Data Analytics and Machine Learning – What You Need to Know for Your Business

Data analytics and artificial intelligence (AI) have been creating headlines around the world.  Many industries have now been fundamentally changed by the availability of real-time, relevant Big Data. In the highly-competitive, global marketplace, data can be the key to an organization’s survival.

What do the terms data analytics, machine learning, and AI actually mean?  Forbes provides straightforward definitions:

  • Data analysis refers to reviewing data from past events for patterns.
  • Predictive analytics is making assumptions and testing based on past data to predict future what/ifs.
  • AI machine learning analyzes data, makes assumptions, learns and provides predictions at a scale and depth of detail impossible for individual human analysts.

Basically, data analysis is based on events or actions that have happened in the past.  There is no prediction involved in simply collecting data.  Predictive analytics begin with the data analysis and introduce variables or assumptions to try and predict future actions or events.  Still, predictive analytics incorporates human interaction.

AI machine learning is the next step.  The AI structure utilizes predictive analytics but is able to make assumptions, test, and learn independent of human intervention.  Machine learning begins with the outcome and automatically searches for variables and reevaluates the model and data.

Machine learning is an automated method of data analysis.  According to SAS, “It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.” A desired outcome is programmed into the AI system along with data and examples, but no rules are provided for the machine to follow.  The machine learns the important variables and rules from the examples. As new data and examples are provided or learned, the AI system adapts to produce new decisions and results.  This helps organizations to discover what variables are important to achieve certain goals. Organizations can make better decisions utilizing limited human interaction. Eventually, it is expected that machine learning will advance to a level that it can be applied to scenarios where machines can assess complex situations, take action, and then adapt responsively to the evolving conditions. This level of “thinking” has historically been reserved to living, thinking beings.

The technology that makes artificial intelligence possible has been around for a long time.  Even prior to its feasibility, science fiction writers have envisioned multitudes of potential AI scenarios, ranging all the way from benevolent to the ultimate extinction of humanity.  In recent years, however, the power of computers makes it seem as though AI sentience is just around the corner.  The future use possibilities of AI are exciting to imagine!

Join Illinois BIS for further exploration into the future of data analytics and machine learning during our breakfast seminar on November 12, Data Analytics and Machine Learning: What You Need to Know for Your Business.  This 2-hour seminar will provide a foundational understanding of data analytics and machine learning and will offer practical examples on how these capabilities can and will change businesses. Register today!

Sharon Andersohn,
VP Grant Programs

References:

Machine Learning: What it is and why it matters
Data Analytics vs. Machine Learning
When Business Analytics meets Machine Learning
Do You Know the Difference Between Data Analytics And AI Machine Learning?
What is the difference between data analytics and Machine learning?

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