The Top 10 Big Data Trends to Watch in 2021
Big data has been a buzzword for years, with companies generating vast amounts of data from various sources. The challenge is how to make sense of it all to derive valuable insights. With the advancement of technology and access to new data sources, here are the top 10 big data trends to watch in 2021.
1. Artificial Intelligence and Machine Learning
AI and machine learning technologies are becoming more prevalent in the world of big data. Data scientists can use these tools to build predictive models, find patterns and anomalies, and make recommendations. AI and ML technologies also allow businesses to automate mundane tasks, improve operational efficiency, and reduce costs.
2. Edge Computing
Edge computing involves processing data at the network’s edge, closer to where the data is generated. It reduces latency and ensures data privacy and security, making it suitable for use in industries such as healthcare and finance.
3. Cloud Computing
The rise of cloud computing has transformed the world of big data, making it more accessible and cost-effective. Cloud computing providers offer scalable infrastructure, ensuring that businesses can easily store, process, and analyze large volumes of data.
4. Natural Language Processing (NLP)
NLP allows computers to understand human language and speech. Its use in big data analytics helps businesses to gain insights from unstructured data such as customer feedback, social media posts, and audio recordings.
5. Blockchain
Blockchain’s secure and transparent nature makes it a suitable technology for big data. Businesses are exploring the use of blockchain to secure their data, increase transparency and trust, and enable secure data sharing.
6. IoT
The Internet of Things (IoT) has grown exponentially, and the volume of data generated by connected devices is vast. IoT devices are used in industries such as healthcare, manufacturing and logistics, allowing companies to collect data from sensors and devices to optimize operations and improve service delivery.
7. Dataops
Dataops, the integration of data management with DevOps, is gaining traction. It involves automating the processes of managing, testing, and deploying data pipelines and models. With the increase in data privacy regulations, businesses can use dataops to ensure data protection compliance.
8. Data Democratization
Data democratization refers to making data accessible to all employees within an organization. It reduces the siloed approach to data management and enables decision-making at all levels of the organization. By democratizing data, businesses can unleash the untapped potential of insights from different parts of the business.
9. Data Ethics and Governance
Data ethics and governance have become more important as data privacy regulations have become more stringent. Businesses must have robust processes to ensure that they handle data ethically and transparently while complying with regulations such as GDPR, CCPA and LGPD.
10. Augmented Analytics
Augmented analytics uses AI and machine learning to help data analysts and business users to find insights quickly. By automating insights discovery, businesses can optimize resources and gain a competitive advantage.
In conclusion, businesses must keep up with the latest trends in big data to remain competitive. By leveraging these trends, businesses can gain valuable insights from vast amounts of data, automate mundane tasks, and optimize operations. As big data continues to evolve, businesses that stay ahead of the curve will undoubtedly reap the rewards.
