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The Future of Artificial Intelligence for Business Analytics

To make sense of the massive amounts of digital information organizations generate from sales, customer interactions and internal operations, leaders are adopting enhanced business analytics to succeed in today’s data-driven landscape.

Analytics tools and technologies, including artificial intelligence (AI), enable businesses to identify trends and patterns in data to accelerate decision-making and optimize forecasting. Business analytics is a critical process across operational units, from human resources to strategy.

Analytics support agility and provide a competitive advantage through improved performance, better resource allocation and sustainable growth in today’s data-centric business environment. Graduates of the University of Illinois Springfield (UIS) online Master of Science (MS) Management Information Systems (MIS) with a Concentration in Business Analytics program are prepared to utilize the power of AI in business analytics.

How Are Business Analytics and Predictive Analytics Related?

Business analytics are a subset of data analytics. The former uses statistical analyses and modeling to drive business success. Data analytics, on the other hand, mines data and ensures its accuracy. Business analytics comprise three primary types of outcomes:

  1. Descriptive: supplies a snapshot of current operations
  2. Prescriptive: recommends solutions and provides scenarios of potential results
  3. Predictive: models data for forecasting

According to Google, predictive analytics could provide forecasts for the near future, such as pinpointing “abnormalities that indicate fraud and other vulnerabilities,” or the distant future, like anticipating customers’ eventual purchase intent.

What Are Emerging Trends in Business Analytics?

With all the developments in the field, businesses must stay aware of many changes and updates.  As McKinsey & Company notes, “While the volume of available data has grown exponentially in recent years, most companies are capturing only a fraction of the potential value in terms of revenue and profit gains.”

Organizations are joining the AI revolution to unlock the hidden value in their vast and complex stores of information, enhance their business analytics, optimize operations and accelerate decision-making processes. According to Pluralsight, cutting-edge applications include popular, intuitive generative AI platforms such as Tableau, ChatGPT, Polymer and Microsoft Power BI.

In fact, Pluralsight names six “bonus” AI analytics that require coding and technical skills to deploy. Among them include the following:

  • DataRobot. This generative AI platform enables enterprises to build a scalable system that the company describes as a “unified platform for generative and predictive AI.” The agile platform integrates seamlessly with applications that support network communications, data platforms and business analytics systems.
  • Databricks. By supporting enterprise-wide access to digital assets, the data intelligence platform uses natural language processing that democratizes business analytics, enabling business units to discover insights, make decisions and gain efficiencies. Organizations use it to create proprietary AI platforms tailored to their specific needs and refine and deploy them.
  • IBM Cognos Analytics. AI-powered business intelligence turns operations into “power users,” freeing up analysts to drill deeper into data for more valuable learnings. The benefits of the second-generation platform include advanced data modeling and multi-user dashboards that support predictive analytics and forecasting.

Harvard Business Review notes how most executives agree that “having a data-driven culture” and “democratizing access to artificial intelligence ” are critical to their organizations’ success.

How Are Businesses Charting the Future Landscape?

Demand for experts with advanced knowledge and insights into business analytics is growing. According to LinkedIn, the big data and business analytics market “is projected to reach $684.12 billion by 2030,” with a compound annual growth rate (CAGR) of 13.5%.

Earning an advanced MIS in business analytics degree is an ideal way to gain a competitive advantage for lucrative, high-demand, future-proof positions. The online program offered by UIS, for instance, equips graduates for success through a comprehensive curriculum that focuses on the concepts, processes and evaluation of predictive analytics, data-driven decision-making and change-management skills.

“Developing business analysis capability requires careful planning and great leadership,” according to Yash Mahta, writing for CIO. Mehta adds that investment in business analytics solutions is expanding at a CAGR of 7.3%. “This is a testimony to the fast-changing technological landscape for smarter professionals,” he concludes.

Graduates of the UIS online MS MIS – Business Analytics program are equipped to step into business analytics roles and effectively use AI for future business needs. Whether graduates become business intelligence analysts, database administrators, software developers or pursue other roles, they can confidently lead organizations into the future of business analytics.

Learn more about the University of Illinois Springfield’s online Master of Science Management Information Systems with a Concentration in Business Analytics program.

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