Data plays a major role in today’s business processes—from marketing to streamlining internal processes. The data companies need to process grows larger each day, and companies need a way to process all this data efficiently before they can make sense of it. Data analytics has become ingrained in business and marketing, so much so, that 49% of respondents from Deloitte’s Analytics Advantage Survey say that analytics helps them make better decisions.
Data is vital for businesses because it helps visualize performance. It helps give a number to what is usually an abstract concept, helping companies measure performance metrics and modify them as necessary. Even business processes benefit from data analytics because it helps turn feedback into actionable items that help improve and streamline workflows. Essentially, data provides a deeper understanding of preferences and behavior that can help improve a company’s overall performance.
An in-memory data grid (IMDG) can help companies process big data and transform them into actionable insights that will help stakeholders make sound business decisions. It works by running specialized software on all computers within a network or “grid.” These computers interact with each other and combine computing power to process large jobs that cannot be achieved by a single computer. A data grid is typically composed of computers that are spread out across geographically remote sites that share data and resources with each other. Commonly known as grid computing, the objective of a data grid is to leverage the combined power of the computers within the grid to accomplish large, complex tasks.
The Data of Business
A data grid can provide your business speed, scalability, and simplicity when it comes to data processing, making it a viable solution for companies that handle large amounts of data. Currently, data grids are used in a variety of use cases due to its flexibility. One of the most common and apparent uses of a data grid is as a huge data store. Using several computers within a grid, aside from providing ample amounts of memory, makes the shared data collaborative, since data can easily be shared by the entire site. The data grid also allows the computers to coordinate with each other so that data sharing is seamless for all grid users despite geographical location.
Another use case where data grids have been very useful is microservices, a set of software applications designed to work with each other on a limited scale to create a bigger overall solution. Each microservice is designed to do a specific task and to be “good” at it. They are not designed to be solutions in themselves but to coordinate with each other to perform smaller microservices that contribute to that solution. This makes the workflow efficient and consistent when it comes to quality of output.
Data grids can also be used as a backbone for private cloud computing, which is a common platform used by a number of companies today. In a private cloud system, computers within a network power virtual machines for users. Similar to public cloud services, virtual machines in a private cloud only use a portion of the power of a physical computer. The only difference is that a private cloud is owned wholly by the organization that operates it. This is an efficient solution for organizations with short-term computing needs because resources are freed up immediately once they are not in use, allowing other tasks to make use of them.
An IMDG is beneficial in all these use cases since it processes data using the computer’s main memory (RAM), allowing for data access at breakneck speeds. Because data is stored in-memory across all computers within the grid, it limits data movement within the network and allows both data and the application itself to collocate in RAM. An IMDG is the ideal solution for companies that require high throughput and low latency because it does away with the bottlenecks caused by disk-based storage. It allows for synchronicity of data that makes data retrieval and updating easier and application development quicker and more efficient.
The Business of Data
When it comes to big data, businesses rely on speed, simplicity, and scalability, so companies need a platform that offers the same characteristics. IMDG allows for high-speed data processing and simplifies scaling and acceleration of applications so companies can focus on improving performance and not on implementing computing platforms. Technology has developed enough to allow for the transformation of data to real-time insights, and the IMDG is the practical application of this concept.
As companies gradually transition into cloud-based platforms, an IMDG remains a feasible solution because it allows for a hybrid configuration that supports cloud and on-premise platforms. The key is ensuring that applications and services run on both—effectively ensuring a future-proof system.