How to Cope with Three of the Most Tedious Big Data Obstacles

Data processing is in itself a simple and straightforward process, but big data can be as intimidating as its name promises.

From the second you start reading this sentence until the moment you reach the end of it, thanks, largely in part, to mobile solutions, cloud computing, and IoT, data has been produced in huge quantities.

The data generated come in all shapes and forms:

Internal and external
Structured and unstructured

What’s even more astounding, there’s no stopping big data from growing.

Big data adoption

According to a whitepaper published in 2017 by research group IDC, worldwide data will swell to 163ZB by 2025, with the majority of this data being created and managed by enterprises. In turn, organizations will be looking to invest heavily on big data campaigns by buying or developing proprietary software, upgrading their servers, and increasing staff headcount with people of high analytic skills, such as data scientists, research analysts, data architects, and business analysts

As more and more organizations embrace big data to power their day-to-day operations and integral decision-making functions, understanding the obstacles inherent in big data is the first step to overcoming them.

1. Data collection

Data is everywhere. For organizations new to big data, one significant challenge is identifying the best possible ways to collect …

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