9 Big Data Challenges of 2021

Rodrigo Inostroza, 2020-12-23

From better Machine Learning technology, development of tools for qualitative analysis, to revolutionizing the health industry and climate change research, Big Data will play a key role in 2021. Continue reading to know more about Big Data challenges of 2021.

1. Instant Data Stream Handling: One of biggest Big Data challenges for 2021 is to be able to focalize the efforts on data that actually serves business decisions in real time. Many companies are generating data by the second, which requires better analysis solutions that are able to ingest and process data continuously rather than in batches. This continuity ensures that no data is lost, like it does happen when you brake it into batches. Applications of data stream handling in our every day are, for example, self driving cars.

2. Improving Data Culture in Companies: Companies will have to better themselves at having a cohesive Data Culture through all aspects of their production chain. This goes from individual contributors and employers to business leadership. Having clarity on all levels will create a more efficient cycle of data analytics inside the company. Using modern practices such as agile processes, scrum teams, and open communications it is possible for organizations to take advantage of true digital transformation through data driven decisions and advanced analytics.

3. Smart homes? Think smart cities: The IoT has seen revolutionary advancements with the use of Big Data. The smart home experience for example, has reached groundbreaking advancements, like Honeywell's smart thermostats that use machine learning to know home owner's habits. This trend will slowly but surely start applying to making our cities smarter. The Big Data challenges in this scenario, according to researchers in the University of Pennsylvania, would be to "improve the performance of health, transportation, energy, education, and water services leading to higher levels of comfort of their citizens."

4. Natural Language Processing: Natural language processing techniques is a subfield of linguistics and artificial intelligence that uses computational methods to analyze human nuanced language. The idea is to allow better interactions between ourselves and computer intelligence, where the AI is able to detect, for example, different unstructured qualities of our spoken language. One of the Big Data challenges of 2021 for every business is to provide better customer service, which is why many are implementing NLP techniques to integrate virtual customer assistant, or chatbot technologies, to their different contact channels.

5. Augmented Analytics will dominate: As Gartner has defined, Augmented Analytics is an approach to analytics that automates insights using machine learning, AI, and Natural Language Processing. It relieves companies dependency from data scientists by automating insight generation by using advanced machine learning algorithms and artificial intelligence. These Big Data tools are basically analyzing themselves to figure out a better, easier and more straightforward way to create insight for the company's different interests.

6. Accessible Data Management as a service: Cloud based services are already the staple of how to store data that can be used by anyone anywhere in a company. Data lakes and flexible storage environments should be more accessible than ever before, not only in accessing the data, but allowing new forms of visualization, analysis and predictive modelling. In other words, cloud based services will need to up their game to offer new tools for processing the data their storing.

7. Data Security: With more data generated exponentially through time, the necessity for privacy and security of data has become one of the main Big Data challenges of 2021. The challenge relies on a lack of skill in the market, where cybersecurity specialists are not enough for the demand of security (according to Cybercrime Magazine, unfilled cybersecurity positions will reach 3.5 million by 2021). Another interesting aspect of cybersecurity for big data is how the Blockchain technology will be applied to offer security due to a network architecture that is difficult to counterfeit or change.

8. Big Data uses for the Health Industry: With the world going into crisis mode after the Covid-19 pandemic, the creation of vaccines has seen an incredible change in the way they are created. With the use of Big Data analytics, scientists are able to predict protein structures with further develop the understanding of how viruses operate and react to different medicine. This was the case of Google’s Deepmind, which was able to determine 3D shapes of proteins decades before scientists expected to solve the problem.

9. Big Data uses for climate change: If not the biggest Big Data challenge of 2021, it is surely one of the most urgent. Big Data technology will be key to reduce the carbon emissions of the world, where the combination of meteorological data, earth sciences, ocean research, and even nuclear facilities, will shape the future for better urban planning, transportation and energy efficiency.