How do I analyze big data quickly

3 possibilities of big data analysis

(Guest author: Dr. Alexander Beck)

Big data is on everyone's lips, but apart from the immense mountains of data that everyone sees in front of them, it is above all the possibilities of data analysis that make our eyes widen. But what do these possibilities actually look like?

Descriptive - What happened so far

Scientist Dr. Michael Wu told Information Week that this type of data analysis is the simplest of the three types. This is how it is filtered out from huge mountains of big data how something went. Wu estimates that around 80% of all current company analyzes consist of such data. No wonder, for example, Google Analytics offers exactly this kind of data. How many visitors were on a website and what they did there - Google Analytics tells us.

What's the point?

With descriptive analytics, companies can find out whether campaigns were successful, whether user numbers have increased, how users behave, etc.

Predictive - what could happen

With predictive analytics, it is possible to take a look into the future with the probability of occurrence for certain scenarios. This is comparable to a weather forecast compared to a weather report, with the latter corresponding to classic business intelligence.

However, not all scenarios from everyday business are equally suitable for use in predictive analytics methods. Factors that are decisive for success can be identified by taking a look at the 4 Vs:

  • Volume - is there enough data?
  • Velocity - do processes take place frequently and quickly?
  • Variety - is there a noticeable fluctuation in the characteristics of a process and are there also influencing factors that show a high degree of variability?
  • Value - does an improvement in a process have a business-relevant impact?

If these factors are given, the chances are good that a profitable predictive analytics can be developed from them.

What's the point?

Companies can use predictive analytics to optimize repetitive business processes. In other words, predictive analytics cannot predict unforeseen events, but it can predict tendencies of repetitive things.

Prescriptive - What to Do

Prescriptive analytics can only be used profitably if forecasts are converted into decisions. Different probable scenarios are compared, consequences are determined and recommendations are given as to which scenario could produce the best possible results (for example the purchase of a product).

What's the point?

Companies can use prescriptive analytics to make improved decisions on an ongoing basis. With prescriptive methods, individual decisions can be continuously optimized. In a holistic view, this then leads, for example, to increased conversion rates, increased customer satisfaction, reduced costs or increased sales.

Dr. By the way, Alexander Beck also explained in an interview on the subject of analytics what is possible with analytics and where even the best customer data has its limits.


Use analytics methods to increase your campaign success. In our recording, our AI expert explains how it works and what's behind it.


Dr. Alexander Beck is Manager Professional Services at the management consultancy ec4u ag. There he is responsible for the area of ​​data science and artificial intelligence and leads various projects on this topic. He has been working on data-driven decision-making and the intelligent automation of business processes for over 10 years.

You can contact him on LinkedIn.