The McKinsey report said: data is being commercialized, and the value is likely to belong to the owners of scarce data, players who integrate data in a unique way, and people who provide valuable data analysis. What do we think of business data analysis? Is it the company’s business data analysts’ calculation after collecting, sorting and presenting all kinds of data? Or does an alpha rhinoceros system come to a conclusion as soon as it runs? So, there are only two types of business data analysis: intelligent and semi-automatic. Small companies rely on manpower to draw conclusions along the analysis theories and methods. Large companies often use various advanced systems to seamlessly integrate data. Once the system runs, many decision-making bases “jump on paper”. Is business data analysis really that simple? We might as well let acloudear, an enterprise operation digital strategic service provider, share the network for you.
Ordinary business data analysis – you can always see the existence of “manual”
Remember that some buddy Tucao knows: a company that learns statistics is caught by HR and make complaints about the list of forms. Can this be business data analysis? It seems more like business data collation. In terms of accuracy, we will put a question mark. In terms of timeliness, managers often can’t wait for decisions. Can the conclusion from this analysis be used? Leaders dare or not? Therefore, non business oriented business data analysis is basically equal to “playing hooligans”. We can understand it by borrowing a picture of knowing close friends.
Business data analysis focuses on working side by side with the business
Even artificial people have to find the right posture and method? With the above posture, the method needs to use four levels of business data analysis of Gartner, a world-famous consulting company, including descriptive analysis, diagnostic analysis, predictive analysis and prescription analysis. In this way, artificial business data analysis can be closer to the truth and more responsible for leaders’ decisions.
Four levels of Gartner business data analysis
Powerful business data analysis — dominated by intelligence
Many small partners want to say that it’s not a new era. In the era of big data, intelligence and cloud computing, it’s still manual, not so troublesome. In this case, we might as well explore how leading business data analysis can help enterprises mine and transform data value through the sap business technology platform [BTP business technology platform] of sap, the management master behind the world’s top 500.
In the analysis layer of SAP BTP platform, we take “analysis cloud” of SAP analytics as an example to understand that ordinary business data analysis can be completed by drawing various conclusions after analysis. What about SAP analysis cloud? It can help enterprises realize integrated intelligence, enhance analysis, predictive analysis and enterprise planning functions. Conventional analysis is pediatrics. Enhanced analysis and forecast analysis are also associated with enterprise plans. Advanced analysis is supported throughout the enterprise. Is it powerful?
Finally, let’s summarize that business data analysis is not as simple as data analysis. Its core lies in that business and business are the real benefits and value points. Business data analysis needs to focus on business, dig into the essence of business, get through and support enterprise and business management, and provide prediction, analysis and plan, so that managers can know the current situation, problems and methods of the enterprise, and provide the most powerful support for scientific decision-making. In other words, conclusions and suggestions that do not have usability are “busy in vain”.
If you want to know more about advanced business data analysis partners, you might as well start with SAP BTP and SAP analytics cloud to improve the value competitiveness of business data.
This article "Business data analysis, intelligent management decision-making route!" by AcloudEAR. We focus on business applications such as cloud ERP.
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