Flexibility in strategy has now been realized as critical to startups that want to compete in the increasingly challenging and saturated industries. From optimizing strategies and navigating unexpected issues to maximizing effectiveness, the importance of enabling a swift and data-driven approach to startups is crucial. One such tactic that can aid startups in critical decision-making and adopting a streamlined, flexible, and accessible approach to strategy is cloud analytics.
With a wealth of benefits, cloud-based solutions offer an innovative variation to regular data analytics, allowing startups to easily enable vital business decisions. In this guide, we’ll answer questions like “What is cloud analytics?” and “Why is cloud analytics a must-have for startups”? As well as explain how it works and what startups must do to start their cloud analytic journey.
What is cloud analytics?
Cloud analytics refers to analyzing and manipulating data in the cloud in conjunction with a service provider instead of in a local on-premises system. With this platform, startups can work with an extensive set of data, identify ends, and determine areas in their business that need improvement. Since the analytics provider generally manages setup and maintenance, it is easy for businesses to empower their employees with deep data insights through performance, scalability, cost savings, and reliability.
Why is cloud analytics a must-have for startups?
As a startup grows, so does the amount of data it collects. Modern startups understand the importance of using data to establish what’s working, what’s now, and how to address the concerns that might be deterring their performance. Cloud analytics can help review data from every perspective to identify and repeat their successes then determine and eliminate potential issues. Advanced cloud analytics algorithms enable accurate predictions, so startups can easily understand the outcomes of their efforts.
Cloud analytics can also help improve data sharing and collaboration. Vast quantities of data don’t give value to any startup if stored away. With cloud analytics, startups can look at all of their data instead of pieces of it. Every department has the same understanding of the truth instead of finance having access to financial data and sales seeing only sales data. With cloud analytics, each unit has access to the same data, resulting in more informed decision-making and better transparency.
Furthermore, by monitoring and optimizing the customer experience, a startup can set itself apart from the competition. Cloud analytics helps startups get valuable insights from these data to help measure customers’ experience and satisfaction with their services and/or products. With this knowledge, startups can significantly improve every stage of the customer’s journey.
How does cloud analytics work?
Most times, cloud analytics systems run on a network of secured and advanced data centers that offer the storage space and processing power required for analyzing a large amount of data. With cloud analytics, all the data generated by the startup are collected and stored in the cloud, where it can be accessed and utilized from anywhere with an internet-connected device. There, the data can be organized, processed, and analyzed.
It presents these insights to the users through various data visualizations and intuitive formats. While each cloud analytics solution has its own unique set of features, they all have several standard components, including:
- Data sources
- Data sharing and storage
- Data models
- Data processing
- Computing power
- Analytics models
In addition to these features, AI has become an integral part of cloud analytics. Machine learning, for instance, allows cloud analytics systems to learn without being expressly programmed and more accurately predict future outcomes.
What should startups consider before using cloud analytics?
Every startup possesses different goals, requirements, and metrics. When considering the cloud analytics system to incorporate, startups must assess various factors to integrate the right service. They must ensure their current volume of data can be supported in an easily manageable format and be cost-effective. While also ensuring the system is accessible based on the data workers’ existing expertise and skill level.
Startups should also consider the form of Service Level Agreement (SLA) they will have to adhere to, as in some situations, these may pose restrictions in the volume of date, time of access, and available support.