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A Brief History of Data Quality

The term “Data Quality” focuses primarily on the level of accuracy possessed by the data, but also includes other qualities such as accessibility and usefulness. Some data isn’t accurate at all, which, in turn, promotes bad decision-making. Some organizations promote fact-checking and Data Governance, and, as a consequence, make decisions that give them an advantage. […]

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 […]

Facing a Big Data Blank Canvas: How CxOs Can Avoid Getting Lost in Data Modeling Concepts

The volume of data now available to businesses continues to grow exponentially. When looking to extract valuable insights into their business’s performance, C-level executives (CxOs) must navigate the big data blank canvas. This requires a strategic approach, in which CxOs should define business objectives, prioritize data quality, leverage technology, build a data-driven culture, collaborate with […]