In-Memory Data Grids and Predictive Analytics

Big data is the future, but without the proper tools to process and analyze data, it can’t be transformed into actionable insights that can help in making sound business decisions. Especially in times of crisis, companies need to be a step ahead to keep their customers happy and their business afloat. The introduction of AI into your business systems will help not only in sales and conversion, but also in other aspects, including logistics optimization, spend analytics, and forecasting. McKinsey research shows that 53% of companies showed an increase in revenue as a result of integrating AI into their supply chains, with 61% also reporting a significant reduction in costs.

From enhancing marketing campaigns to optimizing internal business processes, data analytics has shown how big a role it plays in today’s business landscape. The Deloitte’s Analytics Advantage Survey shows 49% of respondents reporting that analytics has helped them make better business decisions. The growing challenge for most is the rapidly growing amounts of data that need to be processed and analyzed each day. Without proper data management, it would be a challenge to monitor and visualize business performance. Workflows could also be streamlined by transforming data into actionable feedback, providing a more in-depth understanding of behavior and preferences that could help improve overall business operations.

One of the best data analytics solutions available today for improving business operations and performance is an in-memory data grid (IMDG). By running specialized software on each computer within the network, it allows these computers to combine their processing power to perform large, complex jobs that can’t be handled by a single computer. Using an IMDG allows networked computers to be in remote sites but still share data and work together seamlessly. Combining the power and of multiple computers allows it to manage even the largest and most complex of tasks. Speed, scalability, and high availability are the highlights of an in-memory data grid, and it helps in predictive analytics by providing real-time responsiveness and a distributed data layer for maximum performance.

What is Predictive Analytics?

As the name suggests, predictive analytics is specifically designed with the main objective of making predictions about future outcomes through the use of historical data. Machine learning and statistical modeling are common methods used in predictive analytics. A sophisticated predictive analytics tool like an IMDG can help businesses forecast trends with a significant degree of precision using current and past data. The reliability of predictive analytics has not gone unnoticed, with a projected global market value of approximately $10.95 billion by 2022.

Historical data is something that every business has in abundance, and an IMDG can help turn that data into something you can act upon. It will help you sift through large amounts of data and identify patterns that can either highlight opportunities or detect risks. This contextualization of data helps in getting real-time insights from an organization’s transactional data so quick–and better–business decisions can be made. With the ability to handle millions of events per second, an IMDG efficiently analyzes data so that potential risks and their impact are detected early and appropriate actions are taken immediately. It can also help in preventing cyber attacks and customer churn.

Combining AI with an IMDG gives organizations the power to discover relationships between behavioral patterns and use it to gain a competitive edge. This allows for the assessment of a specific set of conditions that can either benefit the business or put it at risk. By transforming data into something more tangible and comprehensible, an IMDG gives businesses the power to make informed decisions that are data-driven and impactful.

Why Predictive Analytics?

In today’s extremely competitive business landscape, it’s not enough to just know the history and past behavior of your customers. You must ensure that you’re always a step ahead of both them and your competitors, and the only way you can do this is by learning how to understand big data. An in-memory data grid will help you use predictive analytics to look into the future and make reliable predictions about vital business outcomes. Knowing what will happen in the next few days, months, or years is essential knowledge that will help your business earn and save money in the long run.

Almost all insights today are data-driven and almost all business models are digital in some way. Getting started with predictive analytics may be a challenge if you don’t have the systems and tools necessary. However, it’s something worth investing in if you want to boost your business and push it into the future. Once you start and see the returns, it will provide actionable insights for years to come with minimal maintenance required.