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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 […]

Data Catalog, Semantic Layer, and Data Warehouse: The Three Key Pillars of Enterprise Analytics

Analytics at the core is using data to derive insights for measuring and improving business performance [1]. To enable effective management, governance, and utilization of data and analytics, an increasing number of enterprises today are looking at deploying the data catalog, semantic layer, and data warehouse. But what exactly are these data and analytics tools […]

Elements of a Modern Data Warehouse

Businesses are generating vast amounts of information every second. Traditional data warehouses, which were once considered the gold standard for handling and analyzing large datasets, are struggling to keep up with the rapid pace of data growth and evolving analytics requirements. This has given rise to the concept of modern data warehouse, which provides a […]

The Fundamentals of Data Integration

Data integration uses both technical and business processes to merge data from different sources, helping people access useful and valuable information efficiently. A well-thought-out data integration solution can deliver trusted data from a variety of sources. Data integration is gaining more traction within the business world due to the exploding volume of data and the […]

Distributed Data Architecture Patterns Explained

Distributed data architecture, models using multiple platforms, and processes for data-driven goals continue to generate increased interest. As William McKnight, president of McKnight Consulting Group (MCG) and well-known data architecture advisor, says, “Seldom a database vendor does not interact with concepts around distributed data architectures: the data lakehouse, data mesh, data fabric, and data cloud, and I am […]

What Is a Data Warehouse?

A data warehouse is a centralized repository that stores and provides decision-support data and aids workers engaged in reporting, query, and analysis. Data warehouses represent architected data schemas that make it easy to find relevant data consistently and research details in a stable environment. Data sources, including data lakes, can pipe data to a data warehouse. […]

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.  […]