Of late, digital transformation initiatives have increased across industries. And, you can expect the trend to gain momentum further.
According to IDC, companies will allocate more than 50 per cent of their IT spending to digital transformation initiatives by 2024. Moreover, the digital transformation investment market is likely to reach USD 6.8 trillion by 2023.
Now, let us unfold the trends that drive the digital transformation trends, dictating the need for a smart data catalog tool. Here are the trends:
Data Literacy
Many enterprises are considering data cataloging as a core part of their digital transformation strategy. We get to see that data cataloging has found uses in every single strategic use case. For example, uses such as democratizing data, enabling self-service analytics and AI to enable enterprise-wide data governance and compliance initiatives, and accelerating the migration to a multi-cloud environment.
Given the widespread usage, the trend is likely to continue at a faster speed in 2021. With such trends in place, the need for becoming data-literate has become more than ever before. It is also necessary for businesses to operate well in a challenging data environment and support a remote workforce.
But there is a prerequisite for becoming data literate. First, you need to have complete visibility of your data. You should know what data you have, where it stays, who owns it and governance constraints. And that means you need to have a detailed understanding of your data from various angles.
In this context, Garter says that by 2023, businesses promoting data sharing will outperform their peers on most business value metrics.
Data Science and AI to Go Hand-in-Hand
Given the prevailing trends, it is worth believing that data science and AI adoption will gain significant steam from now on. Furthermore, it has been learnt that at least 76 per cent of businesses prioritized the implementation of AI and machine learning in their 2021 IT budgets.
The usage of machine learning is increasingly becoming widespread as many businesses have adopted machine-learning algorithms or robotic process automation (RPA) to actuate some levels of automation.
With increased automation across different business processes, enterprises will leverage the most value from their AI and data science investments. Also, businesses will be able to extend data science and AI to a broader user community within their organizations in contrast to the traditional practice of confining them to a small pool of data scientists.
The constantly growing customer base also triggers the need for empowering data science teams with rapid data discovery and data collaboration. Many users are leveraging the benefits of the catalogue to operationalize analytics and AI initiatives.
The transition from One Cloud to Multi-Cloud
The trend of cloud adoption is becoming popular among businesses as a strategic initiative aimed at achieving cost reduction, drive innovation and greater efficiency.
In this context, IDC says that by the end of 2021, 80 per cent of businesses will migrate to the cloud. And things will not end there. IDC further says that 93 per cent of businesses will implement a multi-cloud strategy to reduce single vendor dependency, vendor lock-in and mitigate long-term risks.
When businesses implement a multi-cloud strategy, they reap a slew of benefits, despite increasing complexity levels.
It will entail navigating and managing multiple data sources across clouds and in-house environments. And at the same time, there also arises the potential risk of creating a new set of data and technology silos.
It is where the role of a smart data catalog comes into play. A data catalog will help enterprises to reduce the complexities.
For example, a smart data catalog allows users to discover the data with them regardless of the source quickly.
The catalogue also bears end-to-end data lineage and impact analysis capabilities that enable businesses to get in-depth information about the transformations their data underwent throughout the lifecycle, during the traversal from the source to target across in-house and multi-cloud environments.
There is more on the offer. A smart data catalog allows enterprises to maintain a holistic view of their data. It eases businesses from the hassles of maintaining, reconciling and toggling across multiple data catalogs specific to the cloud.
Advanced-Data Lineage Is the New Trend
Data lineage has a key role to play, especially while driving successful data-driven business transformations, like enterprise data governance and compliance, data warehouse modernization, and self-service analytics and AI.
But there is a crucial point to note. All data lineage tools are not equal in capabilities. Given the growing complexities, businesses are likely to adopt advanced data lineage capabilities to extract deep data lineage with detailed information at a granular level from a host of data sources to build a comprehensive data catalog.
Bear in mind that the need for data lineage extraction that is both deep and broad will only make the data landscape more complex.
Also, things get more complicated in some regulated industries, where users need a proper understanding of their data to support data science and AI initiatives while meeting the existing compliance regulations.
MLOps Takes Off
MLOps is a set of best practices that are drawn from inspirations of DevOps. MLOps plays a critical role in promoting greater collaboration and communication among data scientists and other professionals to manage the development and production of machine learning pipelines throughout the lifecycle.
You can expect that MLOps will positively impact operationalizing AI that will gain more prominence in the coming days.
You can also expect that smart catalogues will play a crucial role in MLOps teams to find, validate and collaborate on data.
Conclusion
You now know that a smart data catalog tool plays an important role in digital transformation initiatives. If your business is undergoing digital transformation, ensure that you invest in the tool.
