While it can be tempting to think about "the good old times" of data management, the reality is that the scale, complexity, and speed of today's data landscape make traditional methods inadequate. Here are the 5Vs to remember:
🧑💻 Volume: the sheer amount of data being generated today is staggering. IDC predicts that by 2025, the global data sphere will grow to 175 zettabytes. To put this into perspective, if you store them on DVDs, it would require a stack that could reach from Earth to the Moon and back over 60 times! Traditional data management systems simply can't handle this volume.
👩🏽💻 Variety: in the past, most data was structured and relatively easy to manage. Today, data comes in a wide variety of formats – from structured data to unstructured data like emails, videos, social media posts, and more. Managing this variety requires more advanced systems.
👨🏻💻 Velocity: data is being generated at an unprecedented speed. Think about social media posts, online transactions, IoT devices - all creating data in real-time. Traditional methods are not equipped to process this data in a timely manner.
👩💻 Veracity: with so much data from so many sources, ensuring accuracy and reliability is a significant challenge. Traditional data management practices don't have the mechanisms to deal with this issue effectively.
🧑🏿💻 Value: Data has become a valuable resource for businesses, offering insights that can drive decision-making and strategy. However, extracting value from vast amounts of diverse data requires sophisticated analytical tools and approaches that were not part of traditional data management.
In short, while traditional data management served us well in the past, the demands of today's data-driven world require more advanced, flexible, and scalable solutions. In DataEnq we look back fondly on those old ways of processing data but are excited about the prospects for data management in the modern world 💫
Comments