The 5 challenges Big Data faces

Vector ITC, Spanish technological and digital group, points out that Big Data is one of the most important technological trends for the digital transformation of companies, as it has represented one of the greatest impacts in different economic and business sectors. The application of this type of technology is varied and ranges from decision making, through customer segmentation, to the drastic increase in productivity. For example, 53% of companies worldwide have substantially improved their customer service thanks to this technology.

However, despite the fact that investment in this type of technology does not stop growing, the reality is that 65% of projects based on Big Data launched in Spain end up failing. The reasons are due to the scarce technological and formative preparation of the companies, or for not having external experts to help design and monitor this type of innovations. Added to the fact that the digital transformation in Spain is progressing, but at a medium pace, companies must analyze the challenges posed by Big Data and determine how it will impact on each of their processes when implementing it. In this sense, Vector ITC points out the following challenges:

  • Need for talent: The advance of Big Data in recent years has been so rapid and has impacted in such a way that professionals in this field have become the most coveted by companies. Data scientists are among the highest paid experts in the industry. This is due to one of their main functions, which is to analyze large volumes of data with different technological solutions to determine if the information is valuable, with the aim of improving different types of processes in the company.
  • Data quality: One of the most important challenges when implementing Big Data solutions is ensuring that the information being analyzed is accurate and relevant to the business. Although this process slows down reporting, it will be critical to ensure that the ideas to be implemented are based on relevant information.
  • Cybersecurity: The storage of data, especially those that are classified as confidential, is often one of the most attractive targets for cyber attacks. Companies must ensure that their data repositories, whether on physical or virtual servers, have the necessary security measures to prevent theft, kidnapping or even destruction of information.
  • Regulation: Most of the information that companies store is confidential or private, so it is important to comply with certain legal frameworks specific to each industry when storing and analyzing data. As a consequence of the rapid advance of technologies in Big Data, companies must guarantee the protection and circulation of their own and customers’ data with the latest regulatory codes such as the General Data Protection Regulations.
  • Dynamic Change: The constant and rapid development of technology forces organizations to rethink the possibility of investing in Big Data tools. Without a correct analysis of the processes to be streamlined or the costs to be saved, can result in a bad implementation, causing a loss of money, time and obsolescence in the short term.

“Big Data offers companies the possibility of obtaining detailed, reliable and deep knowledge to make smarter and less risky decisions. The crucial importance of this technology does not lie in storing a large volume of data, but in knowing how to analyze them in order to extract the maximum value from them. Companies must first consider for what type of processes they need to implement data analysis solutions and what challenges their implementation presents, with the aim of reducing costs and increasing business profitability,” says Rafael Conde del Pozo, Director of Digital & Innovation at Vector ITC.

Vector ITC has extensive experience in the application of Big Data technologies, with the aim of being adaptable to the business of each type of company. In addition, it has integral solutions for the analysis of great volumes of data, fundamental for the efficiency of the processes, the improvement in the taking of decisions and the reduction of costs for each company.