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Avoid These Mistakes on Your Data Warehouse and BI Projects

Dataversity

Data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations who seek to empower more and better data-driven decisions and actions throughout their enterprises. These groups want to expand their user base for data discovery, BI, and analytics so that their business […].

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Developing Agile Data Warehouse Architecture Using Automation

Dataversity

In the past, designing and developing a robust data warehouse that satisfied the need for timely and effective business intelligence (BI) was an overwhelmingly difficult task, as it required significant time, capital, and risk. In essence, agile […]. In essence, agile […].

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Are Data Warehouses Still Relevant?

Dataversity

Over the past few years, enterprise data architectures have evolved significantly to accommodate the changing data requirements of modern businesses. Data warehouses were first introduced in the […] The post Are Data Warehouses Still Relevant? appeared first on DATAVERSITY.

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Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 2

Dataversity

In Part 1 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their user base for […].

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7 Factors to Consider When Deploying a Modern Data Estate

Dataversity

The abilities of an organization towards capturing, storing, and analyzing data; searching, sharing, transferring, visualizing, querying, and updating data; and meeting compliance and regulations are mandatory for any sustainable organization. For example, most data warehouses […].

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Build Data Warehouse with Concentrated Teams

Astera

Enterprises will soon be responsible for creating and managing 60% of the global data. Traditional data warehouse architectures struggle to keep up with the ever-evolving data requirements, so enterprises are adopting a more sustainable approach to data warehousing. Migrate to Cloud-based data architecture.

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Why You Need Cloud Data Integration for Analytics

Domo

According to Gartner , data integration is “the consistent access and delivery of data across the spectrum of data subject areas and data structure types in the enterprise to meet the data consumption requirements of all applications and business processes.”