Data analytics has become an inevitable part of every industry. Not to mention, Big data analytics is the key technology working behind this analytics. Processing of such terabytes and zettabytes of data at one end provides real-time insights. Besides, with new evolving technologies, Big data landscape is changing with time.
Whether it is increasing the use of the Internet of Things or Big data machine learning combination in the business fields! However, at present, the most interesting question is how this enormous data will change the Big data landscape 2020?
Read more – 8 characteristics of Big data
The changing Big data landscape 2019 shows a clear indication that multiple factors are working behind to change the Big data technology landscape. Interestingly this changing Big data landscape will eventually change the Big data market landscape. So, let’s focus on the areas and how those factors will change the Big data landscape 2020.
Factor 1 # Growth of use of Internet of Things and more data generation
With more focus on the Internet of Things and AI, we live in the age of smart technology and smart devices. Ultimately, these devices generate a massive amount of data that will reach up to 44 zettabytes by 2020.
As per the IDC report on 3rd October 2016 in "Worldwide Semiannual Big data and Analytics Spending Guide," Big data market will hit $203 billion by 2020. In the words of IDC’s Dan Vesset: "The availability of data, a new generation of technology, and a cultural shift toward data-driven decision making continue to drive demand for Big data and analytics technology and services."
As data continues to grow, the shift will harness those data to get the business insights. No doubt, this will ultimately proliferate the use of Big data and related technologies.
Read more - 5 Big data analytics trends for 2019 expected to influence Artificial Intelligence
Factor 2 # Automation in analytics a new game changer
Big data analysis is a real challenging task as it associates with data preparation load, operational cost, efficiency, and a considerable amount of time. Furthermore, human effort in such massive data handling often causes accuracy issues. Automation in Big data technology landscape can be a revolutionary turn as it has several benefits, which include:
-For predictive analysis, decoding complex algorithms take months. However, with the implementation of automation, it will take only a few hours.
-We can expect nearly 96% accuracy with automated analysis.
-Data preparation through automation works in a more streamlined way.
-Through automation, it is easier to detect the data feature prediction.
Hence, the automation of Big data Analytics will give a new face to data science practice as data scientists. Thus the business won’t need to dig deeper into its operational complexities. Furthermore, it will be cost-effective and accessible. This will help the data scientist concentrate on the competency build up rather than spending time on trivial data analysis tasks.
Factor 3 # Enhanced use of Big data machine learning in Big data landscape
Big data Machine learning will contribute to predictive analysis, which will help businesses foresee market trends. This will also enable them to decision making easier.
Interestingly, the proliferation of Big data will expand the learning and procedure scopes of machine learning. This was a roadblock for a long due to a lack of data. With a large amount of data now, the experiment and learning will be easier.
Factor 4 # Prescriptive analytics will get a new edge
Mainly three types of data analysis happen in data science –
1.Descriptive analysis – Provides insights on historical data
2.Predictive analysis – Provides insights in future data
3.Prescriptive analysis – Provides advisable analytics reports for the future
The first two analysis is widely practiced with Big data. However, prescriptive analytics is a complicated procedure and uses machine learning, simulation, etc., for decision analysis. With the growth of Big data usage, prescriptive analytics will also grow exponentially and contribute to automated analytics. This will change in Big data strategy as a whole.
Factor 5 # Big data as a Service (BDaaS) will become more popular
With the vast amount of unstructured data generation, analyzing those data for predictive analysis will be a real burden for companies. Furthermore, it will be more cumbersome with in-house resources and tools. Big data as a service is a combination of Data as a Service (DaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).
BDaaS = Data as a Service (DaaS) + Platform as a Service (PaaS) + Software as a Service (SaaS).
Thus, Big data as a service intends to provide this analysis service by some outside vendors. Not to mention, this will become a competitive advantage for the companies. As per the statistics, Big data as a Service (BDaaS) is expected to grow nearly 15% of the Big data market landscape. This will act as a managed service and will rely upon cloud storage for data access.
In addition to that, BDaaS will help provide real-time insights on the data and keep the data privacy intact.
Factor 6 # Big data will change the business landscape
Today it is not the business size that determines whether it will use the Big data or not. Almost all businesses are harnessing Big data to get better market insights. Thus, with advanced business intelligence, predictive analysis, the business can determine the product choice inclination of the customers.
The analysis will also answer what kind of customer services they are opting for, cost optimization of the product, etc. Also, it will help in increasing the ROI of the companies.
Final verdict
Big data, no doubt, has been considered a key enterprise data management system. Consequently, many Fortune 1000 companies have allocated a budget for upgrading their analytics and Big data infrastructure. This will ultimately replace older Big data technologies. The core infrastructure will continue to mature with the robust combination of Big data and AI.
Big data landscape 2020 shows a golden year ahead. Besides, if we consider the overall Big data industry, it consists of services, storage, security, infrastructure, applications, analytics, etc. Hence, it shows a huge career opportunity in Big data analytics and Big data field.
Please share your valuable inputs in comment area to make the article more informative.