In a time when big data is becoming more and more important, businesses are seeking new and better ways to create and change the way data is being managed and analyzed. Previously, businesses would pile up and send their data to several different business systems, such as their ERP or a transactional business system. However, because each businesses has their own ERP and use different business systems, it increases the chances of misreporting data, which in turn, effects the business as a whole. According to the Harvard Business Review, on average less than half of an organizations structured data is actively used in decision-making, with less than 1% of unstructured data used at all. Inefficiency is also rife: as much as 70% of analysts time is spent on discovering and preparing data. Two important technologies that are helping the advancement of data analytics and reducing the risk of misreported and inaccurate data are cloud and machine learning.
Cloud allows enterprises to move their data from any of their business system to the a cloud, basically making it a centralized location for all of the data. Because of all of the data that is being stored in the cloud, it can serve as a medium for collaboration between different departments of the business. This will speed up data deployment and will lower maintenance cost for the business. Cloud is already predicted to have half of the enterprises using a cloud-first approach this year. According to Brian Hopkins, an analyst at Forrester Research, an increasing number of technologies are available for processing data in the cloud.Some examples of these technologies would be IBMs Bluemix cloud platform and Amazons Redshift data warehouse. One very powerful cloud-based platforms is SAPs HANA. HANA can be used as an on-premise or used in the could, which helps businesses bridge the gap between their historical data and the real-time data. Of course there are still concerns about the cloud. People do worry mostly about cyber attacks, which are becoming more and more popular, and other things, such as government invasion. However, more often than not, businesses do not have qualified cloud developers that know how to make the cloud secure or it occurs internally within the business. In actuality the data being stored in a cloud is being encrypted which makes it much less likely that a hacker could get to the data.
Machine learning is the other advancement in technology in regards to data analytics. Machine learning is basically just automating the data. Because of how important big data is becoming, there is astronomical amount of data that needs to be analyzed and it would not make sense to hire an absurd amount of employees, that is where machine learning comes into play. Of course machine learning is not a new idea, but because technology evolves, so does the idea. When this idea first came about, its theory was that, computers can learn without being programmed to do specific tasks, in other words, the computers learns from the data. Due to recent developments in machine learning, it is now able to apply complex calculations over big data, faster than it ever could before. Machine learning is important for businesses to have because it allows them to analyze bigger and more complex data faster than it ever could, giving more accurate results. Some Examples of machine learning you may be familiar with:
1. Self-Driving Google Car
2. Online recommendations (e.g. Amazon)
3. Fraud detection
A very important concept for any business to understand is what does their customers want? With all these technological advancements happening, businesses are obtaining more and more data regarding the customers habits such as what they do, what they want, when they want it, and so much more. With all this information about their customers, business are able to increase their profits and revenue.