independently discover, access, and process data, reducing reliance on data engineering teams.

Data Architecture 52

Data Architecture Data Warehouse Data Quality Government 52

Astera

APRIL 24, 2024

Enterprise-Grade Integration Engine : Offers comprehensive tools for integrating diverse data sources and native connectors for easy mapping. Interactive, Automated Data Preparation : Ensures data quality using data health monitors, interactive grids, and robust quality checks.

IBM Support 52

IBM Support IBM cost IBM Maintenance Visualization 52