Blog: Data Insights

What is Analytics as a Service? Your Complete Guide

December 22, 2020 - by Synoptek

When Software as a Service (SaaS) was first launched, it completely changed the way software services were delivered and consumed. Little did anyone imagine, however, the pace and scale of growth of the market – today, the concept of providing “anything as a service” has broken all boundaries, with every possible service being offered via a pay-as-you-go model. As the need to constantly glean insight from the growing volume of data intensifies, the latest entrant in the as-a-service market is Analytics as a Service (AaaS). So, what is Analytics as a Service, and why should your business embrace it? Keep reading to find out.

The Need for Real-time Analytics

Organizations across various industries have finally woken up to the fact that data is the new oil that can propel their business to the pinnacle of success. This realization has set the ball rolling for data analytics, with many collecting and storing large amounts of data on a daily basis. When an organization is able to gather this much data, they can then analyze itand use the results to drive better decision-making within their business.

Unfortunately, most organizations lack the capabilities needed to unearth insight from their ever-evolving data sets, which puts them in a tight spot. Since data analysis is a business-intensive process, it requires skilled team members who can constantly analyze data in real-time using modern tools. Given the basic analytical capabilities of the existing pool of resources, however, and the constant dearth of analytics skills in the market, filling the analytics gap becomes extremely difficult. Constantly training the existing pool on the latest technologies or driving efforts in hiring them from the market not only requires substantial investments in terms of time, but it also costs a lot of money.

In the absence of the right tools, technology, people, or even approach, organizations struggle with analyzing critical business data that hampers their ability to make accurate and timely data-driven decisions. In the long run, this translates into poor business efficiency, lackluster employee productivity, sub-par customer experiences, and a weakened competitive position.

The Realm of Analytics as a Service

For organizations that seek to accurately analyze their growing volumes of data, Analytics as a Service provides anytime, anywhere access to skilled resources, tools, and procedures. Once implemented, AaaS can help turn data into insights and insights into action. This subscription and cloud-based service model offers a fully customizable data analytics solution with end-to-end capabilities. These features range from collecting data, organizing and analyzing it, to presenting it in a way that empowers even non-IT professionals to take immediate action.

By using techniques such as data mining, predictive analytics, and AI, Analytics as a Service helps in effectively revealing trends and insights from existing data sets without having to personally manage or maintain them. All tasks are carried out entirely by the service provider in a scalable, reliable, and affordable manner, so organizations can make smarter decisions in real-time.

The Benefits of Analytics as a Service

Today, several data-reliant companies from across industries are increasingly turning to Analytics as a Service to meet their analytical needs, and with enough reason. Here’s a compilation of the top benefits of Analytics as a Service:

  1. Access to Skilled Resources: One of the biggest benefits Analytics as a Service offers to organizations is access to a world of new-age skills and capabilities that their existing data teams invariably lack. You can be sure to have proficient resources work on your data analytics program to help you get the most out of your existing data in the least possible time.
  2. Enhanced Scalability: Since Analytics as a Service uses cloud-based technologies to carry out analysis of big data, it offers far greater scalability as opposed to traditional on-premise databases that need to be procured to collect, store, and analyze the data. As your data needs grow, you can easily scale the solution to meet your new and increased demand.
  3. Customizable Reports: As an extensible analytical platform offered via a cloud-based delivery model, Analytics as a Service allows you to configure the solution and build customizable reports based on your specific business needs. You can choose from a range of dashboards and reports and get accurate and continuous insight into huge quantities of heterogeneous data.
  4. Reduced Overhead: Despite the pressing need for real-time data analytics, the costs associated are considerably huge. Analytics as a Service eliminates the need for large, upfront investments in modern-day databases and analytical tools, allowing you to leverage the capabilities you need, and pay only for what you use. It also helps save up costs of upskilling your teams on the latest technology and/or hiring proficient data analysts from the market.
  5. Faster Time-to-Value: Analytics as a Service also accelerates the pace at which you can unearth insights and drive critical decisions. Since all tasks related to analyzing data are taken care of by the provider, you can focus on your core business offerings, and use the insight generated to power critical decisions while improving time-to-value.

Capitalize on New Business Opportunities with Analytics as a Service

The trends in big data and cloud are constantly evolving, and combining the power of these two technologies can help organizations redefine the enterprise computing space. However, discovering insights from humongous volumes of data, especially for organizations not in the business of IT, can be extremely taxing.

For businesses that struggle to act on their data in an accelerated manner, Analytics as a Service is becoming a valuable option to overcome all the challenges that come with setting up their own analytics team. Since data analytics is a time, cost, and resource-intensive process, Analytics as a Service offered by a qualified Managed Services Provider helps bypass unnecessary costs while helping organizations capitalize on new and upcoming business requirements with ease and efficiency.

Download our resource, to learn how enterprise data warehouses and BI work together in the age of the cloud to improve your business.

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