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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Yes! Data is Relevant Across the Mortgage Industry

Some folks might say that the operational basics of every business are essentially the same, but significant differences can exist. For instance, the manufacturing industry depends upon its performance to gauge its index of quality. Here, quality refers to the processes through which components are assembled and overall quality of these components. However, in the mortgage industry, data is evolving as the most important component. Here, products are the decisions based upon this data.

Understand the Issue: Data Perception among Bankers and Investors

It is generally believed that "Big Data" is beyond the reach of small to medium-level businesses. This notion is driven by the fact that corporations like Google and Facebook have pioneered the cause of being data-driven. Such brands look upon data as their most valuable resource. Many mortgage industry professionals look at cloud-based data and analytics with circumspection. They are not sure whether these data-driven technologies are useful for managing their day-to-day challenges. However, if looked closely, it becomes evident that these technologies are capable enough to find out meaningful processes and facilitate growth.

Is data the cure for all mortgage industry ills?

To be brutally honest, the answer is NO! Typical roadblocks towards using data efficiently are yet to be addressed. For instance, loss of data integrity shows no signs of abating. Many data mistakes might originate from the lender. This is where established dynamics of the industry come to the fore—sales being aggressive and often ignorant of quality or safety standards. To realize the true potential of data, the industry has to think beyond loan and risk performance. They will have to work towards ensuring accuracy of data incorporated into their database.

The Evolving Industry Shift towards Data

Since the economic crisis of 2008, the mortgage marketplace has become more introspective. The industry might not be using data robustly but it is exploring the utility of investing in big data. Investors have traditionally relied on performance of loan-term as the primary benchmark. Data analytics can provide insight beyond this aspect. Data can facilitate access to lesser-recognized factors. This can help industry regulators and investors in better evaluation of securitization or compliance. Data provides useful analytics that helps to achieve better accountability and well-informed decision-making.

The visible progression is towards creating a more comprehensive dataset. This will eventually make governance more effective. However, this is a colossal shift for an industry that has been primarily driven by financial assets. The changing perspective towards looking at data as an asset will take time. However, the change is underway and very palpable. There have been some slow-downs in the way.

 

Several regulations have been introduced that push towards adopting a more data-tolerant attitude. However, a lag is indicated since all organizations cannot jump on to the big data platform immediately. The big change lies in organizations becoming more open towards collaborating data. This is the first step towards creating uniform data that can be used seamlessly across the mortgage industry. This will help to create more effective home-finance regulations.