Too much data, the very challenge entailed by digital disruption, has also created an anomalous opportunity. As the cloud continues to enable increasingly powerful processing capabilities, in line with rising data volumes, it is making it possible to train and execute algorithms on a very large scale. This is extremely necessary to realize the complete potential of Artificial Intelligence (AI).

The story of data analytics and cloud keeps evolving, ranging from information products and continuous intelligence to supporting internal decision making. The cloud analytics business is expected to Although traditional on-premises data center is thought to be ideal to operate in-memory databases, it is not the best solution for the entire IT strategy. Thinking outside the technical box, the cloud provides greater flexibility and is cost-effective along with demand-oriented billing.

Building a Cloud-Agnostic Data Analytics Platform

There are many tools and services available at present for building the data analytics platform in the cloud. It is vital to choose the right solution to meet an organization’s requirements. Key parameters that an organization must consider while assessing the options and making their decisions include:

  • Elasticity: As the cloud is known well for its elasticity features, the data analytics platform must also have the ability to scale up and down. This will help in scaling quickly and managing the cost while meeting changing requirements. 

  • Interactive Analysis: Businesses must be able to analyze massive data volumes and get rapid results. They must be capable of slicing and dicing, rolling up and down, and interactively exploring their data to derive meaningful insights.

  • Ease of Use: Most of the time, the users face difficulties in utilizing the data for making decisions owing to the growing dependency on data analysts and IT teams to pull reports from the data. The data analytics platform must enable self-service access to data across the organization.

  • Speed to Insights: Speed is imperative when delivering insights on data, in order to shape the success of an organization’s data initiatives. As most analytics platforms become sluggish with the increase in the size of the data, it is of paramount importance for organizations to build an environment to achieve insights instantly whenever required. 

Cloud Analytics is a massive initiative that needs a significant investment in terms of processes, people, and time. It is therefore important to build a solution at full length that takes care of data storage as well as the actual data consumption by the business users.

The Competitive Edge of Cloud Analytics

The more organizations commoditize their compute infrastructure, the more flexible are they to move their analytic apps and data for best-of-breed functionality. Being cloud consumers, flexible storage of data and analytic applications is a top priority of an organization’s financial bottom line, data teams, and developers. However, the ability of organizations to execute a cloud-agnostic, flexible data strategy is contingent on the size of the platform used for data management.

While considering a data analytics platform it is critical for organizations to make sure that the vendor’s product roadmap will emphasize future investment in cloud-native capabilities. Also, organizations that ensure having a well-documented history of their cloud analytics will be able to develop a robust roadmap and expand capabilities in line with the market’s evolution.

Tags: , , , ,