Businesses need a strong Data Strategy to manage vast amounts of data, drive innovation, develop a data culture, and to maintain a competitive advantage. Though cloud environments offer fast, high-volume data collection and scalable storage space; machine learning-powered data preparation; AI-enabled analytics; data backup and recovery facilities — leaving the developers free to pursue coding.
Although cloud security is still a common concern, the advantages far outweigh the security-related headaches. Thus, it is easy to fathom why Data Strategy and a cloud environment will complement each other.
The following events have transformed businesses in recent years and are pushing for such an intersection
- Business automation is leading toward a smart-machine-driven world of business. “Smart-machine-driven” and “data-driven” are interrelated concepts as intelligent machines are propelled by data
- Data has taken the place of information currency, giving rise to enterprise preoccupation with core data practices like data replication, data storage, and data transfer technologies
- More and more businesses are moving to the cloud to avoid having large on-premise data centers, while helping other technologies like serverless or edge to gain prominence
- In next-gen businesses, a core differentiator will be real-time data processing.
Predictions About to Become a Reality
Of the 10 top technologies that Gartner has recommended for speedy digitization of infrastructure and operations (I&O), serverless again signals the growing importance of cloud environments for global businesses of all shapes and sizes.
Gartner also states that businesses operations can no longer survive alone; they must align with overall business strategy to deliver competitive products and services. Gartner’s David Cearley, Vice President and Gartner Fellow, said, “The continuing digital business evolution exploits new digital models to align more closely the physical and digital worlds for employees, partners, and customers.
The “intelligent digital mesh” is now being described as the future business model. Technology and Data Science will pervade every layer of this new model, thus making Data Strategy one of the core drivers of business processes. With the ever-increasing popularity of infrastructure technologies like cloud, serverless, and edge — in near future cloud and associated data-processing environments will embrace Data Strategy as a happy partner.
A Forbes post highlights LogicMonitor’s Cloud Vision 2020: The Future of the Cloud, which stands apart from other studies in the sense that it does not just offer industry statistics but provides a review of the present and future of cloud computing.
It is believed that serverless will reach its adoption maturity in 2019, as it is considered a game-changer in the cloud community. Serverless strengthens cloud computing with security and governance capabilities.
Talend Cloud, Google, Amazon, and Microsoft have all joined the race for launching serverless capabilities. What makes serverless so powerful is its ability to do without dedicated hardware management, and provide support to all types of data professionals — data scientists, data engineers, data stewards, data analysts, and other business users. Serverless will also promote the growth of different types of cloud-based services like FaaS, BaaS, and IaaS to provide relief to on-premise IT teams.
The above events have forced business operators to rethink their business strategies as they cannot survive without data or cloud. An Infoworld article explains how Data Strategy has to be redesigned for cloud-native transformations to accommodate data replication in secondary stores, typically after long breaks.
What are the Advantages of Serverless Computing?
In a data-powered business environment, data storage space, data-processing speed, and advanced analytics capabilities are all key contributors to success. The serverless computing model offers all that by enriching the cloud with Data Governance and security tools. Cloud is inherently suitable for vast storage needs, high-speed data processing, and advanced analytics through packaged services. Data processing on the cloud includes the following benefits:
- Helps businesses to eliminate costly and manpower-heavy data centers.
- Cloud service providers assume all Data Management headaches.
- Frees up developers and IT personnel to concentrate on other important IT work.
- Provides access to excellent Function as a Service (FaaS) and Infrastructure as Service (IaaS) services
Big Data Strategy for the Serverless
Moving Big Data to the cloud sparks new thinking on Data Governance on the cloud, which has traditionally been viewed as less secure than on-premise data storage facilities. Moreover, high-speed data transfers always include a possibility of data leaks or data loss.
All these concerns indicate that an enterprise Data Strategy may have to be mapped with the cloud service provider’s Data Strategy to ensure that the business and the service provider agree on governance terms
Implementing a Cloud Data Strategy quotes Anthony Algmin, Principal at Algmin Data Leadership as saying, “Thinking of a Data Strategy as something independent of Business Strategy is a recipe for disaster.”
The ongoing concerns surrounding the cloud’s ability to handle high-volume data, potential security leaks, data storage and replication policies, and loss of data from hosts can be addressed by a Data Strategy team. Most Big Data projects are involved with IoT data pipelines, which typically call for real-time processing. Real-time Data Processing with Serverless Computing introduces the concept of real-time data processing on serverless with examples like Mapbox and Netflix.
As serverless offers full scalability, agile application development, and reduced time to market, it is a tempting proposition for most businesses struggling to beat their competition in the marketplace. The icing on the cake is the absence of infrastructure management, which is handled by the cloud service provider.
However the challenges are on the data side, where data architectures must be redesigned to match the scale of a project. You may get a glimpse of the Big Data serverless environment on a blog post, but the point of using serverless for Big Data projects is enabling the developers to concentrate on coding without worrying about infrastructure management and deployment.
Cloud Is the Future
Right from the C-suite executives to the highly technical IT personnel, everyone in business thinks that cloud is the future. IDC has indicated that currently 50 percent of business IT expenditure is on cloud-based technologies. The sudden rise of the Internet of Things (IoT) gave a boost to cloud computing, and the rest is history. The future also belongs to AI and associated automation technologies best suited for cloud.
AI, ML, and many other advanced technologies work in tandem with Data Science. As businesses invest heavily on fully- or semi-automated solutions, then data, Data Strategy, and technologies like serverless will create the backbone of technology infrastructure in a machine-driven world.
Data Governance and Serverless Computing hints that in a cloud-first business world, the technology vendors will have no choice but to include Data Governance tools or solutions in their product offerings. Such products will have to focus on data-integration policies, data access controls, data monitoring, and data lifecycles.
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