Read more about co-authors Alexey Utkin and Oleg Royz. For years, organizations have invested heavily in dashboards, data warehouses, and centralized reporting platforms. Yet many still struggle to turn their growing volumes of data into real business results. The problem isn’t the data, it’s how we think about it. Business leaders must treat data not merely as an asset to be stored and queried, but as a product – something…

This is the second in a two-part series exploring data quality and the ISO 25000 standard.  Read more about author Mark Cooper. OK. You’re with the program. You recognize that having quality data is important for accurate AI models. You would even concede that it’s important for other stuff too, but whatever, because AI is getting all the attention right now. You want to start publishing data quality metrics. All…

Read more about author Neha Das. In today’s data-driven business environment, enterprises are increasingly relying on sophisticated data migration strategies to manage and move vast amounts of information, particularly unstructured data. As enterprise IT infrastructure evolves, so too does the complexity of data migration. The scale, speed, and accuracy required to successfully migrate large datasets – often containing billions of files – pose significant challenges. These unstructured data migrations, when done…

Read more about author Tejasvi Addagada. Data has evolved from a back-office function into a central driver of innovation, customer experience, and regulatory compliance. Yet, many organizations still apply a one-size-fits-all approach to data governance frameworks, using the same rules for every department, use case, and dataset.Here’s the issue: What works for managing a legacy HR system doesn’t work for a real-time fraud detection model. Governance journey needs to be…