Big data and analytics have started to transform the modern industry in a big way. These days, data analytics domain witnesses a paradigm shift from adapting the ways of traditional analysis to adopting the big data analytics. The role of big data analytics becomes more crucial when it comes to making subjective decisions like branding and hiring people.
In such a scenario of massive shifts in approaching and implementing big data analytics in the corporate sector, let’s make a list of ten key trends and predictions for the year 2020 and beyond.1. IoT, Data Analytics, and Digital Twins
Looking at the growth of IoT technology in recent years, we can certainly expect that we will have more than 38 billion connected devices by 2020. All these devices will fetch data for analysis and it will directly increase the scope and value of data analytics. Led by large enterprises, even SMEs will also rely on IoT devices to perform their daily operations seamlessly using big data analytics.
In the coming years, we will have more analytics solutions designed for IoT devices. These solutions will not only provide relevant data but also offers transparency. The exponential growth of IoT in recent years is responsible for the growth of digital twins or digital replicas of physical objects or people. Digital twins will also be in billions in line with billions of IoT devices.2. Data as a Service (DaaS)
As per the IDC research report, up to 90% of large companies will generate some sort of revenue from DaaS (Data as a Service) in 2020. DaaS is a cloud-based technology that enables customers to access various digital files with the help of the Internet.
With the roll-out of 5G in 2020, DaaS will become more prevalent. Its globalization will assist in bridging gaps between various departments in the well-established companies that need to share data but cannot do it because of technical issues. It is fair to mention that DaaS will make the data sharing process quicker and easier for companies while improving their productivity.3. Augmented Analytics
We will witness the steady growth of augmented analytics in 2020. This concept has already shown its potential in the corporate sector in creating a unique way of creating, developing, and sharing analytics. Augmented analytics can combine AI techniques with ML (Machine Learning) to bring revolutionary changes in data analytics.
It is predicted that the augmented analytics market will grow to almost $18.4 billion globally by 2023. In such a scenario, there will be no surprise if this trend will become highly popular in the near future.4. Data Security and Privacy Protection
Data security concerns will be increased with time as more companies will opt for data sharing and analytics. It is expected that almost 30% of large enterprises will use backups and snapshots to ensure safety, privacy, and reliability within the security management portfolio.
Surprisingly, many organizations have no intention of using their backed up data with personal and confidential information. In the coming years, we can predict that more companies, irrespective of their size, will emphasize on data security and privacy protection. It will certainly increase the importance of back up.
Gartner has predicted that both edge computing and cloud computing will become complementary models to each other. This trend will eventually decrease latency and data-processing costs for organizations by 2020. Some experts are of opinion that edge computing will help increase data security by combining with analytics. This is fairly attributed to the decentralized approach of edge computing that enables data processing at the local level and minimizes the need to send data over other networks.
In contrast to this approach, some experts claim that edge computing-based devices can be easily hacked due to a lack of IT security protocols. It is interesting to see how the explosion in edge computing and data analytics will shape the big data domain in the future.6. Cloud-based Data Analytics
Cloud computing has become an umbrella technology for big data, analytics, and even ML. Until recent times, the focus has remained on the tools and various processes to get a better understanding of stored data. But, as cloud technology is getting mainstreamed in the corporate world, the full scope of data analysis becomes visible and the entire system can get the benefits of real-time data analytics.7. Dataops
The DataOps concept has gained ground in the year 2019 with the advent of more complex data pipelines that required more integration tools. DataOps involves both Agile and DevOps methods to the entire lifecycle of data analytics. From collection to analysis and testing to delivery- DataOps can support big data and analytics in several ways. It promotes collaboration and improvement in quality while using statistical process control for the data pipeline.
In the coming years, this trend will get more importance in the data analytics domain.8. Regulation Requirements
The implementation of GDPR is just the beginning of an era of prioritized data governance. Though it has a great impact on various companies worldwide and many companies are yet to comply with it, we can say that the year 2020 onward, we will have more regulation requirements in the data-related fields. The California Consumer Privacy Act is ready to come into effect from the year 2020. These rules and regulations have a lasting impact on data processing, handling, and security.
We can certainly expect that these requirements will keep business persons on their toes for understanding the impact of regulations on various operations. As a result, the demand for data analysts with skills in data privacy and security will remain an all-time high.9. ML and Big Data
Gartner has predicted that more than 40% of all data science-related tasks will be automated by 2020. ML (Machine Learning) technology and its advancements can drive this automation. This concept is capable of fetching insights that even the skilled data analysts cannot do manually. The entire process is also faster and more accurate than the same done by humans. ML and big data combination can help the organization boost efficiency and reaction time to particular events. Also, with AI (Artificial Intelligence), ML can provide high-quality data analytics functionality.10. Business Intelligence (BI)
Gone are the days when the data analyst or data scientist was kept alone in a tower and stayed away from the organization. Time is changed and the data scientist now interacts directly with various teams and the company’s decision-makers. It means that data analysts must be able to communicate with non-technical professionals on complex and technical subjects. In other words, communication becomes a necessary soft skill for implementing BI (Business Intelligence).
Along with this, BI requires domain-specific skills like programming skills in SQL, tool experience, and problem-solving techniques. Even the data analyst consulting includes business intelligence and in the coming years, this trend will become more prevalent than ever.
Apart from these trends, we can expect those conversational analytics, Enterprise Content Management (ECM), and personal assistant technology will also dominate in the domain of big data analytics.
All these trends will give rise to data analytics consulting services as entrepreneurs will jump on the big data bandwagon. From grabbing the opportunities and increasing efficiency to providing improved customer experience, these trends will help companies to achieve the right growth.Concluding Remarks
‘Smart’ will become a new norm as we head into 2020. A combination of emerging technologies with big data will bring digital disruption in modern businesses. All these data and analytics trends will change the method of industrial processes over the period. We can certainly expect that in the coming years, we will have more intelligent and smarter systems thanks to advancing big data analytics.
At Silver Touch, we provide the best-in-class big data and analytics services to transform your business processes into more customer-centric and result-oriented. Our Big data solutions are intelligent and innovative enough to provide actionable data and quick output. Do you want to know more about our Big Data Analytics solutions? Simply send us a mail at email@example.com for big data consulting.