Breaking Down the Cloud Data Journey: From Initial Set-Up to Advanced Analytics

Did you know that organizations are 17x more likely to increase cloud spend than reduce it over the next 12 months? After all, the days of cloud computing being viewed simply as a style of technology are quickly drawing to a close. Instead, it is becoming more and more essential to enabling business innovation. In other words, “there is no business strategy without a cloud strategy,” according to Gartner.

It’s easy to see why. A few key strategic benefits of cloud data platforms include:

• allocating resources on the fly
• increasing strategic focus by replacing database management with cloud-native managed services
• increasing cost control with manageable pay-as-you-go opportunities
• facilitating agile delivery, DevOps, and flexible microservices
• accessing a rich ecosystem of data analysis, machine learning, AI tools, and APIs
• improving and securing employee access to data remotely

What does this mean for future-oriented businesses? Every enterprise needs to assess its level of cloud readiness and then formulate its cloud strategy to help ensure it’s successful. To that end, Maven Wave recently conducted a webinar series on the cloud data journey to help organizations ready their approach. Here’s the rundown on what we discussed:

Getting Started

Identify the Best Approach

No two cloud journeys are identical. However, most approaches can be placed into one of two categories: tactical or strategic.

Tactical approaches are usually driven by a specific timeline, whether that be an upcoming lease expiration or an impending regulatory change. As a result, workload portability is the main goal of a tactical approach, and organizations using this approach can expect reduced costs, speedy migration, and employee skill carry-over.

Alternatively, optimization drives the strategic approach. This includes re-factoring architecture, obtaining the latest and greatest tools, reducing maintenance and overhead, and creating a flexible cloud-based environment.

Determine the Organization Method and Ownership

From there, you’ll need to figure out how you want to organize the data. Typically, your choices can be broken down into three options:

• Data warehouse – a warehouse team curates data for you
• Data lake –  lake team owns the data, but provides open access to the business team with security permissions
• Data mesh – owned and accessed by the business team

Pinpoint Your Data Processing Approach

Once you’ve figured out how you want to organize the data, your next step is deciding how to process it. your options include:

• Batch (i.e., time-based triggers)
• Stream (i.e., always on)
• Event (i.e., on-demand)

Decide On Your Tooling Method

Finally, you’ll want to figure out your tooling method. The three types are:

• Cloud-native (tightly integrated, minimal set up)
• Open-source (cloud-agnostic, pay only for support)
• Third party (niche focus, robust toolset)

Prepare Your Company Culture

Finally, organizations must understand that cloud adoption requires both technical and cultural transformation. For that reason, there are four areas leadership must focus on to ensure your business is prepared for this transformation:

• Organizational readiness
• Sponsorship and engagement
• Training and incentives
• Communication and marketing

It is impossible to overstate the importance of this step in the process. Without preparation and buy-in from every key employee at every level, the success of your cloud migration journey is in jeopardy. So, ensure your team — and company culture — is prepared for the road ahead. Learn more by streaming our webinar recording on how to get started with data in the cloud.

Controlling Cost

During your cloud data journey, you’re bound to encounter high costs. When that happens, you’ll need to identify the cause — especially if the costs point to a potential security incident. So, to drill into those details, you’ll need to approach your assessment in four phases.

Operations and Alerts

When you encounter a high cost, you’ll want to be aware of it as soon as possible, which means you’ll need real-time reporting. Additionally, you’ll also want these alerts on your cloud infrastructure so you know what’s happening (and why) the moment an incident occurs.

Cost Management

In addition to operations and alerts, you’ll also need to keep an eye on any cost utilization trends. This will help you plan for any additional expenses in the future and know where to allocate your financial resources.

Audit

Next, focus on detailed information to drill into issues or concerns. Your audit should answer questions around:

• Who created what and when
• Who accessed what and when
• What service accounts have access to what permissions
• Who governs the data

Utilization and Adoption

Finally, you’ll want to assess your utilization and adoption. The goal of building most data platforms is for them to be used by someone other than an extract, transform, load (ETL) grunt, so this part of the process tells you who is using what technology and how often. Once you have the aforementioned data, you can use it to pinpoint the cause of the cost and formulate a potential plan to address future costs. Learn more about cost control for data programs by streaming our webinar recording.

Building Advanced Analytics Programs

Finally, once you’ve built your platform and understand how to troubleshoot it, it’s time to move to the big leagues and take your data analytics beyond business. You can apply analytics to your data operations, data engineering, and data platforms. However, doing so takes time, focus, and commitment.

At Maven Wave, our goal is to apply data analytics in an individualized way that meets each client’s unique needs. To do that, you must first identify your own data needs. Start by asking yourself questions like:

• What is your organization’s data culture? (i.e., do you view data as a racehorse or plow horse?)
• Who are the participants and key stakeholders?
• What are the key objectives driving your journey?
• What are your business drivers and quick wins?

Data Organization and Ownership

Historically, data was owned by a single team. (Think back to the examples of the data warehouse, data lake, and data mesh above.) However, a modernized data approach enables organizations to pick and choose which tools they want in their data toolbox — as opposed to the restricted toolset associated with historic cloud data organizations. That said, for this “Bring Your Own” model to work, you must support and enable your analysts to effectively use all of the resources available to them. Learn more about creating your advanced analytics program by streaming our webinar recording.

Enterprises are increasingly looking to the cloud as a strategic asset to accelerate innovation, data analytics, speed to market, and business value. If you’re ready to begin your cloud data journey, our data migration experts are here to help. Click here to watch our recent webinar series on data migration or contact us to connect with our experts.