Tap the Opportunities of Business Intelligence and Big Data
Business intelligence (BI) and business analytics are topics with a great deal of potential, since they promise companies the ability to make perfect decisions based on thorough analyses and accurate forecasts. Big data – with a huge variety of information and new technologies – brings companies even closer to achieving this goal. Executive boards, IT departments, and user departments spend time examining innovative ideas and application scenarios in this field. However, apart from the technical challenges of implementations, there are hurdles in the area of data protection and data security. And these must be identified and addressed. This is precisely where canacoon comes into play with its consulting services.
The Significance of Security and Data Protection for Big Data and Business Intelligence
The two aspects of data protection and IT security play a fundamental role, for example in the area of HR analytics, but also for many customer data analyses. With regard to data protection, the following questions are often asked: What is permitted? What is executable and tenable? What framework do current and future, national (German) and international legal regulations, such as the German Federal Data Protection Act (BDSG), the EU Data Protection Ordinance, or – in particular – the CoC – Data Protection for the insurance industry provide? What additional measures need to be put into place to ensure the technical and organizational security of the data required? Even today, many companies are still dodging these questions and do not perform the necessary analyses or accept the risks, which in most cases still tend to be underestimated. As a result, they leave potential for improvements – with regard to both employees and the company – untapped. But those who are willing to tackle the challenges of such analyses and implement the resulting measures today, and thus find acceptable solutions, will gain competitive advantage and stay ahead of the pack. The tactic is therefore to use security and data protection to achieve success.
Even if the data is not personal, damage caused by lost information can be immense. Here, big data offers on the one hand many new data categories and on the other hand new potential risks: How much knowledge about a company’s products is hidden in the service and sensor data that vehicles and machines gather? How much knowledge can be extracted automatically from e-mails, social networks, or other sources, for example by competitors or criminals?
The security of data can definitely become a mission-critical issue. If, for example, a great amount of important data is stored centrally in risk analytics systems, an attack may well result in risk assessments and genuine risks finding their way to unauthorized persons or the public, sometimes with serious consequences such as plunging stock prices or rapid drops in sales. How can such systems and architectures – which are becoming ever more complex – be effectively protected from attacks? Authorization concepts are a start, but they only address a very small part of unauthorized accesses and attacks. If the underlying systems are vulnerable – which is true in many cases – and are not monitored for attempted manipulations and attacks, highly critical data could be leaked without anyone at the company noticing.
If, in addition, data is even manipulated and, as a result, the wrong risk decisions are taken, various nightmare scenarios could occur. Although the number of identified and also published attacks is currently relatively low and the number of unreported attacks is presumably high, companies are becoming increasingly prepared to tackle the challenges here offensively and transparently.