Astera

APRIL 4, 2024

Data governance’s primary purpose is to ensure organizational data assets’ quality, integrity, security, and effective use. The key objectives of Data Governance include: Enhancing Clear Ownership: Assigning roles to ensure accountability and effective management of data assets.

Data Governance 52

Data Governance Government E-Commerce Data Quality 52

Astera

FEBRUARY 28, 2024

Data Governance and Documentation Establishing and enforcing rules, policies, and standards for your data warehouse is the backbone of effective data governance and documentation. Metadata describes the structure, meaning, origin, and data usage.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

JUNE 4, 2024

Key Features of Data Catalog Inventory of All Data Assets The data catalog encompasses structured data (e.g., relational databases), semi-structured data (e.g., JSON, XML), and even unstructured data (e.g., text documents, images, and videos).

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Astera

SEPTEMBER 4, 2024

This approach involves delivering accessible, discoverable, high-quality data products to internal and external users. By taking on the role of data product owners, domain-specific teams apply product thinking to create reliable, well-documented, easy-to-use data products.

Data Architecture 52

Data Architecture Data Governance Government Data Discovery 52

Astera

FEBRUARY 27, 2024

It also supports predictive and prescriptive analytics, forecasting future outcomes and recommending optimal actions based on data insights. Enhancing Data Quality A data warehouse ensures high data quality by employing techniques such as data cleansing, validation, integration, and standardization during the ETL process.

Data Warehouse 52

Data Warehouse Data Quality Cloud Computing Monitoring 52

Astera

FEBRUARY 27, 2024

It also supports predictive and prescriptive analytics, forecasting future outcomes and recommending optimal actions based on data insights. Enhancing Data Quality A data warehouse ensures high data quality by employing techniques such as data cleansing, validation, integration, and standardization during the ETL process.

Data Warehouse 52

Data Warehouse Data Quality Cloud Computing Monitoring 52

Astera

MARCH 20, 2024

Enterprise data management (EDM) is a holistic approach to inventorying, handling, and governing your organization’s data across its entire lifecycle to drive decision-making and achieve business goals. It provides a strategic framework to manage enterprise data with the highest standards of data quality , security, and accessibility.

Data Management 52

Data Management Master Data Management Government Data Quality 52

GAVS Technology

JUNE 2, 2021

In the recently announced Technology Trends in Data Management, Gartner has introduced the concept of “Data Fabric”. Here is the link to the document, Top Trends in Data and Analytics for 2021: Data Fabric Is the Foundation (gartner.com). Srinivasan Sundararajan.

Healthcare 52

Healthcare Data Governance Government Data Mining 52

Astera

MAY 14, 2024

This metadata variation ensures proper data interpretation by software programs. Process metadata: tracks data handling steps. It ensures data quality and reproducibility by documenting how the data was derived and transformed, including its origin. Data is only valuable if it is reliable.

Government 52

Government Data Governance Master Data Management Documentation 52

Astera

MAY 8, 2024

Improved Data Quality and Governance: Access to high-quality data is crucial for making informed business decisions. A business glossary is critical in ensuring data integrity by clearly defining data collection, storage, and analysis terms.

Data Governance 52

Data Governance Government Healthcare Data Quality 52

Astera

MAY 30, 2024

Variety : Data comes in all formats – from structured, numeric data in traditional databases to emails, unstructured text documents, videos, audio, financial transactions, and stock ticker data. Veracity: The uncertainty and reliability of data. Veracity addresses the trustworthiness and integrity of the data.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Data Pine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

Business Intelligence 144

Business Intelligence Business Intelligence Artificial Intelligence Data Discovery 144

ElegantJ BI

JANUARY 22, 2017

Content Management Systems (CMS) and online meeting software furthered collaboration and sharing and helped business users to come together to review and edit documents and work on projects. In the old days, team members and employees shared and discussed information at the water cooler or in the cafeteria.

Business Intelligence 100

Business Intelligence Business Intelligence Data Quality Data Discovery 100

ElegantJ BI

JANUARY 22, 2017

Content Management Systems (CMS) and online meeting software furthered collaboration and sharing and helped business users to come together to review and edit documents and work on projects. In the old days, team members and employees shared and discussed information at the water cooler or in the cafeteria.

Business Intelligence 100

Business Intelligence Business Intelligence Data Quality Data Discovery 100

ElegantJ BI

JANUARY 22, 2017

Content Management Systems (CMS) and online meeting software furthered collaboration and sharing and helped business users to come together to review and edit documents and work on projects. In the old days, team members and employees shared and discussed information at the water cooler or in the cafeteria. About Kartik Patel.

Business Intelligence 100

Business Intelligence Business Intelligence Data Quality Data Discovery 100

Astera

JUNE 14, 2024

Instead of relying solely on manual efforts, automated data governance uses reproducible processes to maintain data quality, enrich data assets, and simplify workflows. This approach streamlines data management, maintains data integrity, and ensures consistent data quality and context over time.

Data Governance 40

Data Governance Government Data Quality Data Discovery 40

Astera

AUGUST 28, 2024

Ideal for: user-friendly data exploration and self-service analytics, well-suited for businesses of all sizes with a focus on intuitive data discovery. SAS Viya SAS Viya is an AI-powered, in-memory analytics engine that offers data visualization, reporting, and analytics for businesses. The quality of customer support.

IBM Support 40

IBM Support IBM Maintenance IBM cost Data Mining 40

Astera

DECEMBER 6, 2024

Transform Your Document Processing with NLP and LLM Combine NLPs precision and LLMs versatility. With Asteras cutting-edge IDP solution, you can extract, process, and analyze documents effortlessly. transformers) to track context across paragraphs or entire documents, making responses more cohesive and context-aware.

Documentation 52

Documentation E-Commerce Artificial Intelligence Data Warehouse 52

Insight Software

MARCH 14, 2024

Jet’s interface lets you handle data administration easily, without advanced coding skills. You don’t need technical skills to manage complex data workflows in the Fabric environment. Data Discovery and Semantic Layer By facilitating effective data discovery and the development of a semantic layer, Jet gives Fabric users more control.

IBM Maintenance 52

IBM Maintenance IBM Support Data Discovery Supply Chain 52