AaaS stands for “Analytics as a Service” and is a cloud computing offering that provides access to data analysis tools over the internet. As the amount of data is getting bigger every day, it became a harder challenge to gather meaningful information from it. AaaS allows organizations of every size to gather the information they need from the data they have collected. Similar to other cloud offerings, it eliminates the requirement to invest in an on-premise solution. Most AaaS solutions provide customization options to organizations, allowing them to organize, analyze, and visualize data to suit their needs.
Basically, it offers the same features as an on-premise solution. AaaS also uses the same data analysis methods, such as data mining, predictive analysis, data visualization, and advanced techniques, including artificial intelligence and machine learning. Just like other cloud solutions, AaaS comes with a subscription-based payment method, allowing its customers to pay only for the resources they consume.
AaaS not only eliminates the need to acquire an on-premise data analysis solution, but it also eliminates the necessity to hire professionals, such as data scientists. AaaS providers also manage the infrastructure. Some organizations prefer to outsource simple analysis tasks, allowing their own data scientists to focus on more complex analyses. There are also some organizations using a hybrid form of AaaS that combines their infrastructure with cloud services.
How does AaaS work?
In AaaS, the organization shares the data collected with the AaaS service provider. AaaS uses various methods to create meaningful information from the raw data, such as data mining, querying, reporting, predictive analytics, artificial intelligence, machine learning, data preparation, and data visualization. It enables organizations to gather the information they need from the petabytes worth of data from various sources by using these methods. To establish data sharing between the customer and the vendor, both should support files in standard formats, such as XML, JSON, and others.
Importance of Analytics as a Service
AaaS offers a customizable business intelligence solution, allowing organizations to make the right decisions to be able to maximize their profit. AaaS provides actionable insight to help C-level professionals to be able to make the right decision for the organization. AaaS is especially beneficial for SMBs since big data requires large investments to create an on-premise business intelligence solution.
With AaaS, SMBs are able to gather the information they need at a more affordable price. AaaS is also very popular among healthcare organizations that store clinical data, patient data, finance data, or supplier data in siloed databases across the various organizations. Organizations in the transportation industry are also using AaaS solutions to monitor their fleet through predictive maintenance.
Advantages and Disadvantages of AaaS
| Pros | Cons |
|---|---|
| ✔ Eliminates the upfront cost of installing an on-premise solution and the necessity of hiring data scientists. | ✘ Some organizations may not want to share their data with a third-party service provider. |
| ✔ Provides actionable insights to organizations, making it possible to make decisions. | ✘ Although the provider handles most of the tasks, it can be a complicated process for inexperienced customers. |
| ✔ AaaS can be beneficial for customizing customer experience, running smooth operations, and understanding the latest trends in the industry. | ✘ AaaS can caause slower data transfers and add latency. |
| ✔ In AaaS, customers only pay for the resources they actually use, making it easy to scale. |