Market trends suggest that with an approximate growth of about $7.3 billion in 2018, the big data market size will be bound to break the $40 billion mark by the end of the year. The demanding growth in big data analytics has induced various industries to begin implementing and updating their big data systems to adapt to the higher workloads.
Structured and unstructured data has cracked the world of computational data and analytics into a divide. While algorithms and tools have enabled the easy categorization of structured data, unstructured data is left unsorted due to its complexity beyond the comprehension of simple tools. Unstructured data has been left out of most databases and wasted simply due to the sheer impossibility to classify or structure it into simpler forms.
Increased integration of business intelligence tools:
The implementation of machine learning, artificial intelligence (AI), and neural networks into the working processes of industries have begun to rapidly shrink the gap between structured and unstructured data. The intensive research in the fields of business intelligence is ensuring that all unstructured forms of data are analyzed, organized, scaled, and even used to predict trends which will not just generate viable data but also offer the required advantage for businesses to tap into unforeseen patterns to dramatically improve their key processes. Forrester has predicted that, with more than 70% of businesses integrating AI modules, businesses will have to be quicker and “think on their feet” to quickly tap into the upcoming trends and beat the competition.
The structuring of dark data:
Dark data that has constantly been discarded as unusable and left literally in the dark due to the unavailability of resources or appropriate tools will be streamlined into usable data with the use of these business intelligence tools. By processing and analyzing the old databases as well as that which will be acquired in the future, these business intelligence tools will help detect the often unaware or neglected quality anomalies. This enhancement will not just enable a correction in the business process but also augment the success of many businesses that have lost out on the competition.
Increased impact of IoT:
Further, Internet of Things (IoT), which has thus far proved to have a great impact on big data, will create a greater wave in the transfer of data through sensor technology. Many businesses are benefiting better by cashing in on the benefits of IoT enabled networks as compared to those businesses that are still hooked to outdated forms. An apparent benefactor of IoT would be retail businesses as they would be able to analyze their customer behaviors and other trends in real time through the data generated from their equipped smart stores. A simple sensor on a rack can help with real-time inventory management.
The greater shift from remote servers to cloud storage:
Another component that business will have to adapt to without fail for the success of the integration of these business intelligence tools would be cloud storage. These business intelligence components would cease to exist if businesses fail to utilize either or both cloud storage and cloud computing platforms to effectively collect, analyze or process any data. Accessibility to real-time data without the constraint of limited storage, like that of remote servers, is crucial not just for in-house data but also for the overall smooth management of every component of business intelligence tools.
Checking and updating security protocol:
Most importantly, or rather more obviously, another component that businesses cannot afford to lose out on is security protocol. With the extensive use of cloud technology, security risks are higher, and therefore require the constant upgradation of cutting-edge security measures to fight against cloud security threats. A simple breach could cause loss of sensitive data and repeated damaging attacks that could devastate the business. Business intelligence tools like AI have dedicated protective platforms that could avert a crisis even before occurrence that could otherwise be impossible for a human workforce to even control after a hack.
The need for big data and its smooth integration has been happening at a rapid pace in the past few years, and the current need of the hour is maximum utilization of these resources for a successful and disaster-free future for businesses. With a lot of businesses changing the current from the traditional to technological cores, the constant revision of algorithms is required to gain the edge over competitors. This year is all prepped for data-driven – innovation, discovery, and inventions.