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SAP Analytics: solid data is imperative to make sound business decisions

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Data is precious only if it’s worked upon or analysed; it doesn’t offer much insight on its own. And data becomes valuable if it’s related to a particular marketplace. Moreover, facts alone don’t suffice to make good business or professional decisions. However, decision-making is no easy task in the modern business environment even if you have significant clarity pertaining to your firm’s purpose and vision.

To make good decisions, good data is imperative. But as data can be sourced from multiple avenues and are available in different formats, working with the information on hand can be difficult. Also, data management is getting increasingly automated. Fortunately, SAP Analytics portfolio that was made public at SAPPHIRE NOW, a SAP user conference, can help.

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Trust is Key

Generally, as optimisation or predictive models such as SAP Analytics get introduced to assist manual decision-making, the entire process starts with a proposed decision. This permits the decision-maker to go through the options and arrive at the final decision. Since decisions turn out right for businesses with time, people start trusting the process and the outcome, letting more automatic decisions to be made using machine learning models such as SAP HANA.

There isn’t any particular formula for the types of decisions to make depending on machine learning or automated processes, versus decisions that humans must make using data analysis. At the end of the day, machine or automated learning algorithms are naturally probabilistic. There isn’t any guarantee that the results would come out as expected.

 

For instance, when incorporating algorithms for making medical decisions, doctors must realise their decisions are “machine-assisted” and they would have to take up responsibility ultimately. For example, information could be modelled to locate patients who are most likely to benefit from a particular medicine. Physicians could then prepare a prioritised list of people who may find the specific medication beneficial. In such cases, machine learning could augment the doctor’s productivity and success probability, but no guarantee can still be made on the medical treatment's outcome.

 

Trustworthy and Futuristic Analytics

SAP manages business processes for a variety of companies, of different sizes and within a wide range of industries. In fact, more than 75 percent of the global transactions happen on SAP tools. With time, SAP has created a comprehensive solution set that helps deal with all data forms irrespective of their variety, velocity, and volume.

 

For example, natural disasters cannot be prevented, but using high-performance processing capabilities of database platforms such as SAP HANA, disasters resulting from natural phenomena could be predicted. In addition, increasing development in information technologies such as big data, blockchain, and IoT (Internet of Things), solutions such as SAP Leonardo lets firms to capture, assimilate, and examine high-speed streaming information.

 

Huge volumes of different data types could be seamlessly merged with transactional information from applications like SAP Leonardo. This lets customers acquire a consolidated perspective of their firm by aggregation and analysis of information from different sources and putting them out in a format that’s actionable and also comes with drill-down abilities as witnessed in SAP Digital Boardroom.

 

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