The Data Administration Newsletter

AUGUST 3, 2021

Database standards are common practices and procedures that are documented and […]. Rigidly adhering to a standard, any standard, without being reasonable and using your ability to think through changing situations and circumstances is itself a bad standard.

Documentation 116

Documentation Data Quality Data Modelling Data Architecture 116

Astera

APRIL 24, 2024

A data governance framework is a structured way of managing and controlling the use of data in an organization. It helps establish policies, assign roles and responsibilities, and maintain data quality and security in compliance with relevant regulatory standards.

Data Governance 52

Data Governance Government Data Architecture Data Quality 52

Tableau

JANUARY 27, 2021

In 2020, we released some of the most highly-anticipated features in Tableau, including dynamic parameters , new data modeling capabilities , multiple map layers and improved spatial support, predictive modeling functions , and Metrics. We continue to make Tableau more powerful, yet easier to use.

Business Intelligence 70

Business Intelligence Business Intelligence Government Visualization 70

Astera

JANUARY 2, 2024

Relying on this data to power business decisions is like setting sail without a map. This is why organizations have effective data management in place. But what exactly is data management? What Is Data Management? As businesses evolve, so does their data.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Tableau

JANUARY 27, 2021

In 2020, we released some of the most highly-anticipated features in Tableau, including dynamic parameters , new data modeling capabilities , multiple map layers and improved spatial support, predictive modeling functions , and Metrics. We continue to make Tableau more powerful, yet easier to use.

Business Intelligence 52

Business Intelligence Business Intelligence Government Visualization 52

Astera

DECEMBER 29, 2023

In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way. Free Download What is a Data Warehouse? Data is organized into two types of tables in a dimensional model: fact tables and dimension tables.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

DECEMBER 29, 2023

In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way. Free Download What is a Data Warehouse? Data is organized into two types of tables in a dimensional model: fact tables and dimension tables.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

MAY 13, 2024

Besides being relevant, your data must be complete, up-to-date, and accurate. Automated tools can help you streamline data collection and eliminate the errors associated with manual processes. Enhance Data Quality Next, enhance your data’s quality to improve its reliability.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Astera

FEBRUARY 27, 2024

These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

FEBRUARY 27, 2024

These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

MARCH 28, 2024

Data Catalog vs. Data Dictionary A common confusion arises when data dictionaries come into the discussion. Both data catalog and data dictionary serve essential roles in data management. How to Build a Data Catalog? Creating a catalog involves multiple important steps.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Astera

AUGUST 22, 2023

Uncover hidden insights and possibilities with Generative AI capabilities and the new, cutting-edge data analytics and preparation add-ons We’re excited to announce the release of Astera 10.3—the the latest version of our enterprise-grade data management platform. Specify the data layout and the fields you want to extract.

Innovation 52

Innovation Documentation Data Analytics Data Analytics 52

Astera

JUNE 14, 2023

Managing different versions of the same dataset can cause conflicts. Transformation: Converting data into a consistent format for easy use. Aligning external and internal data formats. Handling inaccurate and abnormal data. Ensuring data quality and consistency.

Procurement 52

Procurement Data Security Retail Monitoring 52

Astera

JULY 13, 2023

Data integration involves combining data from different sources into a single location, while data consolidation is performed to standardize data structure to ensure consistency. Organizations must understand the differences between data integration and consolidation to choose the right approach for their data management needs.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40

Tableau

SEPTEMBER 23, 2021

Low data discoverability: For example, Sales doesn’t know what data Marketing even has available, or vice versa—or the team simply can’t find the data when they need it. . Unclear change management process: There’s little or no formality around what happens when a data source changes. Now, data quality matters.

Data Governance 91

Data Governance Government Data Quality Change Management 91

Tableau

SEPTEMBER 23, 2021

Low data discoverability: For example, Sales doesn’t know what data Marketing even has available, or vice versa—or the team simply can’t find the data when they need it. . Unclear change management process: There’s little or no formality around what happens when a data source changes. Now, data quality matters.

Data Governance 79

Data Governance Government Data Quality Change Management 79

Astera

OCTOBER 27, 2023

The “cloud” part means that instead of managing physical servers and infrastructure, everything happens in the cloud environment—offsite servers take care of the heavy lifting, and you can access your data and analytics tools over the internet without the need for downloading or setting up any software or applications. We've got both!

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Cprime

MAY 4, 2023

Data integration merges the data from disparate systems, enabling a full view of all the information flowing through an organization and revealing a wealth of valuable business insights. What is Data Integration? Replication can occur in bulk, in batches on a scheduled basis, or in real time across data centers and/or the cloud.

Data Warehouse 52

Data Warehouse Big Data Finance Data Quality 52

Astera

APRIL 24, 2024

Key Features: AI-Driven Data Management : Streamlines data extraction, preparation, and data processing through AI and automated workflows. Enterprise-Grade Integration Engine : Offers comprehensive tools for integrating diverse data sources and native connectors for easy mapping. It has a collapse command feature.

IBM Support 52

IBM Support IBM Maintenance IBM cost E-Commerce 52

Insight Software

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

IBM Support 52

IBM Support IBM Maintenance Data Warehouse IBM cost 52

Insight Software

SEPTEMBER 1, 2023

These include data privacy and security concerns, model accuracy and bias challenges, user perception and trust issues, and the dependency on data quality and availability. Data Privacy and Security Concerns: Embedded predictive analytics often require access to sensitive user data for accurate predictions.

Predictive Analytics 52

Predictive Analytics IBM Support IBM Maintenance Embedded Analytics 52