Technology is growing at an astonishing rate and consequently shaping the world of business. However, only a business that is willing to embrace such changes is bound to make it big or rather achieve competitive advantage over the rest. Specifically, data warehouse architecture has experienced tremendous changes in recent years that businesses can take advantage of in today’s time. Such changes, if utilized accordingly, can significantly and positively impact the way business is conducted besides driving changes in other areas of the company. Advanced analytics is one key development that has been witnessed as far as data warehouse architecture is concerned. This technology is well described as a broad classification of inquiry which can be used in helping to drive changes as well as bringing improvements in the practices of a business. But, what difference exists between the traditional analytical tools and the advanced ones?
Basically, the traditional tools, which are made up of business intelligence, usually examine historical data. On the other hand, advanced tools normally focus on predicting future events, as well as behaviors. This, in turn, allows businesses to carry out what-if analyses which help them in forecasting the impacts of possible changes in business strategies. This is, in essence, tremendously beneficial to any company that aims at shaping its practices in line with potential changes.
Major analytical categories
Some of the analytical categories that fall under advanced analytics heading include data mining, predictive analytics, location intelligence and big data analytics. These categories are the most popularly applied ones in businesses and organizations. They are actually widely applied in many industries ranging from healthcare, marketing, risk management as well as insurance. While doing such complex analyses demands a team of highly experienced statisticians, these new tools coupled with data visualization technologies have facilitated easy access to predictive modeling by the average user.
Perhaps the most notable thing that businesses must exercise to reap optimal benefits while using this new technology is to ensure an integrated approach to issues of data sourcing, organizational transformation and even model building. This is how business managers and the rest of the concerned employees can avoid the popular trap of beginning with the data and then wondering of what benefit it can do for the company. In this regard, business leaders should consider investing enough time and energy in the task of aligning managers in the organization to be in support of the mission. If they are able to manage this, the technology will prove beneficial to business of any type and size.
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