How The Cloud Has Enabled The Next Level Of Analytics?

Data analytics is now a mainstay among companies. Research shows that the big data analytics market will reach $103 billion by 2023. However, many companies still struggle to implement data analytics meaningfully and comprehensively. One reason could be the limitations of cost, scalability, agility, and speed imposed by on-premise infrastructure.

On-premise provides limited storage systems. There are also other expenses, such as infrastructure, hardware, and maintenance. As data volume increases, companies will have to use advanced analytic tools to identify trends quickly and build strategies that can help them gain a competitive advantage. Scaling up infrastructure in tune with these needs is hard.

The cloud has made it easy for companies to move to the next level of analytics by overcoming these limitations. By moving to the cloud, data analytics becomes more accessible across the companies, and decision-makers can witness a remarkable improvement in their decision-making process.

How Can Cloud Propel Advanced Analytics?

1. Saves time and costs

According to studies, legacy systems consume over 75% of the company’s IT budget. They need continuous maintenance too. The company has to spend more on infrastructure if they scale up analytics. These expenses can be controlled if companies move their analytics to the cloud. The cloud uses the pay-per-use model. So, the company will have to pay only for the infrastructure they utilize. This saves the company from massive upfront investments.

Another benefit is that managed cloud services take care of maintenance costs, security management, upgrades, etc. So, companies can save up to 30% of their expenditure on analytics infrastructure. Besides saving costs, the cloud also helps save time as advanced analytics enable companies to get real-time data insights that help them make decisions quickly. Also, as administrative tasks such as upgrades and buying additional infrastructure are taken care of, companies can respond to market demands faster.

2. Improves scalability

Companies now have to process petabytes of data to make informed business decisions. On-premise infrastructure has limited capacity to process that much data as volumes add up. Scalability is one of the main features of the cloud. So, when analytics is moved to the cloud, companies can process huge volumes of data easily and can ramp up their infrastructure capabilities in concert with the needs of the organization.

It’s also easy for companies to deploy data-intensive applications on the cloud. Another benefit is that the infrastructure can be scaled up or down depending upon data volume and business needs. They also don’t have to purchase additional infrastructure for that. Cloud-based analytics is useful for large companies and also small, medium businesses that don’t have the required infrastructure to store and maintain data.

3. Fosters innovation

Consumer demands change rapidly. Companies have to respond quickly to their demands. To do this, they need to inculcate a culture of innovation among data analysts and scientists. Innovation often takes a backseat when companies have to focus more on infrastructure, maintenance, etc. The lack of real-time insights from legacy analytic tools could also delay the decision-making process. The data team needs access to data tools that help them understand the trends and make quick business decisions.

Cloud-based analytics tools offer the opportunity to be innovative. This strategy eliminates the need to maintain and upgrade infrastructure and enables the team to focus on more critical tasks such as making decisions, building data models, implementing them, measuring the outcome, and improving how the company functions. It also provides powerful and readily available tools that break data silos and simplify them to help companies make accurate decisions. Cloud analytics is also accessible to authorized people. This democratizes analytics and promotes innovation across the company.

4. More use cases

Data analytics is useful for many reasons. It helps companies acquire more customers, sell or cross-sell products, understand market trends, personalize the customer experience, and much more. Companies can also use it to predict inventory and probable bottlenecks and ensure smooth operations. To analyze a large volume of data and make accurate decisions, companies can use AI and machine learning technologies. The benefit of cloud analytics is that companies can test large data sets as there are no capacity limitations and can develop new use cases and build innovative solutions.

Conclusion

Insights-driven companies grow at 27% year on year. They acquire 23x more customers and are 19x more profitable. Needless to say, advanced data analytics is essential for companies to go to the next level. Cloud makes it more effective due to its advanced capabilities of scalability and elasticity.

However, companies could face various challenges while implementing analytics in the cloud environment. To begin with, cloud security is still a major concern for many companies. Some industries like healthcare might hesitate to implement analytics in the cloud due to the compliance laws such as HIPAA. Vendor lock-in with stringent contracts and latency issues could also pose challenges for companies. That’s why it’s important to work with a partner who can understand the business needs and help companies move their analytics to the cloud successfully.

At Veracitiz, we have partnered exclusively with IBM to help companies run their data across any cloud and integrate analytics to optimize their business and improve innovation.

To know about how we can support your data ambitions, contact us.