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 […]
Data Warehouse vs. Database
What are data warehouses and databases? How are they different, and when should you use a data warehouse vs. database to store data? Below, we will look at the differences and similarities between them. What Is a Database? In a database, data is presented in a structured manner for easy access and manipulation. Vast amounts […]
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 Data Warehouse Development Lifecycle Explained
The desire to leverage data as a strategic asset has led to the development of sophisticated systems and methodologies that go beyond basic data storage and retrieval. Among these advancements is modern data warehousing, a comprehensive approach that provides access to vast and disparate datasets. The concept of data warehousing emerged as organizations began to […]
Data Provisioning: Ingest, Curate, and Publish
A collection of facts from which inferences can be made is called data. It is the basis on which factual information is derived, providing relevant results to the end users. Data is the cornerstone of contemporary society and is crucial to many facets of people’s lives. In order to gain knowledge and make wise decisions, […]
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 […]