Continuous technological developments and the emergence of the cloud have made digital transformation inevitable. But becoming a cloud-first organization isn’t just about embracing a bunch of modern tools or moving data to the cloud. It requires organizations to thoroughly understand the many nuances of operating in a cloud environment and building solutions that leverage the benefits of cloud technologies to the maximum extent possible. Read on to learn how you can navigate the cloud with data engineering.
Operating in a Cloud-Based Environment Comes with Its Own Set of Challenges
The many benefits of the cloud make migration a pressing priority for most businesses today. Yet, when it comes to successfully operating in a cloud-based environment, not everything is a cakewalk. There are many challenges that businesses need to contend with as they transition to the cloud:
Handling the Overload of Data
Cloud-based systems produce so much data that businesses often do not know how to handle it. Identifying important data while discarding irrelevant data is critical for business decision-making. Organizations must also take steps to maintain data quality and ensure compliance with necessary data protection and privacy guidelines.
Managing and Supporting Cloud Apps
As organizations move their data and apps to the cloud, they need to constantly manage and support them 24/7 — right from planning and architecting cloud-based systems to migrating, implementing, and monitoring them.
Enabling Seamless Scalability
While scalability is an inherent feature offered by most cloud systems, organizations must also put efforts into researching and implementing new services to scale their apps and maintain service levels.
Monitoring Cloud Performance
Another critical responsibility that cloud technology brings is the need to monitor performance around the clock. Tracking the functionality and operations of apps for potential bottlenecks and resolving performance issues in time is vital.
Formulating a Robust Recovery Plan
Operating in the cloud is beneficial in many ways. But it also demands a well-thought-of and well-planned recovery strategy. Formulating a robust recovery plan and successfully executing it in the event of a failure or outage is crucial to protect data.
Keeping Costs Under Control
Embracing the cloud and all its capabilities is great until cloud bills begin surging. As cloud provisioning becomes increasingly easy, organizations need to invest in data lake storage solutions to store their data at scale. They also need to keep a tab on cloud growth to reduce ongoing cloud expenditure while meeting key SLAs.
Overcoming Cloud Challenges with Data Engineering
In today’s cloud-obsessed and data-driven era, data engineering has become an essential part of successful business operations. The effective design, testing, and monitoring of data in the cloud allow data scientists, analysts, and other users to access and analyze data for various business needs.
Build and Manage Robust Cloud Data Infrastructure
Using modern data engineering tools and services, organizations can build and manage a robust cloud data infrastructure that can handle large volumes of data. By collecting, processing, and storing data in an efficient and standardized manner, they can maintain the right level of data quality and enable easy access for business decision-making.
Extract, Transform, and Load Information Correctly
Data engineering enables organizations to extract data from various sources, transform it, and load it into the right data warehouse. This helps ensure that business data is accurate, consistent, and error-free. It also aids in automating the process of collecting, cleansing, and integrating data, ensuring cloud users only rely on accurate and updated data.
Process and Analyze Data in Real-Time
Embracing data engineering in a cloud-based environment is also a great way to process and analyze data in real-time. Since cloud apps generate data at a lightning-fast pace, data engineering allows organizations to collect, process, and analyze large volumes of data – as and when they get generated.
Run and Scale Big Data Workloads
As cloud technologies lead to big data workloads, data engineering allows organizations to run large-scale data processing. Using statistical algorithms and predictive models, they can conduct intelligent what-if analyses and uncover hidden patterns and correlations in their data streams. They can also build and scale data pipelines and enable large-scale model training, analysis, and reporting.
Achieve Data Governance Goals
Data engineering plays a critical role in achieving data governance goals. It enables organizations to build the right policies and practices around data quality and usability. It ensures the right data is available at the right time to the right users for effective decision-making. It also helps in implementing the right encryption and access control measures and maintaining the required levels of transparency and lineage.
Realizing Cloud’s Potential with Data Engineering
If you want to make the most of the flexibility, scalability, and cost benefits of the cloud, you must embrace data engineering best practices. With the right data engineering tools and approach, you scale your cloud environment up or down based on your business needs. You can also add and remove resources as needed – without worrying about breaking or impacting the underlying infrastructure. You can also choose from a wide range of data storage and processing capabilities and make the most of robust security features across encryption, access control, and compliance certifications.
Need help in navigating the many challenges of the cloud and ensuring a smooth transition? We can help! Our qualified pool of data engineers can help you establish a strong cloud foundation and empower you to take the right data engineering steps. Accelerate cloud adoption today with Wissen and stay on top of the latest innovations.
