September 6, 2019 Last updated September 6th, 2019 5,064 Reads share

The Exponential Growth of Big Data

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With Big Data solutions gaining traction, it is evident that the technology has outstanding growth possibilities now and in the days to come. The market for Big Data is estimated to cross $100 billion by the year 2020, which is now roughly at $25 billion. Again, Big Data analytics solutions have no indications of slowing down and are in much demand. It is expected to touch the $40.6 billion mark by the year 2023. Besides, the technology will have a significant effect on the world economy together with the industrial internet improving global GDP by $10 to $15 trillion in the next 10 to 15 years. Therefore, you can see that the aggressive growth of Big Data solutions will continue in the future. 

Today, machine-based and human-generated data are witnessing an overall growth rate of 10 times faster than conventional business data. When it comes to machine data, it is experiencing an exponential growth rate of 50 times faster. It is no wonder why Big Data solutions companies are hiring people skilled in this technology. 

The act of acquiring business information with Big Data analytics solutions and its interpretation into actionable insights go past data centers to the edge as well as into the cloud in an unspoiled hybrid setting. Information processing together with analytics systems comes with special features for efficient computing and business analytics. Read on to learn more about the exponential growth of big data. 

HDPA is at the Core of Big Data Analytics 

With the inception of Big Data and computing, there has been a convergence in Big Data, big compute, and the Internet of Things (IoT). The International Data Corporation (IDC) classifies such union as high-performance data analytics (HDPA). The high-performance data analytics (HDPA) market is at the core of big data analytics and a major driver in the integration of data-exhaustive computing. It helps Big Data solution providers to scrutinize loads of data fast at the creation point we well as at scale. 

Today, Big Data solutions companies can access robust and affordable computing platforms, as well as up-to-the-minute software such as Spark and Hadoop enabling real-time analytics for a plethora of use cases. These include business intelligence (BI), fraud and glitch detection, product design and development, personalized medicine, affinity marketing, and process automation. Besides such software frameworks, employing storage capabilities as well as competences that improve the flow of data, storage performance like high-efficiency distributed file systems and object storage, and in-place analytics, is crucial for efficient scaling. 

Major Initiatives for Big Data Use and Growth 

Based on an IDC survey on the critical digital transformation projects, the participants mentioned that IoT (32 percent), Big Data solution (27 percent), and cloud transformation (66 percent) are the key initiatives behind the implementation of big data and its development.  

IoT forms the base for investment in Big Data services, Big Data computing, and the cloud offers scalability. According to IDC, all business analytics applications would integrate regulatory analytics based on cognitive computing technology. Moreover, the volume of valuable data or information will increase two-fold, thus making 60 percent of data delivered to decision-makers or business leaders actionable. 

Key Drivers Leading to the Exponential Growth of Big Data 

You know that the market for big data is booming and more big data solution providers are embracing the technology more than ever. But why? Here are some of the major reasons:

Huge Data Volumes

Today, you have more information compared to the past and more data explosion is expected in the coming years. Numerous studies show how the world’s yearly data collation increased from around 1-2 Exabytes back in 2000 to 2,700 Exabytes after 12 years with an estimation of 40,000 Exabytes in the year 2020. It is not all astonishing because businesses and Big Data services continue to incorporate data from their operations, public departments, customers, partners, and third parties. 

More Innovations in Software Development

You will find numerous developments and innovations for unorganized data. Today, most data is not structured including audio, social media posts, videos, research articles, and photos. NoSQL and Hadoop, for example, are offering machines and humans to chomp huge data volumes. Then, the majority of these software applications are open source as well as available on Software-as-Service model, thus having a deep and significant outcome. Therefore, you must look for Big Data consulting services, which have in business for some time. 

More Activities in the Futuristic Technology Space

Did you know that analytics algorithms have made progress in numerous areas, especially in machine learning? It has led to activities in the futuristic technology space in numerous areas. These include artificial intelligence, robotics, fraud detection, speech recognition, medical diagnosis, and facial recognition. The progress in analytical algorithms led to the disruption of numerous domains such as retail, financial sector, and weather forecasting with enhanced abilities to foretell what’s is expected in the future. 

The Issues in Data Growth

Even experienced Big Data services companies dealing with high-speed and voluminous information face certain problems. These include data center power, space restrictions, and cooling. The other issues are system management and problems in the growing cluster, data storage, management intricacies, and movement of data. 

Though there is much demand for Big Data, there is a dearth of the right skill sets to incorporate and control the big data ecosystem. There is also a shortage of proper support when it comes to diverse environments as well as accelerators. 

Better Infrastructure Results in Improvement 

Big Data services companies are examining and employing the right infrastructure to drive improvement including enhanced flexibility, managing the operational expenses and development of big data infrastructure, fast deployment, scaling infrastructure, and ensuring performance for varied workloads, and simplify management with Big Data as a Service (BDaaS). 

Final Words 

The phenomenal growth of Big Data has resulted in operational efficiency and maturity of the Hadoop data system, thus making it simple for the easy, affordable deployment of the same at the organizational scale. Therefore, the demand for Big Data consulting services has increased in the last couple of years and going to skyrocket in the days to come.

David Smith

David Smith

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