5 Benefits of Moving your Data Analytics Loads to the Cloud
Here is how this alternative can help your business optimize processes.
With the increasingly faster flow of input data, companies across all industries and sizes need to make more effective decisions. Besides, decisions are no longer made on an intuitive basis as they used to be. Today, they are data-based.
That’s in this context that the Big Data and Data Analytics arise. Growing trends in the corporate world, these disruptive systems, which eliminate the need for a proprietary infrastructure to manage information by moving them into a cloud, are already a reality.
According to a survey conducted by Gartner, approximately 75 percent of the biggest global organizations will have at least one pilot project of Artificial Intelligence- or Machine Learning-based Data Analytics by 2023. Accordingly, they will transform the huge data volume made available over the course of the planning, production, sale, and loyalty stages into actual assets with potential to generate new businesses.
The survey also shows that, by 2024, some 35 percent of the world’s major global companies will adopt Decision Intelligence solutions, leveraging advanced data analytics resources to help streamline and improve decision making in their operations.
Cloud computing is the unification of computing services, which include servers, databases, software and intelligence analysis, making the management of a huge volume of data scalable. The service enables organizations to reduce operating costs, manage their entire internal IT logistics more efficiently and adjust demands according to their needs.
5 benefits of moving your data analytics loads to the cloud
Every company has data integration processes and data analytics loads. With the proliferation of cloud solutions, mainly public clouds such as Azure and AWS, new ways to create, manage and optimize these processes have arisen, built on improved tools with higher storage capacities and reduced costs.
Check the top 5 benefits of moving your data analytics loads to the cloud:
1.Scalability with cost-effective services
With an elastic scalability, cloud computing enables the Big Data and Data Analytics processes to access the resources they need to work efficiently. The cloud scale flexibility can be used to increase computing and processing capacity only when necessary, translating into reduced costs.
2.Possibility of multiple connections
Leading public clouds allow both hybrid and multi-cloud architecture patterns, meaning they can connect with local networks and other clouds. Therefore, organizations can load data into the server that better meets their needs. This approach often eliminates the requirement of creating an infrastructure migration project.
3.Governance and monitoring facilitated with orchestration tools
Many free and paid cloud providers offer a broad set of policies, technologies and controls that facilitate governance and monitoring processes, strengthening data security policies and helping protect data, apps and infrastructures from potential threats.
4.Use of new connectors for several types of systems, often with no need of investing or developing components
The cloud technology, also considered an on-demand service, creates an environment in which it is possible to test, deliver, manage and develop software applications, eliminating the need to configure or manage a parallel infrastructure of storage servers, networks and databases.
5.Quick deployment of AI without requiring machine learning expertise
With cloud services, it’s possible to connect all data hosted on the cloud and use pre-built AI products, such as Azure Cognitive Services. In this environment, the AI learns from historical data, identifies patterns, and makes recommendations, providing the necessary subsidies for assertive decision making. All this working as a service, that is, without requiring machine learning expertise.
These are only some of the many benefits of using Cloud Computing for your Data Analytics loads. There are several other advantages linked to the practices mentioned above. Visit our website to learn more about our cloud-based Big Data solutions.