Big Data Analytics is transforming the industries and organizations, and businesses are adopting it fully to go beyond the traditional ways of analysis.

Currently, Big Data Analytics is making some remarkable changes in the decision-making landscape of business. It is reflecting business performance, providing actionable market and customer insights, and helping business leaders in making clued-up decisions. Till now, we have seen how big data analytics is making a huge shift in how business is being done. But, it is exciting to see what this powerful technology holds for us in 2020.

Therefore, here in this blog, we have rounded up the top eight big data analytics trends to watch for 2020.

1. IoT and the Growth of Digital Twins

There are so many technologies that are expected to change the current business landscape in 2020. It is hard to keep up with all that. But, IoT and Digital Twins are expected to pick up traction in 2020.

As per the study, 42% of organizations that have IoT solutions in production or IoT projects in progress are planning to use digital twins within the next three years.

Digital Twins are simply a digital representation of a physical object or system. Business applications and system leaders can use digital twins to decrease complexity in their IoT ecosystem as they can run simulations before actual devices are built and deployed.

2. Augmented Analytics

No doubt, the augmented analytics will become dominant in the next few years. It has shaken up the industry already by merging artificial intelligence and machine learning to craft new ways of creating, developing, sharing, and consuming analytics. Nowadays, it is one of the most popular technologies to use for business analytics. Augmented analytics offers the following benefits.

It can automate many analytics capabilities, such as preparation, analysis.

With it, one can easily interact with the business models and insights generated.

3. The Harnessing of Dark Data

Dark data is a kind of unstructured, untagged, and untapped data. It acquired through various computer network operations but not used in any manner to get business insights or make business decisions. Dark data is not just a small piece of Big Data, but it is the biggest and fastest growing. It holds considerable potential for those who can harness it fruitfully. As per the study performed by IBM recently, it is expected that by 2020, 93% of data will be dark and unstructured. By merging structured and unstructured data sets, companies can achieve high-value results.

4. Data-as-a-Service

Today more and more companies, who have a large amount of data, want to get into data analytics so that they can get better insights on their business and customers. But, just collecting data is not the final step. It is just the beginning. The organization must adapt a cloud-based technology such as DaaS to support bridging between departments within the larger organizations for data sharing. With DaaS, they can share data in real-time, easily, and quicker. It is expected that 90% of big organizations will be able to generate revenue from DaaS in 2020.

5. Data Storytelling and Visualization

Data storytelling and visualization will become more established in 2020 as these days, more and more organizations are moving their traditional and siloed data warehouse to the cloud. It will help their employees and stakeholders to tell a great data-driven story to customers. So, it will drive better decision making within an organization. It will help with lead generation and better customer retention.

6. DataOps

The latest technological workflow to come up from the fields of IT and Big Data professionals are DataOps. It is not to be confused with DevOps. DataOps focuses on how to cultivate, manage, and process data with agility and accuracy so that end users can have insights quickly.

It can be useful to make critical decisions. It is collaboration between different fields like data scientists, engineers, and managers, which helps to keep everyone on the same page at any time of the data analysis life cycle. So, by applying DataOps, everyone benefits.

The main thing that you should keep in mind for best performance while you implement DataOps is make data open in your organization, leverage open-source tools, and automate most of the processes. It is expected that by the end of 2020, many companies will fully experience the potential of DataOps.

7. In-Memory Computing

It is expected that over the next decade, more and more businesses will start using in-memory computing platforms. As per the study, by 2021, the in-memory market will reach the $15 billion mark. In in-memory storage, data is stored in RAM across multiple computers instead of one centralized database. It results in faster performance and scaling of data in real-time. Of course, the cost of storing all data in memory will be high but a viable solution for it is a memory-centric solution that supports the use of other memory and storage types.

8. Cold Storage and Cloud Cost Optimization

Migrating data warehouse to the cloud is nearly less expensive than an on-premise build. But, it doesn’t mean that your cloud system cannot be cost-optimized further. With this intention, in 2019, more organizations turned to cold data storage solutions like Google’s Nearline and Coldline, and Azure Cool Blob. Keeping unused and older data in cold storage can save organizations almost 50% on storage costs. So, organizations can free up cash in data activities that can generate sky-rocketing ROI instead of the money drain.

Wrapping Up

Briefly, if businesses want to guide their digital transformation along the right path and achieve success in years to come, they must keep themselves updated with the latest big data analytics trends. If businesses smartly bet on big data analytics, it can keep them ahead of the curve, the competition, and the threat of obsolescence.

Source: datafloq.com