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Data Warehouse vs. Data Lakehouse

The phrase “data warehouse vs. data lakehouse” offers an exciting topic for ongoing debate in the global data management world. While businesses have relied on traditional data warehouses for storing structured and semi-structured data for years, the more recent technological solution of the data lakehouse is growing in importance because of its unique ability to provide structure to raw data.  […]

What Is Data Integration?

Data integration combines information from multiple sources into unified, reliable data that drives business operations and decision-making. It consolidates data from databases, applications, spreadsheets, and tribal knowledge into a single cohesive system for effective use. Modern businesses generate vast amounts of data across different systems and departments. Without data integration, this information remains scattered and difficult to use. With it, organizations can […]

Data Lake Strategy: Its Benefits, Challenges, and Implementation

In today’s hyper-competitive business environment, data is one of the most valuable assets an organization can have. However, the sheer volume, variety, and velocity of data can overwhelm traditional data management solutions. Enter the data lake – a centralized repository designed to store all types of data, whether structured, semi-structured, or unstructured.  Unlike traditional data warehouses, data […]

Mind the Gap: Analytics Architecture Stuck in the 1990s

Welcome to the latest edition of Mind the Gap, a monthly column exploring practical approaches for improving data understanding and data utilization (and whatever else seems interesting enough to share). Last month, we explored the data chasm. This month, we’ll look at analytics architecture. From day one, data warehouses and their offspring – data marts, operational […]

Data Lakehouse Architecture 101

A data lakehouse, in the simplest terms, combines the best functionalities of a data lake and a data warehouse. It offers a unified platform for seamlessly integrating both structured and unstructured data, providing businesses agility, scalability, and flexibility in their data analytics processes. Unlike traditional data warehouses that rely on rigid schemas for organizing and […]

How to Become a Data Engineer

The work of data engineers is extremely technical. They are responsible for designing and maintaining the architecture of data systems, which incorporates concepts ranging from analytic infrastructures to data warehouses. A data engineer needs to have a solid understanding of commonly used scripting languages and is expected to support the steady evolution of improved Data Quality, […]

Fundamentals of Data Virtualization

Organizations are increasingly employing innovative technology called “data virtualization” (DV) to tackle high volumes of data from varied sources. Data virtualization is widely used in enterprise resource planning (ERP), customer relationship management (CRM), and sales force automation (SFA) systems to collect and aggregate multi-source data. From multi-sourced data acquisition to advanced analytics, this technology seems […]