Astera

MAY 14, 2024

Let’s look at some of the metadata types below: Operational metadata: details how and when data occurs and transforms. This metadata type helps to manage, monitor, and optimize system architecture performance. Examples include time stamps, execution logs, data lineage, and dependency mapping. Image by Astera.

Government 52

Government Data Governance Master Data Management Documentation 52

ElegantJ BI

AUGUST 9, 2017

If your role in business demands that you stay abreast of changes in business analytics, you are probably familiar with the term Smart Data Discovery. You may also have read the recent Gartner report entitled, ‘Augmented Analytics Is the Future of Data and Analytics’ , Published 27 July 2017, by Rita L.

Data Discovery 130

Data Discovery Monitoring Data Governance Data Quality 130

Astera

FEBRUARY 27, 2024

Best Practices for Data Warehouses Adopting best practices tailored to optimize performance, fortify security, establish robust governance, ensure scalability, and maintain vigilant monitoring is crucial to extract the maximum benefits from your data warehouses.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

FEBRUARY 27, 2024

Best Practices for Data Warehouses Adopting best practices tailored to optimize performance, fortify security, establish robust governance, ensure scalability, and maintain vigilant monitoring is crucial to extract the maximum benefits from your data warehouses.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

ElegantJ BI

SEPTEMBER 7, 2016

Empower business users by letting them add new data, change data operations, change summary operations, change visualization and layout and even design dashboards, reports and cross tabs without programming skills. If you want your users to drive business results, you must empower them with interactive ad hoc analytical tools.

Business Intelligence 100

Business Intelligence Business Intelligence Data Discovery Predictive Analytics 100

ElegantJ BI

SEPTEMBER 7, 2016

Empower business users by letting them add new data, change data operations, change summary operations, change visualization and layout and even design dashboards, reports and cross tabs without programming skills. If you want your users to drive business results, you must empower them with interactive ad hoc analytical tools.

Business Intelligence 100

Business Intelligence Business Intelligence Data Discovery Predictive Analytics 100

ElegantJ BI

SEPTEMBER 7, 2016

Empower business users by letting them add new data, change data operations, change summary operations, change visualization and layout and even design dashboards, reports and cross tabs without programming skills. Myth #2 – True Self-Serve BI Tools Will Compromise Data Governance.

Business Intelligence 100

Business Intelligence Business Intelligence Data Discovery Predictive Analytics 100

Astera

MARCH 20, 2024

For example, with a data warehouse and solid foundation for business intelligence (BI) and analytics , you can respond quickly to changing market conditions, emerging trends, and evolving customer preferences. Data breaches and regulatory compliance are also growing concerns. Data Quality Management Not all data is created equal.

Data Management 52

Data Management Master Data Management Data Warehouse Government 52

Data Pine

DECEMBER 11, 2019

This means that your business’s data is available and secure regardless of a data breach or system failure. Improved data governance: Vertical SaaS is positioned to address data governance procedures via the inclusion of industry-specific compliance capabilities, which has the additional benefit of providing increased transparency.

Artificial Intelligence 125

Artificial Intelligence Innovation Digital Business Intelligence 125

ElegantJ BI

NOVEMBER 16, 2016

Features and Benefits When your enterprise considers self-serve BI tools, it must look carefully at the features and benefits of these tools and compare them to the requirements and needs of the IT organization (for data governance and data watermarking, as appropriate), and for users at all levels including executives, analysts and business users.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Data Visualization 130

ElegantJ BI

NOVEMBER 16, 2016

Features and Benefits When your enterprise considers self-serve BI tools, it must look carefully at the features and benefits of these tools and compare them to the requirements and needs of the IT organization (for data governance and data watermarking, as appropriate), and for users at all levels including executives, analysts and business users.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Data Visualization 130

ElegantJ BI

DECEMBER 5, 2016

Factors like poor User Adoption, Data Access, Features and Benefits, Self-Serve Analytical Capability, Data Sharing and Reporting, Cost vs. Benefit, and Data Discovery issues must be considered in order to ensure the success of your self-serve business intelligence initiative.

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Data Governance 130

ElegantJ BI

DECEMBER 5, 2016

Factors like poor User Adoption, Data Access, Features and Benefits, Self-Serve Analytical Capability, Data Sharing and Reporting, Cost vs. Benefit, and Data Discovery issues must be considered in order to ensure the success of your self-serve business intelligence initiative.

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Data Governance 130

ElegantJ BI

NOVEMBER 16, 2016

When your enterprise considers self-serve BI tools, it must look carefully at the features and benefits of these tools and compare them to the requirements and needs of the IT organization (for data governance and data watermarking, as appropriate), and for users at all levels including executives, analysts and business users.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Data Visualization 130

ElegantJ BI

DECEMBER 5, 2016

Factors like poor User Adoption, Data Access, Features and Benefits, Self-Serve Analytical Capability, Data Sharing and Reporting, Cost vs. Benefit, and Data Discovery issues must be considered in order to ensure the success of your self-serve business intelligence initiative.

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Data Governance 130