Big Data & Hadoop: What’s Cooking?

If you have been following big data, it is most likely you have come across repeated mention of Hadoop. Before we delve deeper into this discussion, let us take a step back in history and understand how data management has evolved and what led to the current scenario where Hadoop and big data are the favored technologies.

Understand Hadoop: The Early Days

Earlier, computing was limited in volumes and in terms of expectations from outcomes. Applications were created specifically for different data structures to ensure that a problem was comprehensively solved. Since computing volumes were humble, this approach didn’t present too many problems. Multiple data resources were uncommon, almost unheard of during this period. Using organizational databases or network data, larger applications functioned rather well. However, the relationship between data structure and application saw a major upheaval with the creation of relational databases.

Due to this, data access to SQL was standardized. More businesses started using spreadsheets. Together, these two developments created the way for more complex data management systems to emerge.

During the 90s, it became clear that there was more business value in combining data from different applications but this was challenging. Slowly, better and bigger data structures surfaced. However, this picture was soon challenged with the arrival of data-intensive business mammoths in the form of Yahoo and Google. Things changed and data didn’t have a similar, streamlined structure. These organizations were handling massive amounts of data on a daily basis, hoping to create a solution for faster access to retrieve and save data. This paved the way for the creation of Hadoop—a more dexterous, organized, and distributed file system that makes it easy to handle unstructured data.

As Hadoop Progressed, Big Data Arrived

Slowly, the advantages of Hadoop became known to businesses across the world. Managers realized that they could benefit a lot in terms of condensing their operational cycles if data access was made easier without compromising its security. The basics of free data management framework that Hadoop had initiated were then routed towards data-driven businesses that wanted data capabilities of bigger organizations.

The Hadoop-Big Data Connection—Hadoop is the platform that makes it easier for unstructured data to be fed into the big data ecosystem. Conventionally, real estate businesses were somewhat selective about retaining data. They feared massive amounts of data will not be accessible. Big data makes it easier to store everything that seems important. With big data, businesses can feel assured that their organizational and consumer data is secured and easily shareable when needed. With big data analysis, the information can be extracted in an orderly, indexed format and then assessed.

Did Google create Hadoop?

Yes, Google can be credited for bringing Hadoop to the world of IT. This happened with Google’s requirement to index enormous amounts of web data, collating, and categorizing it for its search results. Since the market at that time didn’t have a readymade platform that Google could use, it had to innovate. The platform was first called Nutch. Yahoo played a more integral role in helping Hadoop evolve for enterprise applications.

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