2020 Top 10 Big Data Predictions 

by | Oct 28, 2019 | Blog

Big Data Analytics is rapidly reshaping the landscape of sales and marketing. As more businesses adapt to using big data, the way campaigns are managed, audiences segmented and social media blasted will be increasingly personalised. In 2020, the predictions for big data will see data leveraged more effectively to meet the needs of businesses.

Data Analysis Automation

Automation is used in most industries to improve business and productivity and by next year we can expect to see more than 40% of data-based tasks automated.

Automation assists decision-makers by efficiently helping to predict further ahead than traditional methods. With correct analytics, decisions are made easier for business leaders.

In-memory Computing

The cost of memory has decreased in recent years making in-memory computing (IMC) a mainstream technological solution. The costs and complexity of IMC solutions are reduced by persistent-memory technologies, a new memory tier that is situated between NAND flash memory and dynamic random-access memory.

It provides highly effective mass-memory to support high-performance workloads. This is highly valuable to organisations as they require not only much faster CPU performance, but also quicker storage and larger quantities of memory.

Many industries are adopting IMC to help improve application performance and provide scalability options.

The Rise of DaaS

It is predicted that up to 90% of large organisations will next year be generating some revenue from data as a service (DaaS). DaaS is a cloud-based technology that allows customers to access digital files via the Internet.

High-speed Internet and DaaS are helping globalised organisations share data and files in realtime, which is changing the way that business and employees are interacting.

The IoT and Data Analytics

It is expected that next year, there will be more than 20 billion active IoT (Internet of Things) devices. This means there will be more devices from which to collect data for analysis. In organisations where IoT devices are used in daily operations, capable data analytics are being implemented.

This means more data to leverage for marketing and growth opportunities.

Security and Privacy of Data

In 2015, less than 10% of large corporations were making use of backups and snapshots for more than just recovery. By next year, it is expected that 30% of these corporations will be making use of backups and snapshots for safety, privacy and reliability within their security and identity management portfolios.

Privacy risk in the form of archived personal data will be the largest concern for 70% of organisations in 2020. For this reason, the right solutions for protecting your data need to form part of ongoing technology upgrades.

Mobile Phone Use Developments

More than 50% of consumer mobile interactions will be hyper-personalised by next year. Big data has been used to create autofill solutions, send emails, generate personalised ads and send geo-targeted promotions.

Personal Assistance Technologies

Personal healthcare assistance in the form of devices and robotics has not come as far as predicted 5 years ago. However, the industry is developing the technology for personal care robotics and devices that help to manage healthcare.

Personal robots are set to be a US$18.85 billion opportunity next year. The Asian market for robots in China is expected to emerge as one of the major countries expected to provide innovative, low-cost autonomous mobile robots in the next few years.

The advent of AI is resulting in smart autonomous bots that will eliminate manual tasks. This year, 2.5 million industrial robots were introduced as part of the future workforce, with 42 million service bots operating for domestic use.

Automatic Management of Enterprise Content

Technology is slowly taking over manual tasks with 95% of image and video now automated. The ECM market is estimated to reach US$59.87 billion by 2020. Content management solutions within enterprises are changing as new technologies make these processes more efficient.

Machine Learning and the Cloud

Cloud storage safely stores digital files and third-party solutions have improved the security and efficacy of the service in the past few years.

It is predicted that by 2022, 60% of vendors will rely on cloud storage solutions. It is also predicted that hyper-scale cloud providers like Microsoft, Apple and Google will be making use of cloud-based machine learning to acquire a 20% share of the market in platforms for data science.

Conversational Analytics and Natural Language Processing

Up to 50% of analytical queries will be either automatically generated or generated using voice or natural language processing (NLP) in 2020. Simple search interfaces will mean that analytics are easy to use and report on and developing results through the use of the technology will be made easy.


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