Tag: Security And Compliance

The growing importance of agility and operational efficiency has helped introduce serverless solutions as a revolutionary concept in today’s data processing field. This is not just a revolution, but an evolution that is changing the whole face of infrastructure development and its scale and cost factors on an organizational level. Overall, For companies that are trying to deal with the issues of big data, the serverless model represents an enhanced approach in terms of the modern requirements to the speed, flexibility, and leveraging of the latest trends.

Understanding Serverless Architecture

Working with serverless architecture, we can state that servers are not completely excluded in this case; instead, they are managed outside the developers’ and users’ scope. This architecture enables developers to be detached from the infrastructure requirements in order to write code. Cloud suppliers such as AWS, Azure, and Google Cloud perform the server allocation, sizing, and management.

The serverless model utilizes an operational model where the resources are paid for on consumption, thereby making it efficient in terms of resource usage where resources are dynamically provisioned and dynamically de-provisioned depending on the usage at any given time to ensure that the company pays only what they have consumed. This on-demand nature is particularly useful for data processing tasks, which may have highly varying resource demands.

Why serverless for data processing?

Cost Efficiency Through On-Demand Resources

Old school data processing systems commonly involve the provision of systems and networks before the processing occurs, thus creating a tendency to be underutilized and being resource intensive. Meanwhile, server-less compute architectures provision resources in response to demand, while IaaS can lock the organization in terms of the cost of idle resources. This flexibility is especially useful for organizations that have prevaricating data processing requirements.

In serverless environments, cost is proportional to use; this means that the costs will be less since one will only be charged for what they use, and this will benefit organizations that require a lot of resources some times and very few at other times or newly start-ups. This is a more pleasant concept than servers that are always on, with costs even when there is no processing that has to be done.

To Know More, Read Full Article @ https://ai-techpark.com/serverless-architectures-for-cost-effective-scalable-data-processing/

Related Articles -

Robotics Is Changing the Roles of C-suites

Top Five Quantum Computing Certification

Trending Category - Patient Engagement/Monitoring

In the context of the increasing prominence of decisions based on big data, companies are perpetually looking for the best approaches to effectively utilize their data resources truly. Introduce the idea of Unified Data Fabric (UDF), a new and exciting proposition that provides a unified view of data and the surrounding ecosystem. In this blog, we will uncover what UDF is, its advantages and thinking why it is set out to transform the way companies work with data.

What is Unified Data Fabric?

A Unified Data Fabric or Datalayer can be described as a highest form of data topology where different types of data are consolidated. It is an abstract view of the data accessible across all environment – on-premises, in the Cloud, on the Edge. Therefore, organizations are able to better leverage data and not micromanage the issues of integration and compatibility by abstracting over the underlying complexity through UDF.

The Need for UDF in Modern Enterprises

Today, elite business organizations are more involved in managing massive data from multiple fronts ranging from social media platforms to IoT, transactions, and others. Recent data management architectures have had difficulties in capturing and managing such data in terms of volume, variety, and velocity. Here’s where UDF steps in:

Seamless Integration: UDF complements the original set up by removing the barriers that create organizational and structural data separation.

Scalability: This makes it easy for UDF to expand with data as organizations carry out their activities without performance hitches.

Agility: It also enables an organization reposition itself rapidly when it comes to the data environment of an organization, hence it becomes easier to integrate new data sources or other analytical tools.

Unified Data Fabric for Seamless Data Access and Management

In the context of algorithmization of management and analytics-based decision making, more often than not, companies and enterprises are in a constant search for ways to maximize the value of their data. Introduce the idea of a Unified Data Fabric (UDF) – a relatively new idea that could help in achieving consistent and integrated data processing across various platforms. Let’s dive a bit deeper on understanding what is UDF, what it can bring to businesses, and why it will redefine data processing.

UDF is likely to be more significant as organizations proceed with the integration of advanced technology. The usefulness of being able to present and manipulate data as easily as possible will be a major force behind getting data back into dynamic uses whereby businesses can adapt to change and remain competitive in the market.

To Know More, Read Full Article @ https://ai-techpark.com/unified-data-fabric-for-data-access-and-management/

Related Articles -

AI in Drug Discovery and Material Science

Top Five Best AI Coding Assistant Tools

Trending Category - Mental Health Diagnostics/ Meditation Apps