Process the Data to Answer the Question

The sources and streams of data flowing into your organization are abundant—from email, mobile apps, social networks, e-commerce sites and web traffic—providing information on sales figures, customer engagement, demographic profiles and the overall health of your business. All that data feeds into or is collected and fed into your central data center. Effective data management and programming strategies can help you gather it, clean it and apply it to answer your question.

  • Gather: Extract data from your database through advanced queries using Structured Query Language (SQL), which supports, extracts, transforms and loads data in preparation for analytics model development.
  • Clean: Data cleaning or cleansing identifies and removes errors, corruptions, inconsistencies or outliers that can affect data accuracy and, ultimately, its functionality.

Visualize and Analyze the Data

Now that you have solid data to work with, it’s time to gain intuition and insight through data visualization and analysis.

Data visualization—presented in statistical graphs, plots, charts or other visual context—descriptively summarizes the information so you can apply the right structured data model for analysis. Specialized analytics systems based on your model can provide the analysis and statistics to start answering your question.

  • Statistics and Algorithms: This can include correlation analysis, hypothesis testing, and regression analysis to see whether simple predictions can be made.
  • Machine Learning: Decision trees, neural networks and logistics regression are all machine learning-based predictive analytics techniques that can turn data into proactive solutions.

As you go through data analysis, different comparisons can derive different insights (i.e. applying differing machine learning approaches). With enhanced analysis capabilities, you can realize new opportunities and develop innovative solutions to your business questions.


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