Data management seems to be a field in flux nowadays. Old habits (data warehouses) die hard, while new ones (data virtualization and data mesh) prove difficult to understand and implement. The logical data warehouse emerges as a concept that brings everything—the old and the new—together.
Not every organization can afford a data warehouse or need the full suite of data warehouse capabilities. There must be another solution other than enterprise-grade products for the data integration needs of startups and SMBs. Data virtualization is that solution.
The data needs of a modern enterprise have far outstripped the capabilities of the legacy infrastructure built around data warehouses and lakes. Can a domain-focused, product-oriented concept that empowers employees to self-serve work? Zhamak Dehghani thinks so.
Maximizing the potential of unstructured data requires abandoning the old habits of handling data. This piece takes a look at ETL and ELT methods, examines their strengths and weaknesses, and explains the reasons behind the rising popularity of the latter.
More than 80 percent of data is unstructured today. The software industry has been working on unlocking the full potential of unstructured data for some time. This blog post takes a look at what unstructured data is, its potential use cases, and the associated challenges.
You might have come to appreciate what high-quality data can do for your organization, but achieving it is an entirely different story. This blog post offers readers a few tips to guide them in their quest to improve data quality and become a data-driven organization.
Despite all the talk around 'data,' not many organizations know what to do with it. Good data has certain characteristics, which most of the data organizations have today lacks. This blog post examines the factors that have an impact on the quality of data.
Digital data becoming the predominant form of data is a relatively recent phenomenon, but humanity's history with data goes a long way back. Hop on for a ride with Kelly O'Connor to see how our treatment of data changed throughout history.
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