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Advanced Analytics


Advanced analytics allows business managers to solve problems that were previously impossible or extremely difficult to solve. For instance, predicting customer churn, propensity to purchase one product over another, reaction of customers to media, and so on.

Advanced analytics goes beyond standard data mining, where:

  • Traditional reporting helps us understand what happened and to a certain extent why it happened.
  • Data mining identifies patterns and trends in data to help predict what may happen next.
  • Advanced analytics provides a broader contextual insight and interpretation that directly leads business users towards specific actions.

And it is logical-driven action, not analytics that leads a business towards success.

For more differences between standard analytics and advanced analytics.

Advanced analytics digs deeper into the “why” of a given situation, and insightful models of the likelihood of upcoming events, to help business managers better understand the likely impact in six months or more of the decisions they make today.

The impact this has can be dramatic. Being able to identify likely behaviours of suppliers, customers, partners and competitors can translate into very significant cost saving and profit-maximizing decisions. It can also translate into intangible benefits such as increased efficiency and more innovation within an enterprise.

The outcomes of applying advanced analytics can result in a substantive competitive advantage. By using advanced analytics to:

  • Laser target media, thereby attracting the right customers
  • Positioning the right products to those customers
  • Build and retain a strong customer base
  • Gain cost savings through improved stock management and resource management

…organisations grow leaner and stronger.

By applying foresight gained from advanced analytics, actions become proactive, ensuring that every dollar spent earns the highest possible return.

Advanced analytics on data warehouse data is no longer regarded as ‘specialized software’. It is regarded as a fundamental tool for ‘doing business as usual’.

Current progress in advanced analytics is in the ability to analyze non-structured data such as scanned text documents, digital photographs, CAT scan images etc. Whilst this may be more significant in medical, scientific and military applications, it is becoming an increasing part of understanding the whole business environment.


Challenges

Advanced analytics requires specialized technology to gather, organise and view data. The real value of advanced analytics is not from integrating it into specific applications, but rather from an enterprise level integrated approach.

Also See:

Big Data Analytics

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