Big Data? and its importance today.

When we talk about Big Data, we’re referring to the massive and complex data sets that traditional data management systems can’t handle. When properly collected, managed, and analyzed, Big Data can help organizations uncover new insights and make better business decisions.

As we know, business organizations have been collecting data for a long time. The advent of the Internet and other connected technologies significantly increased the volume and variety of data available, giving rise to the concept of “big data.”

By 2025, companies are collecting vast amounts of data, often measured in terabytes or petabytes, on everything from customer transactions and social media impressions to internal processes and self-research.

Over the past decade, this information has driven digital transformation across all industries. In fact, big data has earned the nickname “the new oil” for its role in driving economic growth.

What is the difference between traditional data and big data?

Traditional data and big data differ primarily in the types of data involved, the amount of data handled, and the tools needed to analyze it.

Traditional data primarily consists of structured data stored in relational databases. These databases organize data into clearly defined tables, making them easy to query using standard tools, such as SQL. Traditional data analysis often involves statistical methods and is best suited for data sets with predictable formats and relatively small sizes.