Over the past two years, companies that were on the fence about data transformation were forced to make some hard decisions. Now that we're finally emerging on the other side of the pandemic, it's time to take what we learned, assess where we are now, and complete the data transformation process before the next unexpected event makes those decisions for us.
According to the current trajectory, we'll generate more than 180 zettabytes of data by 2025. Add that number to security concerns and constantly evolving regulations regarding data collection, storage, and use, and you can see why finding a viable data transformation solution should be your number one priority.
What is Data Transformation?
The fact that we exist in the information age is only one of the challenges facing businesses and government agencies of all shapes, sizes, and industries. In this environment, data may be the single most valuable asset you possess outside of your human resources.
Depending on your objectives, data transformation can happen in the middle of an extract-transfer-load (ETL) process model or to transform raw data at the end of an ELT configuration. The former works for businesses that use an on-premises data storage warehouse, while the latter is best handled with a scalable, fully cloud-based platform.
Data transformation offers solutions that help organize, evaluate, and use data in all of its forms. Done right, it supports shifting business requirements, modifies business processes, and improves the customer experience. This is possible by utilizing the cloud computing option that best suits your current situation and anticipates future requirements. In fact, I would argue that modernization is only possible through cloud computing.
Exploring Your Cloud Computing Options
By now, it's common knowledge that sensitive and high-risk data is best protected by private, on-premises data storage. Less critical data or information that changes often is safe in the virtual world. However, many organizations use some combination of both types of data storage.
In addition to the basic public, private, and hybrid cloud configurations, a number of services are increasingly available as on-demand, cloud-based platforms.
• Software-as-a-Service (SaaS): Obtaining software as a service is probably the most common and familiar cloud-based solution. It's cost-effective, highly scalable, and accessible. Examples include CRMs, inventory management, and marketing automation tools.
• Virtual Desktops (VDI)/Desktop-as-a-Service (DaaS): Business leaders who were wary and slow to realize the benefits of remote desktops are now embracing this option out of necessity. They not only support an increasingly mobile workforce, but they also allow IT specialists to standardize security and control access across a range of devices and platforms.
• Platform-as-a-Service (PaaS): As data multiplies, so does the need for secure, reliable storage and computing resources. Enter PaaS in the form of servers, operating systems, data storage, and other computing resources.
• Infrastructure-as-a-Service (IaaS): You can further pare down on-site storage needs and overhead expenses by contracting IaaS and accessing hardware, software, networking infrastructure, and data centers from the cloud.
• Disaster Recovery-as-a-Service (DRaaS:) Downtime costs money, and it's a sure way to lose customers and credibility. By contracting disaster recovery as a service, you'll already have a backup plan in place and ready to go when you need it without building one from scratch.
• Backup-as-a-Service (BaaS): Anyone who has lost a device knows the value of this option. It's now standard practice to follow the 3-2-1 rule of having at least three copies of data, two on separate devices or media and one that's automatically backed up and stored on the cloud.
• Software-Defined Wide Area Networking (SD-WAN): What's the point of having more cloud solutions and applications if it throttles your network and data gets caught in a bottleneck? Scalable SD-WAN networking services solve that problem.
Best Use Cases for Cloud-Based Data Transformation
The case for data transformation couldn't be stronger, especially in data-driven environments like those of healthcare, banking and investments, retail, and the public sector. Zach Stein, co-founder of the climate-focused investment services startup Carbon Collective, knew the company would have to emphasize digital transformation to compete in a crowded sector. “Planning for data transformation can’t be an afterthought. It’s now one of the most important business considerations. Unless we have our data under solid control and communicate that to customers, we don’t really have a business.”
After solidifying your objectives, your data transformation could include any or all of the following.
Modernizing On-Site Legacy Applications
It's unnecessary to purchase new applications when they can be easily updated through data transformation. However, this option should only be exercised when rebuilding is a more viable and cost-effective solution to total replacement.
Proceed with modernizing when:
- There's no comparable solution available in the market
- The application is a core component of your organization
- The current application is part of compliance or security protocols
Migrating Non-Critical Business Data
Whether you're transferring applications to the cloud or just adjusting to expanding storage requirements, restructuring through cloud-based data migration offers greater agility, efficiency, and a centralized location to access non-critical data and applications.
Securing Sensitive or Critical Information
One of the biggest risks with data migration is security. Aided by automation, organizations can safely transfer petabytes of data to secure private cloud storage faster and with little risk of data leaks, breaches, or unnecessary downtime.
Transforming IT Operations
You don't need to be a large enterprise with a stand-alone IT department to be concerned about transforming IT operations like system troubleshooting and remediation. In fact, automating IT operations allows smaller companies to reduce risk and remain competitive while freeing IT mangers in larger organizations to focus on more high-value projects.
By transforming IT operations at the same time as you perform other data transformations, you reduce the complexity of your digital operations while leveraging the full value of cloud computing.
In the race between technology and socio-economic evolution, time is not always on our side. The time to make those decisions and explore new platforms and ways of doing business is now.
Companies from all industries are learning the advantages of adopting new business models and technologies that save time and money while supporting high levels of customer care. Whether you opt for a hybrid model or transition fully to the virtual world, cloud computing in at least one of its various forms will take you where you need to be.