The big data analytics has already hummed its tune of utility by virtue of its amazing competence of processing and visualizing the data in most proficient way possible. This has lent a hand to many of the businesses to fly with new colors of data success.
Businesses are leveraging big data for the benefit of driving insights and initiatives. The insights generated can be used further to extract maximum meaning from the data. These insights and results must be monitored and fed back into the system in a programmed way for further utilization. There is no doubt about the alliance of analysis and visualization can be further enhanced with the help of scalable computing tools. We will have a brief overview of these concepts in this article step-by-step.
What is Big Data Visualization?
Visualization intends to merge the big data processing capabilities of analytics with the human capabilities of visualization. Simply, it is a demonstration of data in a pictographic or graphical presentation. It empowers data analysts and end-users to monitor analytics output visually, so they can have a clear insight of critical patterns and impactful factors hampering the process or business. Data visualization also run real-time on streaming data. It also helps in tracking any change in attribute value.
Why is Visualization Important?
Visual data has 68% more interaction capability with a human brain over written one, because of the way the human brain processes information, using charts or graphs. Also, visualizing large amounts of multi layered data is easier than getting it done on paper reports. Data visualization is a swift and easy going way to convey concepts in a more sophisticated way. Irrespective of business or scope, all categories of businesses are expanding data visualization capabilities to make use of their data. Here’s how it helps,
1. Identify factors influencing the business.
2. Understand data thoroughly
3. Recognize interactions and patterns
4. Determine evolving ideas
5. Trace out areas that need enhancement.
Which are Leading Tools for Data Visualization?
For fruitful data visualization, tools are the precise weapons one needs. Here are the topmost of them,
4. Fusion chart
7. Microsoft Power BI
8. Oracle Visual Analyzer
What is Scalable Computing?
Scalable computing is a process of using a dynamic computing system that can change as per the need of more dominant computing abilities. Scalability is a desired component for a network, data, practice, or a business strategy.
Why is Scalable Computing Important?
Big data has entered into many businesses pretty rapidly, and thus the emerging performance graph for treating the large volume of data is very vital. Data is dynamic, and it has to be fed to the system as input to cope up with the equally dynamic business needs. In addition to performance, scalability is also a strategic contemplation in context with big data integration. Better performance and scalability can be integrated to use employee time effectively, ultimately boosting productivity, for instance.
Scaling implicates adding further servers for backing the general utilities and computing necessities across different resources. It helps applications to effortlessly extend it vertically or horizontally. Vertical database scalability adds more capacity to a single machine while horizontal scalability increases capacity by adding more machines. Horizontal scalability compliant architectures go nicely with the cloud computing services.
Many hardware and software load balancers are available commercially. An amazingly scaled up architecture can support scaling to 4-8 servers horizontally, thus by growing application throughput by 600-900%. As big data continues to grow, these high-performance, flexible and scalable infrastructures are becoming even more important for companies.
Data growth and scalability are some of the hottest and most important topics in today’s fast-growing applications. Not only data is growing exponentially, the rate at which we receive data from various sources is accelerating at a dramatic pace. As a result, organizations need to blend their scalable data-streaming infrastructure with visualization tools to enable interactive exploration of insights in real-time. Developing infrastructure that demonstrates the scalability of systems to allow large data visualization will prove beneficial and will significantly improve business performance.