With the explosion in cloud adoption, enterprises will continue to focus on digital transformation. Many companies are moving data, using analytics, and exporting business use cases to the cloud. Cloud adoption and cloud migration will continue to gain momentum in 2022 with the introduction and acceptance of DataOps, 5G, and edge analytics playing key roles in the digitisation journey. Let us see what we can expect in 2022 in the field of data engineering.
1. Increase in adoption of DataOps
Organizations will practice DataOps to improve data quality and reduce insight deriving time. DataOps helps in building and delivering trusted, consumption-ready data pipelines to the data analytics team. Most businesses use different tools for data ingestion, data preparation, and pipeline orchestration. Hence, there is a high demand to automate data flow and manage pipelines using a single dashboard.
In 2022, DataOps will come into implementation from on-paper research. DataOps methodologies combined with the pipelines will increase agility and achieve business value faster. Organizations will learn to implement DataOps in their existing multi-cloud and hybrid environment.
2. Improved analytics with launch of 5G
In recent years, edge computing has evolved significantly. However, its adoption was low due to latency limitations. With the launch of 5G worldwide, this limitation is no longer present. Data computation and storage will move close to the source, and communication between edge devices will occur at superfast speed. It will help in collaborating analytics for real-time decision-making. Hence, cloud service providers have started to provide edge computing services.
3. Migration to hybrid, multi-cloud, and edge environments
According to a report by Gartner, investment in public cloud services will grow from $396 billion in the last year to $482 billion in this year. Enterprises are looking forward to more hybrid, multi-cloud, and edge environments are paving the way for new distributed cloud models.
Companies adopting the hybrid, multi-cloud model will see a boost in speed and agility, reduction in complexity and costs, and strengthening of cybersecurity. McKinsey predicts that 70% of the companies will use hybrid, multi-cloud models by the end of the year 2022. The rise in these models is due to the increase in unstructured data. To provide more value to the customers, an organization can no longer use traditional batch-based reporting. Companies must build their infrastructure to overcome the unstructured data challenge while ensuring compliance and security regulations.
4. The great convergence of technologies and services
In 2022, we will see an overlap of technologies implemented in real-time scenarios. These overlaps will include Artificial intelligence, Business intelligence, and Machine learning use cases. Experts predict the convergence of data warehouses and data lakes that will be highly beneficial. It will simplify technologies and vendor landscape.
The organization often collects data from multiple tools and platforms. So, a robust metadata strategy will be required to regulate data processes for higher customer value. Whether no-code/low-code or highly sophisticated structures platforms, a solution that empowers companies to organize data and create a robust architecture will be of high importance in the year 2022.
5. Increased democratisation
After the pandemic, there will be an increase in no-code digital solutions. The rise of no-code/low code will drive greater agility with automation. The organization will move from code-centric-workflows to self-service analytics that allows a non-technical person to become a key player in the ecosystem. These democratized data workflows will ease access to data and make smarter business decisions. Unstructured data will increase manyfold in the coming years. So, ubiquitous architecture will be of great importance. The architecture that enables access to complicated datasets and uses them across various tools and platforms will be in high demand.
Convergence of platforms and services, introduction and adoption of hybrid, multi-cloud, implementation of DataOps with the improved infrastructure of 5G, and increased democratisation are some of the revolutionary changes in data engineering that are expected in the year 2022. Share your thoughts with us at firstname.lastname@example.org on how these innovations will help you.