Necessity Of Advanced Analytics

Necessity of advanced analytics

by

Andy R Robert

Additionally it includes statistical models, machine learning, neural networks, text analytics, and other advanced data mining techniques. Among its many use cases, it can be deployed to find patterns in data, prediction, optimization, forecasting, and for complex event processing/analysis. Examples include predicting churn, identifying fraud, market basket analysis, or understanding website behavior. Advanced analytics does not include database query and reporting and OLAP cubes.

Advanced analytics are based on mathematical principals and started as descriptive statistics which are basically used to sum and count past occurrences for what has happened in the past which is useful in a reactive, course correction manner. Moreover, it allows you to anticipate possible future outcomes and either capitalize on them or adjust now to impact the future. The traditional technique for building a predictive model is based on hypothesis testing which is more of a statistical approach. Data mining is a technique for building predictive models where the data is visually explored and used to determine which predictive model to use to fit the data. For example, if the data visually looks linear then a linear regression technique could be applied. However, if the data plots out logarithmically (fancy work for the hockey puck graph we ve all seen) then a logistic regression technique could be applied.

Advanced analytic techniques allow you to create more precise models of the world around you. Models that can be applied throughout your business in order to help, inform for better decisions. Advanced analytics allows you to:

Predict competitive initiatives with accuracy

Identify latent market demand and innovate products to meet it.

Identify a person s likelihood to develop heart conditions and suggest the right incentives to change contributing behavior?

Anticipate which parts on your customer s cars are likely to fail in the next 30 days and allows you to proactively notify them, preventing warranty claims.

There are two distinct platforms used for translating source code into an executable file. One way is to use a compiler interface, which consists of writing code in a text editor, and then compiling the code with a separate console based compiler. The other is to use an integrated development interface (IDE). An IDE is a much more intricate piece of software and comes with tools to write and compile a program from within itself. Both have their advantages in different situations. Determining which solution is best for a project is important in ensuring that the programmer is working in an environment that is not only efficient but also somewhat ergonomic.

Andy Robert is an expert article writer and likes to write on

advanced analytics

and integrated development environment. If you want to know more about advanced analytics, Please visit online –

asterdata.com/

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