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We are at the height of the digital age, where many companies are opting to transform their businesses and direct them towards a more technological approach, storing their information with the help of cloud services. 

Organizations today are looking to leverage the cloud as a strategic environment to manage data, scale operations and gain actionable insights through descriptive analytics. 

In the following PREDIQT article, we will tell you about the benefits of adopting cloud services for data management and analytics and what best practices you can apply in your company to maximize the value of your data.

What are cloud services?

Cloud services are technological platforms that allow access to computing resources through the Internet: storage, processing, databases, artificial intelligence, among others.

Instead of investing a large budget in maintaining their own physical servers, organizations choose to store their information in the cloud, where they can scale their digital resources on demand, i.e., they only pay for what they use.

Key benefits for your company's data

Adopting cloud services offers multiple advantages for organizations working with large volumes of information and needing to to make reliable data-driven decisions:

Cost reduction 

Cloud storage allows companies to have greater budgetary control and improve efficiency by eliminating the cost of maintaining their own physical servers and infrastructure.

Scalability

Companies can expand or reduce their data storage and processing capacity flexibly and immediately. 

Access to state-of-the-art technology

Leading cloud platforms offer advanced analytics tools, artificial intelligence, machine learningmachine learning, dashboards and predictive models, all of which are very intuitive to use, help to automate data analysis processes and allow extracting value from data in real time.

In addition, the cloud will have your data well protected, since these platforms perform continuous and automatic backups, allowing you to recover your data in case of disasters and always have your information available.

Fully remote access

Teams from different areas of a company can work with the same data, facilitating collaboration on projects and the achievement of objectives.

Best practices for implementing cloud services

• Plan a clear strategy: Have a clear data strategy will help strategy will help reduce the risk of errors. Before you start moving your information to the cloud, identify what type of information you will migrate, the priority of this data and how it will be protected. 
• Security should be your priority: Make sure your service provider meets high security standards for data protection: Data encryption, access controls and constant monitoring are some examples.
• Integrate analytics tools: The real advantage of the cloud lies in its ability to analyze data in real time. Use BI (Business Intelligence) tools, machine learning and analytics engines to transform your data into informed decisions.
• Train your collaborators: Not only your IT team must be well trained with the help of technology courses to use digital tools, but also your operations and business teams, so they can take full advantage of all the features and make better informed decisions.
• Perform ongoing assessments: Cloud environments are constantly being updated, so it is important to perform periodic reviews of your architecture, costs and performance.

Conclusions

Cloud services are a critical enabler for organizations that want to transform their data into real value. By integrating the cloud with advanced analytics tools, organizations can respond faster to change, optimize their operations and uncover new business opportunities.

At PREDIQTwe combine more than 20 years of experience in advanced analytics with cloud solutions to help you transform your data into strategic decisions that drive business growth. Let's talk about how to optimize your cloud infrastructure and make the most of your analytical potential.

FAQ on Cloud Services: Benefits and best practices for data usage and analytics.