Equating the Advantages versus Disadvantages of Big Data

While we have discussed in detail the various characteristics of big data, the world needs to know more about the advantages that are associated with the field and how these easily outweigh the disadvantages or limitations.

It is a remarkable phase for the global business scenario where almost everyone in the industry has either worked with Big Data projects or at least heard of the technology capabilities related to Big Data. In the modern data driven world, Big Data capabilities are seen as the most important component for innovation, engineering, and development of both traditional business practices as well as the newly emerging ones, especially in IT and Software application development. Today, simply understanding the characteristics of Big Data could help to promote the adoption of emerging technologies across diverse industries such as healthcare, e-commerce, and retail, media and entertainment, Banking and finance, education, governance, manufacturing, and logistics.

Let’s discuss.

According to major industry research on Big Data intelligence and analytics, businesses of all sizes and types can leverage Big Data benefits for their various processes, and the advantages are directly applicable to gathering and analyzing new forms of data for enabling enhanced decision making in real-time and deploying new capabilities for process optimization, revenue maximization and cost cutting across the organization.

Let’s list down the benefits of big data characteristics briefly here.

Big Data Teams Now Focus on Quality of data rather than just Quantity or Volume

Big data teams traditionally have been trained to work with a very large or complex set of data that require them to adopt complex data processing applications, such as ETL systems to manage the 4Vs of Big Data. In the initial phase of the data processing cycle, rapid analytical needs force teams to overlook the historical relationship of the data sets with the processes. This often leads to disruptions in the subsequent data management processes. Therefore, we are now seeing big data teams switching their attention to the quality refinement of data, starting with mining, extraction, and analytics.

The biggest advantage of working with high quality Big Data lies in its ability to readily transform any industry into a digital-savvy ecosystem. Video marketing and B2B finance are the biggest examples of this transformational journey, and so are the whole employee experience and working from home platforms. Right from Zoom to Amazon, everyone in the industry uses a highly advanced Big Data platform to provide the best experiences to their employees, partners, customers, and so on.

Saving Cost of Failure

Big Data seldom comes with a failure linked to its projects. 99% of the big data projects are perpetual systems that allow everyone involved in the tasks to continuously make improvements and therefore, big data companies are assured of breakeven sooner than other industries, in addition to sustainable revenue over the course of time. Big data projects get absorbed in the development of software and applications that are used for real time analytics, business intelligence, marketing data research, and cloud modernization. In fact, all these come together within an organization to save costs of outdated processing and manual operations.

From time reductions to providing better predictive insights on the business outcome, there are advanced advantages of using big data tools like Hadoop and others. However, it’s the ease with which new learners can quickly understand the fine nuances of big data and related techniques that makes the industry such a positive one for the hiring marketplace.

Limitations in big data

The biggest limitation is the lack of qualified trainers and learning resources. We are still reeling under intense pressure from the market’s demand for highly trained and talented big data leaders. The IT analysts and BI staff double up as trainers, forcing the talent market to lose on traction growth in the research that goes into taking the industry to next level. Secondly, big data staff has to deal with a lot of ambiguity in the way organizations fail to tap into open source communities that seem to have a great liking for certain practices in Python and R programming languages. With the best online course, we can recover from these disadvantages and turn these into opportunities.

Related Articles

Back to top button