Business analytics is used by companies, which are committed to data-driven decision making. It is the practice of iterative, methodical survey of an organization’s data with a focus on statistical analysis.
Business analytics (BA) forms the basis for making important decisions, as it provides the useful insights and can be used to automate and optimize business processes.
Data-driven companies treat their data as a corporate asset and leverage it for competitive advantage. Successful business analytics depends on data quality, skilled analysts who understand the technology better, and an organizational commitment to data-driven decision making.
Business analytics can be used for:
Once the business goal of the analysis is determined, an analysis methodology is selected and data is acquired to support the analysis. This is where big data analytics becomes effective, which is more than just managing diverse data, asking new questions or formulating hypotheses. Moreover, it involves the close examining of the colossal of information to give a deep insight to help in data-driven decisions, using new analytics techniques, on either new data or data that has been combined in new ways and thus giving a competitive advantage to the organizations over their competitors.
Business analytics (BA) forms the basis for making important decisions, as it provides the useful insights and can be used to automate and optimize business processes.
Data-driven companies treat their data as a corporate asset and leverage it for competitive advantage. Successful business analytics depends on data quality, skilled analysts who understand the technology better, and an organizational commitment to data-driven decision making.
Business analytics can be used for:
- Exploring data to find new patterns and relationships (data mining)
- Explaining why a certain result occurred (statistical analysis, quantitative analysis)
- Experimenting to test previous decisions (A/B testing, multivariate testing)
- Forecasting future results (predictive modeling, predictive analytics)
Once the business goal of the analysis is determined, an analysis methodology is selected and data is acquired to support the analysis. This is where big data analytics becomes effective, which is more than just managing diverse data, asking new questions or formulating hypotheses. Moreover, it involves the close examining of the colossal of information to give a deep insight to help in data-driven decisions, using new analytics techniques, on either new data or data that has been combined in new ways and thus giving a competitive advantage to the organizations over their competitors.
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