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Maryam is an executive of a restaurant operations business that recently expanded their services into new demographics. This move also increased their data collection and required faster analytics capabilities to accommodate unique customer insight.
However, with the recent budget for new outlets, they couldn't afford the high cost of expanding on-premises analytics capabilities.
Mayram sought a new, cost-effective, high-performance solution with AI analytics features to extract insights and maintain a competitive advantage.
If you are like Mayram, in restaurant operations, e-commerce, manufacturing, online retail or other industries, Cloud analytics is an excellent solution to adopt. With the rise of cloud computing services, you can now utilize cloud storage to analyze large volumes of data and enjoy other features without the cost or technical inefficiency of on-premises systems.
In this article, you will learn about:
Cloud analytics uses cloud computing to perform data analysis and business intelligence activities. Unlike on-premise tools like Excel sheets, cloud analytics can help you access, process, and visualize large and complex data sets from various sources using cloud-based tools and services. With this analytic tool, you don't have to worry about system specifications or storage needed to analyze specific datasets.
Cloud computing combined with analytics principles enables you to use advanced techniques such as artificial intelligence and machine learning to generate insights and predictions from your data. Subsequently, you will have a scalable and cost-effective system, allowing you to generate predictions, identify root causes and create strategies to remedy them at record speed.
Data analysis is a method of collecting, inspecting, cleaning, transforming, and modeling data to discover helpful information for decision-making purposes. This process can be carried out using different ways, one of which is cloud analytics.
Unlike data analysis, Cloud analytics uses cloud computing, a technology that provides scalable, flexible, and cost-effective IT services over the Internet to conduct data analysis.
Additionally, cloud analytics is cost-effective, while data analysis costs can vary depending on the method used. Similarly, the performance, data quality and results are better using cloud analytics.
In contrast, data quality, performance and results vary for different data analytics methods. Generally, cloud analytics is a subset of data analytics methods, offering cost-effective and efficient results.
Cloud-based analytics offer many benefits like flexibility, scalability, cost-effectiveness, performance, AI capabilities and collaboration to business. Let's explore each benefit.
Companies' needs constant change to meet consumers' requests and market trends. Adapting to these changes and leveraging real-time data to make informed decisions might be challenging with on-premise tools. However, cloud-based analytics enable you to access real-time data quickly without the challenge of sending email requests and other formalities. With a few clicks, you can pull data from any source or touchpoints, analyze it and generate insight all within the same setup. This way, it's easier to adapt to changes at a less expensive and expertise-constrained process synonymous with an on-premise option.
You can use data, services and resources anytime with cloud-based analytics tools. Since data is available on cloud storage, it can be accessed anywhere within or outside the office. This feature fosters scalability in times when companies' demands increase. Companies with a global workforce can benefit from cloud analytics as it encourages real-time collaboration, which helps generate valuable insights.
Cloud analytics can reduce the costs and complexity of data infrastructure. Unlike on-premise tools, you don't have to worry about the extra hardware upgrade or maintenance cost when your data needs increase. Additionally, you save the expenses of hiring, onboarding and training new data experts as you can access AI features in most cloud analytic systems. These features offered by cloud analytics companies like Kyligence help you automate processes effectively.
Many use cases and examples of cloud analytics exist in today's business world across different industries and domains.
For example, in the healthcare industry, doctors use cloud analytics to analyze data from genetic research. Similarly, cloud analytics helps online retail businesses understand customers' behavior, preferences and feedback.
With AI capabilities, retail companies can analyze unstructured data like surveys, reviews and more to generate deep insights. The information helps you build effective strategies and optimize services for better customer experience.
Also, financial institutions use cloud-based analytics for predictive modeling, which helps predict customer default rates. E-commerce also enjoys the benefits of cloud analytics in forecasting product demand based on historical data, trends and customer behavior.
Migrating to cloud-based analytics solutions isn't without its challenges. Here are some mistakes to avoid ensuring you achieve your desired outcomes:
Cloud-based analytics is a game changer that offers small and large-scale enterprises many benefits. Businesses can leverage the AI capabilities of these tools to analyze large volumes of data and extra insights from unstructured data. Additionally, it fosters collaboration, which helps effective decision-making and scalability.
However, Cloud analytics is not a one-size-fits-all solution. You need a customized solution like Kyligence Zen that suits your needs and goals. Kyligence Zen offers cloud analytics with AI features that help you leverage the full scope of your data from a centralized location. It also supports collaboration and real-time deep dive into data using root cause analysis—sign up for a free trial to experience the personalized data analytics capabilities of Kyligence Zen.
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