Cloud Migration or Cloud Adoption? Which is Better for Business Transformation?

In this modern age of digital revolution, data has become equally important as oil once was. Data plays a crucial role in facilitating and optimizing the day to day business operations of an organization. As this data is sensitive information; it has to be protected and ensured that it doesn’t fall into the wrong hands. Also, as this data grows exponentially, the space required to store the data is so consuming.
This data cannot be stored in your organization’s network anymore. This data can get misplaced, manipulated and be tampered with if it’s kept locally. There could be several other consequences eventually leading to losing clients.

Should the companies switch to Cloud Strategies?

Cloud has become the most sought-after solution for the optimization requirements such as availability, accessibility, infrastructure, performance, etc.
But does this approach indeed turn out to be the ideal solution? Are the companies going for the cloud strategy without even fully understanding the suitability of it?
The answers to these questions and many others like it lie in the requirements of a company and how cloud strategy will help a company to improve its bottom line.

What is Cloud Adoption?

According to HCL Technologies, The strategic move by organizations of reducing costs, mitigating risks and achieving the scalability of database capabilities is known as the process of Cloud Adoption.
The Enterprise-Ready cloud service availability depends upon the size of adoption.

Comments

Post a Comment

Popular posts from this blog

Device Mesh – The new disrupter in the Digital World

Gartner’s Top most Tech disrupter, the Device mesh is a network of connected devices. What is Device Mesh? Device mesh is just a network of devices that aid communication between various entities such as humans, businesses and machines providing a more innovative cohesive user experience. It includes numerous mobile devices, electronic machines, wearable and a wide range of sensors connected through IoT. https://www.wisdomplexus.com/blogs/device-mesh-new-disrupter-digital-world/ Difference between Device Mesh and Traditional network:- In the traditional wireless network there used to be a single router which would transmit signal and all other devices were connected to it, with increasing distance the signal would go on attenuating till a point that it would be impossible for a device to stay connected to the network. Whereas in Mesh network being like a woven fabric every device connected acts as a transmitting node and passes the signal to the next device resulting in i...
Read more

Artificial Intelligence Predictions for Every Business to know in 2019

Image
Artificial Intelligence abbreviated as AI is the self-performance of machines and computers without any human interference which means it is the ability of machine’s intelligence to manage tasks on their own. What is the Future of Artificial Intelligence ? It is presently blooming in all areas of the global market, be it medicines, education or technology machines are replacing human workforce everywhere. But still, it is said to be in the infant stage as some states it will replace humans completely in coming years while others are yet not fully aware of the concept. The answer to this still lies between these two predictions. There are assumptions for Artificial Intelligence that You Must Know to Make 2019 big for Your Business. Let us have a look into how will the year be for Artificial Intelligence: Many Businesses use chatbots for faster services, replacing human resources, but 2019 will introduce “ Virtual Agents ” a real big thing for machine learning as now custo...
Read more

Harnessing Tensor Processing Units: Transforming the Landscape of Machine Learning

Image
  Tensor Processing Units (TPUs) are specialized hardware accelerators designed by Google to enhance the performance of machine learning tasks. Unlike traditional processors, TPUs are application-specific integrated circuits (ASICs) optimized for tensor operations, which are fundamental to deep learning algorithms. This unique architecture allows TPUs to excel in processing large volumes of data and executing complex neural networks efficiently. What Makes TPUs Unique? TPUs were developed to meet the growing computational demands of machine learning, particularly for tasks involving matrix multiplications and other tensor operations. Their design is tailored specifically for these mathematical operations, allowing them to outperform general-purpose CPUs and even GPUs in certain AI workloads. While GPUs were initially created for graphics processing and later adapted for AI, TPUs are built from the ground up for machine learning tasks, making them more efficient in this domain. ...
Read more