The Intersection of Cloud Computing and Business Analytics

Cloud computing is a technology that delivers on-demand computing resources, such as servers, storage, and software, over the internet. It enables companies to store, access, and process business data without investing in an on-site IT infrastructure.¹

Cloud solutions for business analytics can be a game-changer. Cloud services for business intelligence can provide advanced tools for data analysis, helping organizations get deep insights into their historical, financial, and customer information.²

When you're looking to leverage cloud computing in business analytics, it’s essential not only to know the basics and how the integration benefits corporations, but also to gain firsthand experience in using the cloud infrastructure effectively.

Read on to understand the integration of cloud technology in business analytics and how cloud services benefit organizations.

Key Concepts in Business Analytics

Business analytics includes several fundamental methods for making informed decisions. They include:

• Data analysis involves inspecting and transforming raw business data into meaningful information, such as valuable patterns in a company’s financial or marketing data³
• Predictive modeling is the use of an organization’s historical data to anticipate future events or outcomes⁴
• Actionable insights are specific conclusions drawn from data analysis that guide organizational choices. They help businesses make data-driven decisions rather than rely solely on intuition or experience

Cloud computing provides the tools needed to deploy and enhance the effectiveness of these business analytics methods.

The Integration of Cloud Technology with Analytics Tools

Business analytics in the cloud era is cost-effective and more efficient than traditional analytics methods. Cloud-based platforms like Amazon Web Services (AWS), Google Cloud, and Azure provide organizations with an IT environment to run existing business intelligence (BI) tools or build tailored analytics applications without investing in on-site infrastructure.⁵

On the other hand, cloud-integrated business analytics tools, such as Google Analytics, Power BI, and Tableau, enable companies to analyze and extract actionable insights from their historical records, customer data, and revenue information. From this data, cloud BI tools identify patterns that firms can use to predict future trends. This enables corporations to anticipate and mitigate risks.⁶

Benefits of Cloud Computing in Business Analytics

High Scalability

The amount of data a business processes and the computing power required in data analysis can change drastically over time. In that case, cloud BI solutions allow organizations to increase or decrease their computing resources based on their current needs. This can help them save money by ensuring they pay for IT resources on demand rather than investing upfront in a fixed in-house infrastructure.⁷

Improved Accessibility and Collaboration

Cloud-based data analytics platforms and tools are accessible from anywhere via the internet. Centralized data storage on cloud computing platforms breaks data silos between organizational departments, enabling team members to work on the same project simultaneously and in real time.⁸ This improves collaboration.

Advanced Data Processing

Speed is essential in business analytics, enabling companies to swiftly transform large amounts of data into actionable insights. High-performance cloud computing solutions enable organizations to run the most advanced software tools necessary for complex analytical tasks.⁹

Enhanced Security and Compliance

Cloud providers invest in the latest security technologies and expertise, offering better cyber defenses than most on-site approaches. For instance, Google Cloud has data security features that encrypt information at rest and in transit to prevent unauthorized users from accessing sensitive business information.¹⁰

Other cloud providers like AWS provide comprehensive compliance controls that meet industry security standards. As a result, cloud technology in BI helps users comply with data protection and privacy regulations, such as the Health Insurance Portability and Accountability Act (HIPAA).¹¹

Cloud-Powered Advanced Analytics Techniques

Machine Learning (ML) and Artificial Intelligence (AI)

Machine learning and AI in business analytics help organizations tap into hidden insights and save time.

Machine learning tools are designed to identify data patterns that might not be readily visible to the human eye, providing deeper insights into an organization's financial or historical records. Cloud providers offer services that allow businesses to build, implement, and manage machine learning applications. Since creating an in-house ML infrastructure can be expensive, cloud computing makes machine learning accessible and affordable even for small businesses.¹²

Meanwhile, AI predictive analytics focuses on what might happen in the future and is a game-changer in business forecasting. Instead of spending hours using traditional predictive analytics methods, analysts can generate forecasting insights from vast amounts of company data in just a few minutes using AI cloud analytics.¹³

Big Data Analytics

Big data is a massive collection of datasets with volume, composition, and computing power requirements that make it challenging to manage on traditional, on-premises databases. Data analytics cloud platforms provide everything a business needs to collect, store, process, and analyze big data.¹⁴

Internet of Things Data Analytics

The Internet of Things (IoT) connects a vast network of smart devices, enabling seamless business communication and data exchange. As the number of IoT devices increases significantly, managing and extracting value from IoT data becomes more difficult. The power and scalability of IoT-cloud integration enable businesses to efficiently manage and process large amounts of information from IoT devices.¹⁵

Take Your Career to the Next Level: SCU’s Online MSBA

Earning an Online Master of Science in Business Analytics (MSBA) from the Leavey School of Business at Santa Clara University can be the smartest next step in your professional development. Whether you want to focus on big data modeling, deepen your knowledge of cloud computing, or broaden your understanding of cloud IT architectures, you can tailor this flexible, expert-led program to fit your needs and prepare you to be an expert in your field.

Additionally, you’ll have the prime opportunity to interact with other MSBA candidates and build a professional network of industry insiders and peers. To learn more, schedule a call with an admissions outreach advisor today.