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Within the space of a few years, the world of technology has changed immensely. We now live in a world that is intensely complex, immensely competitive, and increasingly more difficult to grasp and comprehend. People have now become vastly more connected and the remnants of their day to day actions are leaving an increasingly baffling size of digital footprints. For businesses, the need of the hour is to collect and make sense of this large volume of rapidly changing and evolving data. Only with better understanding and processing of this data, will businesses be able to derive powerful and actionable insights which can then be delivered to the point of action in due course.
As two needs that keep mutually feeding each other, the need for better technologies concerning Big Data and the emergence of those technologies have happened at roughly the same point of time. As a consequence, businesses now have more power to gain the insight that they desperately require to listen to customers and use those insights to reach new heights of growth. With these abilities, comes the prospect of being able to shape and mold their current market as per their goals, and to enter other new, exciting markets as well.
The Dilemma of Big Data
Big Data and its understanding have now evolved from a nascent stage. Hence its consequences make it prudent for one suggestion – that it can deliver a range of competitive advantage to any business. Those that harness and leverage it properly can expect stellar results, and those that fail to do so risk falling behind in the competition and eventually becoming outmoded. According to many industry leaders and forward thinking visionaries, Big Data has already effected a massive change in the business machinery, pushing traditional boundaries and allowing several providers of non-traditional nature to make headway into industries. Over half of the leading companies around the world expect to face tough competition from data driven startups. This “survival of the fittest” scenario can have various domino effects, and one of its sure consequences has been the emergence and rise of data driven corporate machines.
How Data Driven Insights can Change Business
Businesses in this day and age realize that data insights are extremely valuable as far as their fortunes are concerned. Investment in developing and using Big Data related technologies is set to spike in the coming few years – a fact that amply shows that businesses are willing to do what it takes to gain the maximum out of the Big Data boom. Data insights can change business in many different ways, which include –
- Bringing in innovations which foster better efficiency and lesser costs to give rise to a more cost-effective, streamlined approach to business.
- These insights can help businesses obtain superior quality of information, which facilitates better plans of growth and prosperity within their current niche.
- Additional revenue streams can be explored and deployed with the help of Big Data.
- There is the prospect of monetization of raw data being a separate area of business in and of itself.
Basically, data driven insights can provide organizations with better quality of information. This information can then be used to craft effective expansion and revenue generation campaigns that are more likely to succeed both for the short and the long haul. With the additional scope and potential provided by Big Data, businesses can expand their own scope, capture new areas of the market and make their routine processes much more cost-effective.
Working on the basis of data driven insights also helps businesses make themselves future proof. It allows them to continue to evolve and change themselves proactively, corresponding to changes in the market, in customer behavior and other factors. When businesses are able to reach such a state, they will be aware in advance about possible changes in the market, be able to forecast trends better and stay on top of their competition effectively.
Corporate Machines Driven by Big Data
At present, the advent of Big Data has gone on to suggest that we might be nearing a second Machine Age which will usher in new developments and exponential change. The crux of the matter is whether or not Big Data will go on to prove to be a transformative technology. Many other technologies of the past had started out with similar projections but did not live up to the things that were expected of them. Whereas it is hard to predict the fate of Big Data currently, early signs have been extremely promising.
Big Data has so far been a successful avenue to pursue when it comes to activities like internet marketing and advertising. In comparison with these fields, its importance in other areas is still a matter of waiting and watching. There have already been certain promising developments in the field of various data driven disciplines including application management, agriculture and healthcare. However, there is a foreboding mood that most of its potential is yet to be realized.
What is keeping us back?
The main stumbling block in this regard is still the human factor. After the mass digitization that the world has gone through, it is obvious that data is being produced at a high rate every second. The analysis of that data, however, is still within the domain of human intelligence. Since humans are always limited in some way or the other in their physical, mental and intellectual capabilities, this has caused a bottleneck of sorts. Human labor in this regard also seriously limits the financial scope of businesses, forcing them to invest more to satisfy this need and less towards other areas which might be equally important with respect to their eventual success.
The right answer to this conundrum, according to technologists, is the process of automating intelligent operations. Hot topics like predictive analysis and machine learning are the order of the day at present. In recent times, these are the concepts that have found a more cemented place in the daily order of business in many companies. Intelligent machines that can take over tasks of data crawling and data extraction, but also intelligent processing of that data and the development of data insights can truly be considered viable, value-adding assets for any business.
How Data Driven Machines have Taken Over
The world has already played spectator to some exciting, innovative new uses of data driven, automated machines in various fields. Their meteoric rise indicates that there is a lot more in store when it comes to machine learning and predictive analysis, and the enormous potential of automating intelligent operations is set to be a lasting force in the market and the world at large. They are currently being actively developed and used in many different fields of industry for multiple purposes.
At its heart, there are many important factors which have warranted the rise of data driven corporate machines. Some of the more compelling ones are –
- Computers and supercomputers have become more compact and powerful, coinciding perfectly with the need for them to crunch more and more data. This symbiotic relationship is at the root of the rise of data driven machines for business use.
- The creation of data which is more diverse and clients that are getting progressively more untethered has helped the cause. The exponential levels of improvement like those that we can see in the quality of smartphone hardware and processing chips can bear solid testament to the fact.
- The combination of different technologies in new, innovative ways has opened up new horizons in the field of data processing. These interesting mixes have started providing more value than ever before.
- Developments like better artificial intelligence systems, the concept of autonomous vehicles and smart cities, and the many other examples of smarter machines and smarter software provides an accurate estimation that great things are on course when it comes to data driven technology.
Implications and the Way Forward
Now that data driven corporate machines have made a firm place for themselves in the scheme of things when it comes to providing businesses value and direction, there are a lot more avenues just waiting to open up. At its heart, the focus is slowly shifting from more reliance on human intelligence towards creating more efficient machines to take its place almost entirely if not fully. The immediate implication of this is a boost in efficiency, speed and value. It also open up a lot of time and opportunity for the human workforce to work on further fine-tuning and streamlining of the system.
Whether data driven corporate machines are here to stay is a question that only the future can reveal the answers to. With the small steps that have become apparent of late, the indication is that these machines will grow in scope, versatility and responsibility over time and will be able to aid society in many new ways. The only proviso is that the correct applications and continuous development and growth in this sphere must be kept going for them to reach a truly transformative status.
