Big data challenges impacting data-driven business goals
The exponential explosion of digital data has forced researchers to find new ways of seeing and analyzing the world. It’s about discovering new orders of magnitude for capturing, searching, sharing, storing, analyzing and presenting data. That’s how “big data” was born. Big data is a concept for storing a huge amount of information on a digital basis.
Big data refers to a very large set of data that no conventional database management or information management tool can really work. In fact, we produce about 2.5 trillion bytes of data every day. This amount of data come from different platforms: messages we send, videos we publish, weather information, GPS signals, transactional online shopping records and more. These data are called big data or massive volumes of data. The Web giants, first and foremost Yahoo (also Facebook and Google), were the first to deploy this type of technology.
Though there is no specific or universal definition of big data. Being a complex term, its definition varies according to the communities that are interested, user, or service provider. A transdisciplinary approach allows understanding the behavior of the different players: the designers and suppliers of tools (the computer scientists), the categories of users (managers, business owners, political decision-makers, and researchers), as well as professionals.
Big data is a dual technical system. Indeed, it has its benefits and challenges. The arrival of big data is now presented by many articles as a new industrial revolution similar to the discovery of steam (early 19th century), electricity (late 19th century) and computer science (late 20th century). Others describe this phenomenon as the last stage of the third industrial revolution, which is, in fact, the “information age”. In any case, big data is considered a source of profound disruption in society.
Big data is becoming more popular among businesses in all industries and undertaking a big data project is not easy. According to a study conducted by NewVantage Partners, 95% of the Fortune 1000 entrepreneurs surveyed have undertaken a big data project in the past five years, but only 48.4% have managed to benefit from these projects.
Below are some of the big data challenges businesses encounter:
Clearly, one of the biggest big data challenges to overcome is to store and analyze all the information. According to the “Digital Universe” report, IDC estimates that the amount of information stored in computer systems around the world doubles every two years. Most of this data is unstructured, which means that it is not stored in a database. Photos, documents, videos, and audio files are difficult to analyze.
To overcome this challenge, companies can use different technologies to manage the constant increase in data. In terms of storage, converged and hyper-converged infrastructures, as well as software-defined storage, are proving to make things easy to scale hardware. Technologies such as compression, deduplication, and tiering also reduce the space required and the costs for storing big data. With regards to management and analysis, companies can use tools such as NoSQL, Hadoop, Spark and other big data analytical software, as well as business intelligence software, AI and machine learning to get the insights they need.
Businesses do not just want to store the big data they generate. They are more interested in using big data to achieve their goals. According to the study conducted by NewVantage Partners, the main objectives associated with big data projects are the reduction of expenses, the implementation of a data-driven culture, innovation, the acceleration of the deployment of new capabilities and services and the launch of new products and services. These different goals can make companies more competitive, but they need to get insights and exploit them quickly.
