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How Today’s Digital-Native Businesses Are Securing the Open Data Lakehouse

Dataversity

Today, we’re seeing more companies embrace cloud-based technologies to deliver superior customer experiences. An underlying architectural pattern is the leveraging of an open data lakehouse. That is no surprise – open data lakehouses can easily handle digital-era data types that traditional data warehouses were not designed for.

Digital 246
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Data Warehousing for Insurance Reporting and Analytics

Astera

The significance of data warehousing for insurance cannot be overstated. It forms the bedrock of modern insurance operations, facilitating data-driven insights and streamlined processes to better serve policyholders. The data warehouse has the highest adoption of data solutions, used by 54% of organizations.

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What Is Data Management and Why Is It Important?

Astera

However, this does not mean that it’s just an enterprise-level concern—for that, we have enterprise data management. Even small teams stand to enhance their revenue, productivity, and customer experience through an effective data management strategy. IoT systems are another significant driver of Big Data.

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5 Data Management Trends to Watch in 2023

Astera

Source: Gartner As companies continue to move their operations to the cloud, they are also adopting cloud-based data integration solutions, such as cloud data warehouses and data lakes. Interested in Learning More About Cloud Data Integration? Download Free Whitepaper 2.

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Breaking Down Data Silos: From Fragmented Data to Consolidated Insights

Astera

According to a report by IBM , the cost of data breaches is averaging $4.35 This will provide a single source of truth for all teams, reducing the risk of inconsistent or conflicting data. This can be accomplished through a variety of techniques, including data warehouses, data lakes, and data virtualization.

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Logi Symphony Soars in Latest Dresner Business Intelligence Report

Insight Software

This recognition highlights Logi Symphony’s commitment to exceptional customer experience and its strong reputation within the BI and analytics industry. The Dresner Customer Experience Model maps metrics like the sales and acquisition process, technical support, and consulting services, against general customer sentiment.

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Use Case Analysis for Business Intelligence Projects

Business Analysis Knowledge Share

This may involve data from internal systems, external sources, or third-party data providers. The data collected should be integrated into a centralized repository, often referred to as a data warehouse or data lake. Data integration ensures that all necessary information is readily available for analysis.