From the era of physical filing cabinets to the age of cloud storage, data management has undergone a radical transformation. Historically, businesses have depended on paper-based systems and rudimentary databases, often leading to slow decision-making and lost opportunities. But the digitization of the late 20th century empowered organizations to amass vast troves of information digitally, giving birth to the era of Big Data.
A significant trend in data management has been the rise of data observability, which is concerned with ensuring data quality. With the exponential growth of data and its increasing complexity, monitoring data to ensure its quality has become more challenging. There’s also a growing focus on data privacy, with techniques like confidential computing and differential privacy gaining traction.
In 2023, the oil and gas sector is battling challenges tied to voluminous and complex data sets. The threat of cybercrime, especially ransomware, continues to loom large. Economic uncertainty is squeezing budgets. And as the process of digitization continues, we’ve arguably arrived at Digitization 3.0, the era in which data must enable on-demand user experiences in an ever-growing array of applications, devices, interfaces, and channels.
But the emergence of new platforms underscores the industry’s dedication to enhancing data observability and quality. And it’s not just about storage: the projected growth of the data warehouse market to $58.52 billion by 2027 reveals a mounting emphasis on real-time data analysis, driven by a pressing need for actionable insights.
Amidst all this, a central tenet remains unshaken: the indispensability of structured data. For modern businesses, structured data doesn’t just streamline operations; it acts as the backbone for AI-powered analytics, predictive modeling, and precision marketing. So let’s take a trip and uncover why such data structuring, whether through data management platforms (DMPs) or data warehouses (DWs), is vital for businesses looking to win the Big Data race.
