Five practical recommendations for your 2022 Data And Analytics initiatives in the Cloud

As seen on Forbes.

Covid-19 accelerated digital transformation for enterprises in all industries — and today, cloud initiatives are at the core of digital transformation. Enterprises are likely to experience mixed success with their cloud initiatives in the medium term as they manage challenges such as severe skill shortages, evolving data architecture practices and myriad cloud vendors with similar offerings.

Drawing from our company’s experience of implementing more than 50 cloud initiatives across industries, here are my top five recommendations for business and IT leaders planning significant data and analytics (D&A) initiatives in the cloud.

1. Not everything that can be moved should be moved to the cloud.

Cloud migrations involve significant capital expenditures (CAPEX). In my experience, when you migrate old data applications to the cloud, you should not expect to see operating expenses (OPEX) savings for up to three years. In many cases, all layers are not migrated together due to interdependencies on other systems, leading to a hybrid approach with a combination of on-premises, private and public cloud hosting.

Carefully evaluate the suitability and need to migrate the following category of applications to the cloud:

• End-of-life legacy applications or tool platforms
• Applications built on comparable SaaS (Software as a Service) tools
• Applications accessing data that requires stringent data security and privacy
• Specific hardware-dependent applications

2. Plan to embrace a multi-cloud future.

Three leading public cloud players — Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP) are adding capabilities, services and geographical locations at rapid pace. Most of their comparable services match each other in terms of cost and performance, and with no consolidation in sight, you can benefit from their competition.

Each of these cloud vendors do provide a few differentiating services. To enable the creation of cutting-edge data and analytics solutions, aim to leverage the best services available, regardless of which vendor provides it. For example, one of our clients — a leading media and entertainment company — uses a multi-cloud setup with AWS infrastructure and select AWS services for its data apps, Azure for email services and cloud native PaaS platforms like Domo and Snowflake for analytics.

Within your organization:

• Discourage investment in single cloud vendor
• Promote a culture of looking for the best services, comparing capabilities and costs across cloud vendors
• Encourage technical teams to design data architectures that seamlessly use cross-cloud capabilities

3. Don’t let security be an afterthought.

According to the Verizon Data Breach Investigations Report (DBIR), most cybersecurity incidents now involve cloud infrastructure. We can expect the threat of data breaches to grow in the foreseeable future, and the responsibility for increasing security protections lies with enterprises.

In our work, we have seen that most cloud initiatives, especially enterprises’ early endeavors, try to address security requirements through native services. However, due to inadequate design, these solutions fall short of addressing all risks. Thankfully, there are a number of solutions from third-party vendors available that you can use to address this critical gap. Use these tools to:

• Carefully assess security requirements
• Invest early in holistic security solutions
• Conduct frequent vulnerability scans

A global bank that we work with has implemented a unified data-centric security model with sensitive data-flow discovery, real-time monitoring, behavior analytics and protection across all operational and analytical applications (both on-premises and on-cloud).

4. Monitor all D&A solutions through a unified platform.

Given the nature of cloud services, any data and analytics platform migrated to the cloud gets decomposed into many independent solutions. While this offers advantages, such as no single point of failure and scalable performance, managing multiple platforms can be complex. In case of service level failures, it can be difficult to ascertain the root cause, replay the sequence of events and recover from the failure.

DevOps staff supporting disparate platforms need to invest significant effort in scanning consoles of multiple services for any meaningful analysis — post mortem or change impact. It is highly likely that components of such systems will drift away from the initial architectural vision. To avoid this outcome, push for:

• Holistic assessment of current and future monitoring requirements
• Early investment in a comprehensive monitoring solution
• Frequent “game day” drills to test responses, in processes and people

A global market research firm we work with uses a centralized monitoring platform to track its infrastructure, databases, analytical apps, workflows and security. It gives them the ability to have a 360-degree, single-pane view of its data and analytics ecosystem and provides greater operational efficiency.

5. Aim for an accelerated pace of innovation through the cloud.

For most enterprises, the first set of cloud initiatives includes migrating existing data and analytics applications to a cloud platform. Whether as-is (lift and shift) or re-engineered, these types of migrations don’t change the status quo dramatically.

But there is a constantly expanding set of cloud offerings that covers capabilities like IoT, blockchain, data science, machine learning, media, quantum, robotics, satellite, VR and AR. Explore how your organization can use cloud initiatives to power innovation. How effectively you do this will prove to be a competitive advantage in the Industry 4.0 era.

There are also countless focused solutions available on cloud marketplaces that significantly reduce the cost of experimentation. Take advantage of these cost-effective tools and encourage:

• A culture of innovation with cloud at the center
• A risk appetite based on leveraging cloud offerings and marketplace solutions
• Thinking “cloud first” before costly in-house development of new solutions

Your organization has probably moved the first set of data stores and front end analytics apps to the cloud with varying degrees of success. Enterprises that don’t see measurable positive outcomes with their first cloud initiatives tend to delay the rest of their cloud adoption journey. Don’t fall into the same trap. Cloud initiatives will continue to be a critical ingredient for future business capabilities. By finding the right solutions and engaging the right partners, you can set your organization up to make well-informed choices, develop pragmatic roadmaps and avoid the pitfalls that lead to failure.