It’s hard to deny how the pandemic has affected the way business is done today. Companies have struggled through the crisis, with some managing to stay afloat and some succumbing to the dire consequences of lockdowns, social distancing rules, and other regulatory policies enforced due to COVID-19. Today’s businesses have to be nimble and able to think on their feet if they are to survive in the current unpredictable and highly competitive landscape. More than ever, studying consumer behavior and how it affects business becomes of paramount importance; companies should identify current customer sentiment to determine next steps and overall business direction. This makes customer data a vital part of the equation, especially for businesses looking to expand their operations despite the crisis. Data-driven insights can mean the difference between creating effective strategies and setting your business up for failure.
The first step toward expansion for every business should be optimization and streamlining of operations and processes. For most companies, this could be as simple as adopting the appropriate data processing and computing solutions, such as an in-memory data grid (IMDG). Upgrading older systems should always be considered first before considering newer, more modern ones. Finding out what currently works is vital so you can build upon them and not do a rip-and-replace, which is almost always unnecessary. With this change comes a host of other ones that will affect sales, marketing, operations, and IT infrastructures. Being prepared and knowing your business requirements is key in ensuring that operations continue without a hitch despite the changes that the company needs to undergo.
Data-driven Business With In-memory Data Grids
The IMDG helps businesses in any industry because it helps increase data processing speeds so companies can sort through large amounts of data quicker and transform it into useful information. It can help develop a data processing system that can scale to the whole organization, optimizing an organization’s data management strategy. In 2016, in-memory computing was a major contributor in addressing marketing and business challenges, which included problems in customer retention, product promotion, sales, and customer segmentation.
By using RAM, an IMDG eliminates the need for disk-based storage systems that can be hard and expensive to maintain. It also ensures that data processing is fast with minimal data movement to and from storage and within the network. Because data is stored in RAM, slowdowns are avoided when accessing frequently used data. A solution that’s been present for years, rapid advances in the technology has led to innovative business applications that are beneficial in several use cases. Volumes of data also continue to grow in volume as systems become more capable—and faster—in storing and processing them. Organizations today are also less reluctant to adopt modern computing solutions to achieve business objectives. Common IMDG use cases include open banking, where banks use an API to provide customer details to third-party application developers who then leverage it to create rich mobile applications; eCommerce, where fast data access is required to identify customer behavior patterns and make recommendations; and payment processing, where maximum throughput is required for analyzing transaction history and other regulatory checks, which often goes beyond a single transaction.
The highlight of the IMDG, however, is how it helps predict potential business outcomes, giving businesses a competitive edge when it comes to operational intelligence. Because of its capability to analyze large volumes of data at high speeds, the platform can help with risk management by alerting an organization whenever there’s an anomaly in the transaction data. Data is always moving as it’s gathered and it can change at any given point, which makes data processing quite challenging. This is where an IMDG comes in, effortlessly processing large volumes of streaming data in near real-time without causing slowdowns and network congestion.
Should Your Business Use an IMDG?
The short answer is yes. As the demand for cloud computing, data analytics, and the Internet of Things (IoT) continues to increase, businesses should respond to the call of the times by adopting computing solutions that will help them manage data and understand how it can push their business forward, maybe even unto unfamiliar territory where it can make breakthroughs in its industry. An IMDG will help businesses transform data into insights, without being dependent on their IT personnel. In the so-called digital age, businesses should learn to master data and make it work for them. Below are a few ways an IMDG can help take businesses to the next level.
- Access to real-time data
With fresh data to work with, businesses can make the best possible decisions at the appropriate time. An IMDG ensures fresh data each time by providing access to data as soon as it becomes available instead of days after they are processed.
- Integration of data
Data sources can be varied and are often disparate systems, making them challenging to sort and process quickly. An IMDG allows for the integration of data from different sources and provides a centralized platform from where users can interact with the data to generate reports.
- Visualization of data
Filtering can be challenging and complicated, especially if they originate from disparate systems. Trying to decipher data and determining what’s valuable to the business is important, and data visualization tools allow users to see data through graphs from which reports can be generated. These reports can then help provide actionable insights and determine the organization’s next steps.
The Power of Data
Mastering data management is mastering business in the digital age. Data processing solutions are tools that will streamline a company’s data strategy and operational processes, but only if they make the effort to understand these platforms. While data processing data at high speeds is important, this must be done without negatively affecting data integrity. In an ever-changing business landscape, the data gathered, stored, and processed should remain consistently accurate for it to provide the best results—results that will lead to accurate predictions and actionable insights.