How AI and Data Analytics Fit Together

Norwich Pro

June 1, 2021

Artificial Intelligence (AI) has gone mainstream and is embraced by virtually every industry from manufacturing, agriculture, and information security to retail and healthcare worldwide. Used to automate and streamline operations while predicting outcomes by processing Big Data, AI played a major role in combating the COVID-19 virus by helping to track the virus spread, identifying trends that accelerated treatments, and determining which patient groups might develop severe symptoms.

In 2019, the global AI market was valued at $39.9 billion. Grandview Research reports a compound annual growth rate of 42.2% from 2020 to 2027. That means AI is here to stay with enterprises prioritizing data analytics among their strategic initiatives. In turn, that means growth in AI and business analytic careers.

 

What Exactly is AI?

AI refers to a machine's ability to mimic human behavior to perform complex tasks and continue to learn from experience and adjust to new inputs. Examples of Artificial Intelligence are self-driving cars, computers playing chess, and virtual assistants. Combining different technologies such as machine learning, deep learning, chatbots, and natural language processing, AI can process large amounts of data to recognize data patterns to provide insights or predictions. Using this information, industries in all fields can transform operations through greater decision-making, improved processes, enhanced customer service, and forecasting.

For example, in the manufacturing sector, AI can perform quality checks, predict machine maintenance and offer insights for improvements in customer service. Using chatbots that simulate interactions with users, businesses can provide support on a 24/7 basis.

 

Why Use AI?

AI helps businesses, organizations, and governments to work more intelligently and efficiently, reduce costs, move into new ventures, and improve the use of Big Data. Accenture and Frontier Economics estimate that by 2035, AI-powered technologies could increase labor productivity by up to 40% across 16 industries, including manufacturing.

AI can automate mundane tasks such as data collection while reducing the chance of human error. Taking that a step further, AI applications can analyze data from many sources with a high level of accuracy to supplement human intelligence for better decision-making.

In manufacturing processes, AI-enabled robots can minimize human workloads, taking over tasks such as heavy lifting and transporting. Relieved from monotonous duties, employees can focus on high-value activities for greater job fulfillment.

According to IBM, chatbots can help reduce customer service costs by increasing response times and answering 80% of routine questions. Human agents can work on more complex inquiries for overall improved service.

The uses of AI are boundless as enterprises look into its effectiveness in supporting their business operations.

 

Where Is It Used?

According to a McKinsey Global Survey On AI, adoption is highest within product or service development and service-operated functions. For example, the healthcare industry uses AI applications in many areas, including surgery with AI-assisted robots, patient data processing, and medical imaging analysis. In the future, an AI system with machine learning will help with medical diagnosis.

In retail and E-commerce, AI-based algorithms determine the demographic profile, purchasing history, and other customer preferences to generate targeted recommendations. Similarly, the real estate industry can benefit from AI’s ability to analyze big data volumes that enable agents to find the perfect properties from different real estate websites for clients.

In banking and finance, investments are recommended by robo-advisors that analyze thousands of possible investment scenarios. It is predicted that AI could be managing about 20% of total assets in the near future. These are just some of the top industries revolutionized by AI.

 

Data Analytics + AI

While AI is the field of computer science in creating smart machines that emulate intelligent human behavior, data analytics is the technique of analyzing raw data to derive valuable insights from data. Integrating data analytics with AI creates smarter business intelligence solutions. According to Gartner, by the end of 2024, 75% of enterprises will operationalize AI, driving a 5x increase in streaming data and analytics infrastructures. 

Companies can’t efficiently manage and harness the huge amounts of structured and unstructured data that comes into an organization from different sources using traditional methods. Standard software programs and manual approaches are not robust enough to capture and process useful information. Data analytics analyzes raw data to reveal insights that might get lost in the mass of information. Businesses use these insights to optimize processes, make better business decisions, analyze trends for new product opportunities.

 

AI Careers

With the growing use of AI and data analytics in industries ranging from business and government to health care, jobs for data professionals will increase exponentially. The U.S. Bureau of Labor Statistics expects a 35% job growth for data analysts between 2014 and 2024.

Data analytic careers will offer high salaries and room for advancement as skills are transferrable to many positions. The different career paths in this field include:

  • Business intelligent analyst
  • Data analyst
  • Data scientist
  • Data engineer
  • Quantitative Analyst
  • Data Analytics Consultant
  • Operations Analyst
  • Marketing Analyst
  • Project Manager
  • IT Systems Analyst

Each requires data analysis skills and knowledge of different technologies such as Python, SQL, Ruby, and Java and hands-on experience in database modeling, backup, and design. Some require a background in data warehousing, data modeling, and data mining. Professionals with interdisciplinary skills are in high demand.

 

Gain or Strengthen your Background

For those with a background in AI, certificate courses can enhance current skills for higher salaries and career opportunities. Those new to the field should pursue a bachelor’s degree in data analytics to gain the background to pursue a career in this area.

Norwich Pro offers certificate and microcertificate options on AI/Data Analysis. These include:

 

Norwich University’s Online bachelor’s in Data Analytics offers courses in data science and technology-enhanced techniques, Python programming, algorithm design, and implementation, and machine learning to provide a well-rounded background in AI.

Those entering the field of data analytics or pursuing career advancement can gain new skills through these online programs. For information on Norwich Pro’s complete roster of certificate programs that develop and deepen professional skills to get ahead in careers or enter new ones, visit https://pro.norwich.edu/.

Have questions? Contact Norwich at https://pro.norwich.edu/contact or by email at norwichpro@norwich.edu.

 

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