Data migration takes many forms, including moving data between storage locations or mediums, changing the format of the data, and sharing or importing data between applications. It’s required when retiring a legacy system, introducing new apps or services, migrating to the cloud, or consolidating your data center.
Data storage can be a complicated beast thanks to the myriad ways data grows and integrates with various components of your IT infrastructure. A secondary goal of any data migration project should therefore be data management itself, reducing complexities introduced by application logic, customization, governance, and other entanglements.
Regardless of the destination of your data or the business drivers behind the migration, you’ll need to extract your data, modify it, and perform the actual data transfer. Detailed planning and risk evaluation are key before proceeding, especially as you are likely to handle some sensitive information.
It happens to everyone at some point. Your budget gets slashed; the economy tanks; you’re suddenly in the red thanks to cloud sprawl. Whatever the cause, you’ll likely face a mandatory cost cutting initiative at some point in your IT career.
While cost cutting is a reality, it is fundamentally different from ongoing cost optimization. You should be practicing cost optimization as part of your regular duties, reviewing spend and ensuring the technology, hardware, software, and services in use across your organization are serving their business need and appropriately configured in scope and performance.
By formulating and practicing a cost optimization protocol, you’ll be prepared should the day for cost cutting ever come, while also gathering evidence for the impact IT has on the overall bottom line.
If your organization is large enough to have an information security manager or an entire security team, then it’s likely that any security issue or task will be pushed in their direction. That’s why you hired them, isn’t it?
Security is a specialized area of IT and it requires specific skills for a holistic approach. It is also a moving target with many components and attack vectors across your technology stack. A dedicated security team or individual, whether in-house or contracted, can therefore be valuable. But security must be a shared responsibility among every user, no matter their role.
There’s an inherent problem here and its name is Diffusion of Responsibility. When everyone has a stake in security and there are dedicated managers to boot, users could be more likely to engage in risky behavior. After all, it’s taken care of! That’s why we hired that security guy.
It might feel like DevOps is eating the world, but there’s still room for other innovations within and adjacent to IT operations. One such example is the DataOps movement. The general inspiration behind DataOps is similar to DevOps in that is strives to provide higher quality deliverables from shorter cycles by leveraging technology and specific methodologies around it.
DataOps does not boil down to DevOps principles applied to data analytics, however. While both approaches may embrace automation, continuous improvement, and strong communication between departments, DataOps is less of an infinite cycle and more of an injection of agility into a one-way data pipeline.
Let’s explore the roles, strategies, and technologies at play in a DataOps approach to analytics.
A fundamental building block for your successful adoption of cloud services is the organizational hierarchy, a mode of organizing your cloud services, resources, and virtual machines in such a way that you ensure cloud governance and can better resolve billing within your organization.
Cloud governance is the answer to common questions like:
• “How do I keep my data compliant with industry regulations?”
• “How can I implement chargeback within my organization so I know which departments are consuming cloud services and account for that usage?”
• “How can I mandate security and access measures across our cloud environment?”
By implementing a flexible set of controls and overall organizational hierarchy within Azure, you can enable adoption of the cloud services your business units require and avoid shadow cloud use. A well-designed enterprise cloud environment can accommodate modern agile practices alongside traditional workloads.
Here’s how to structure your organizational hierarchy within Azure so you can set governance requirements and encourage speed of delivery for your individual departments and business units.