Astera

DECEMBER 21, 2022

In comparison to cloud data warehouses, on-premise data warehouses pose certain challenges that affect the efficiency of the organizations’ analytics and business intelligence operations. Moreover, when using a legacy data warehouse, you run the risk of issues in multiple areas, from security to compliance.

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 52

ElegantJ BI

SEPTEMBER 30, 2021

When a business enters the domain of data management, it is easy to get lost in a flurry of promises, brochures, demos and the promise of the future. In this article, we will present the factors and considerations involved in choosing the right data management solution for your business. Data Warehouse.

Data Management 130

Data Management Data Warehouse Data Governance Government 130

Data Pine

MAY 2, 2023

To work effectively, big data requires a large amount of high-quality information sources. Where is all of that data going to come from? On the contrary, without using the right tools, intelligence, and insights, you’ll likely find yourself forever on the back foot. Now’s the time to strike.

Supply Chain 110

Supply Chain Logistics Big Data Customer Experience 110

Astera

OCTOBER 19, 2023

While all data transformation solutions can generate flat files in CSV or similar formats, the most efficient data prep implementations will also easily integrate with your other productivity business intelligence (BI) tools. Manual export and import steps in a system can add complexity to your data pipeline.

IBM Support 40

IBM Support Data Quality IBM Maintenance Real-time Data 40

Insight Software

JANUARY 17, 2022

These five BI requirements (both technical and non-technical) are critical to any analytics implementation and common to most evaluations. Business intelligence requirements in this category may include dashboards and reports as well as the interactive and analytical functions users can perform. End-User Experience.

Business Intelligence 52

Business Intelligence Business Intelligence User Experience Embedded Analytics 52

Astera

MARCH 20, 2024

This article covers everything about enterprise data management, including its definition, components, comparison with master data management, benefits, and best practices. What Is Enterprise Data Management (EDM)? Why is Enterprise Data Management Important?

Data Management 52

Data Management Master Data Management Data Warehouse Government 52

Astera

JANUARY 2, 2024

Businesses, both large and small, find themselves navigating a sea of information, often using unhealthy data for business intelligence (BI) and analytics. 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.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Astera

JUNE 14, 2023

The process enables businesses to unlock valuable information hidden within unstructured documents. The ultimate goal is to convert unstructured data into structured data that can be easily housed in data warehouses or relational databases for various business intelligence (BI) initiatives.

Documentation 52

Documentation Supply Chain Healthcare Logistics 52

Astera

NOVEMBER 28, 2023

Importance of Data Pipelines Data pipelines are essential for the smooth, automated, and reliable management of data throughout its lifecycle. They enable organizations to derive maximum value from their data assets. Your goals will guide the design, complexity, and scalability of your pipeline.

Data Warehouse 52

Data Warehouse Monitoring Data Security Healthcare 52

Astera

FEBRUARY 1, 2024

With a combination of text, symbols, and diagrams, data modeling offers visualization of how data is captured, stored, and utilized within a business. It serves as a strategic exercise in understanding and clarifying the business’s data requirements, providing a blueprint for managing data from collection to application.

Data Modelling 40

Data Modelling Retail Documentation Visualization 40

Astera

NOVEMBER 1, 2023

Businesses rely heavily on various technologies to manage and analyze their growing amounts of data. Data warehouses and databases are two key technologies that play a crucial role in data management. It is important to understand the goals and objectives of the data management system.

Data Warehouse 40

Data Warehouse Real-time Data E-Commerce Data Governance 40

Astera

DECEMBER 21, 2022

Across all sectors, success in the era of Big Data requires robust management of a huge amount of data from multiple sources. Whether you are running a video chat app, an outbound contact center, or a legal firm, you will face challenges in keeping track of overwhelming data. What are the benefits of unified data?

Data Management 52

Data Management Data Governance Government Data Warehouse 52

Astera

OCTOBER 27, 2023

Simply put, a cloud data warehouse is a data warehouse that exists in the cloud environment, capable of combining exabytes of data from multiple sources. Cloud data warehouses are designed to handle complex queries and are optimized for business intelligence (BI) and analytics.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Data Pine

OCTOBER 30, 2019

Usually created with past data without the possibility to generate real-time or future insights, these reports were obsolete, comprised of numerous external and internal files, without proper data management processes at hand. The rise of innovative report tools means you can create data reports people love to read.

Visualization 51

Visualization Retail Data Visualization Government 51

Astera

SEPTEMBER 20, 2023

Data integration is a core component of the broader data management process, serving as the backbone for almost all data-driven initiatives. It ensures businesses can harness the full potential of their data assets effectively and efficiently.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

SEPTEMBER 20, 2023

Data integration is a core component of the broader data management process, serving as the backbone for almost all data-driven initiatives. It ensures businesses can harness the full potential of their data assets effectively and efficiently.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Data Pine

NOVEMBER 27, 2019

Over the past decade, business intelligence has been revolutionized. Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain.

Business Intelligence 144

Business Intelligence Business Intelligence Artificial Intelligence Data Discovery 144

Astera

APRIL 24, 2024

The platform leverages a high-performing ETL engine for efficient data movement and transformation, including mapping, cleansing, and enrichment. Key Features: AI-Driven Data Management : Streamlines data extraction, preparation, and data processing through AI and automated workflows.

IBM Support 52

IBM Support IBM Maintenance IBM cost E-Commerce 52

Insight Software

MAY 1, 2023

Learn how embedded analytics are different from traditional business intelligence and what analytics users expect. Embedded Analytics Definition Embedded analytics are the integration of analytics content and capabilities within applications, such as business process applications (e.g., that gathers data from many sources.

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