Are you truly doing advanced analytics or simple business intelligence?

Advanced analytics and business intelligence are two distinct capabilities that enable organizations to make better decisions. Advanced analytics is a more futuristic approach to data analysis that uses complex algorithms, machine learning, predictive modeling, and other cutting-edge techniques to uncover insights in data that can inform strategic decision making. Business intelligence (BI) focuses on providing near real-time access to information so leaders can make decisions based on a current snapshot of data.

Advanced analytics is best suited to discovering patterns and uncovering insights that could not be obtained through traditional BI methods, such as capturing customer trends and predicting future outcomes. Advanced analytics requires expertise in mathematics, statistics, computer science, and data mining. By leveraging advanced techniques like natural language processing (NLP), predictive modeling, and clustering algorithms, advanced analytics can reveal patterns in data that may be hidden beneath the surface.

Business intelligence is a more traditional approach to making decisions through data analysis that focuses on providing access to data in near real-time so leaders can make informed decisions based upon current trends. With BI, organizations are able to track key performance indicators (KPIs), analyze customer behavior, and identify areas for improvement. BI is used to find data-driven solutions to everyday problems and ensures that the organization is making decisions with up-to-date information.

Advanced Analytics is not business intelligence.

Business intelligence is operational, it visualizes questions you know to ask.

Advanced analytics is science, it surfaces questions you didn’t know to ask.

Advanced analytics uses machine learning to find correlations and patterns your current technology can’t show you.

Advanced analytics requires clean data.

Data lifecycle management is the discipline that enables advanced analytics.

A Data Strategy is a strategic approach to develop an organizational capability with advanced analytics.

A Data Strategy helps you navigate in a digital economy.

Ultimately, the goal of any data analytics program should be to identify patterns in data that can help inform decisions and solve everyday problems. Advanced analytics and business intelligence offer distinct capabilities that, when combined, can give organizations a more holistic view of their operations. By leveraging both advanced analytics and business intelligence together, organizations can make informed strategic decisions based on comprehensive data-driven insights.

We think it’s simple – not easy, but simple. Let us show you how.

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