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The scales have finally tipped! According to a Flexera survey, 93% of organizations have a multi-cloud strategy and 53% are now operating with advanced cloud maturity. For those who are now behind the bell curve, it’s a reminder that keeping your data architecture in an on-premises solution is detrimental to remaining competitive. On-prem architecture restricts your performance and the overall growth and complexity of your analytics. Here are some of the setbacks of remaining on-prem and the benefits of data migration from legacy systems.

Looking for the right path to data modernization? Learn about our 60-minute data architecture assessment and how it will get you there.

Greater Decentralization

For most organizations, data architecture did not grow out of an intentional process. Many on-prem storage systems developed from a variety of events ranging from M&A activity and business expansion to vertical-specific database initiatives and rogue implementations. As a result, they’re often riddled with data silos that prevent comprehensive analysis from a single source of truth.

When organizations conduct reporting or analysis with these limitations, they are at best only able to find out what happened – not predict what will happen or narrow down what they should do. The predictive analytics and prescriptive analytics that organizations with high analytical maturity are able to conduct are only possible if there’s a consolidated and comprehensive data architecture.

Though you can create a single source of data with an on-prem setup, a cloud-based data storage platform is more likely to prevent future silos. When authorized users can access all of the data from a centralized cloud hub, either through a specific access layer or the whole repository, they are less likely to create offshoot data implementations.

Slower Query Performance

The insights from analytics are only useful if they are timely. Some reports are evergreen, so a few hours, days, or even a week doesn’t alter the actionability of the insight all that much. On the other hand, real-time analytics or streaming analytics requires the ability to process high-volume data at low latency, a difficult feat for on-prem data architecture to achieve without enterprise-level funding. Even mid-sized businesses are unable to justify the expense – even though they need the insight available through streaming analysis to keep from falling behind larger industry competitors.

Using cloud-based data architecture enables organizations to access much faster querying. The scalability of these resources allows organizations of all sizes to ask questions and receive answers at a faster rate, regardless of whether it’s real-time or a little less urgent.

Plus, those organizations that end up working with a data migration services partner can even take advantage of solution accelerators developed through proven methods and experience. Experienced partners are better at avoiding unnecessary pipeline or dashboard inefficiencies since they’ve developed effective frameworks for implementing these types of solutions.

More Expensive Server Costs

On-prem data architecture is far more expensive than cloud-based data solutions of equal capacity. When you opt for on-prem, you always need to prepare and pay for the maximum capacity. Even if the majority of your users are conducting nothing more complicated than sales or expense reporting, your organization still needs the storage and computational power to handle data science opportunities as they arise.

All of that unused server capacity is expensive to implement and maintain when the full payoff isn’t continually realized. Also, on-prem data architecture requires ongoing updates, maintenance, and integration to ensure that analytics programs will function to the fullest when they are initiated.

Cloud-based data architecture is far more scalable, and providers only charge you for the capacity you use during a given cycle. Plus, it’s their responsibility to optimize the performance of your data pipeline and data storage architecture – letting you reap the full benefits without all of the domain expertise and effort.

Hindered Business Continuity

There’s a renewed focus on business continuity. The recent pandemic has illuminated the actual level of continuity preparedness worldwide. Of the organizations that were ready to respond to equipment failure or damage to their physical buildings, few were ready to have their entire workforce telecommuting. Those with their data architecture already situated in the cloud fared much better and more seamlessly transitioned to conducting analytics remotely.

The aforementioned accessibility of cloud-based solutions gives organizations a greater advantage over traditional on-prem data architecture. There is limited latency when organizations need to adapt to property damage, natural disasters, pandemic outbreaks, or other watershed events. Plus, the centralized nature of this type of data analytics architecture prevents unplanned losses that might occur if data is stored in disparate systems on-site. Resiliency is at the heart of cloud-based analytics.

It’s time to embrace data migration from legacy systems in your business. 2nd Watch can help! We’re experienced with migration legacy implementations to Azure Data Factory and other cloud-based solutions.

Let’s Start Your Data Migration

Software & Solutions for Marketers is the final installment in our Marketers’ Guide to Data Management and Analytics series. Throughout this series, we’ve covered major terms, acronyms, and technologies you might encounter as you seek to take control of your data, improve your analytics, and get more value from your MarTech investments.

In case you missed them, you can access part one here, part two here, and part three here.

In this last section, we will cover various aspects of software and solutions for marketing, including:

The differences between the cloud and on-premise (on-prem) solutions
Customer data platforms (CDP)
Custom development (custom dev)

Cloud vs. On-Prem

Cloud

Also known as “cloud computing,” the cloud is a global network of software and services that run over the internet on someone else’s server, as opposed to running locally on your computer or server.

Why It Matters for Marketers:

Get the flexibility your business needs. Today’s marketing teams are mobile, require a variety of working schedules, and are often spread across geographies and time zones. Cloud-based software and services are accessible by any device with an internet connection, quick to set up, and reliable to access, regardless of the user’s location or device.
Deliver the level of service your customers expect. Hosting your website or e-commerce business on the cloud means your site won’t get bogged down with high traffic or large data files. Additionally, hosting your data in the cloud reduces the amount of siloed information, empowering teams to work more seamlessly and deliver a higher quality, more personalized experience to customers.
Spend your money on campaigns, not infrastructure. While many softwares are sold with on-premise or cloud options, the cloud-native options (tools such as Snowflake, Azure, AWS, and Looker) enable marketers to use these technologies with little to no reliance on IT resources to maintain the back-end infrastructure.

Real-World Examples:

Most marketing organizations use cloud-based applications such as Salesforce, HubSpot, or Sprout Social. These cloud-based applications allow marketing users to quickly and reliably create, collaborate on, and manage their marketing initiatives without being tied to a single location or computer.

On-Prem

On-premise or on-prem refers to any software, storage, or service run from on-site computers or servers.

Why It Matters for Marketers:

Most marketing software is run on the cloud these days. Cloud solutions are faster, more dynamic, and more reliable.

So why would a business choose on-prem? Today, there are two main reasons a business might still have on-prem software:

The company is in a highly regulated industry where data ownership or security are big concerns.
The company has legacy on-prem solutions with massive amounts of data, making the switch to cloud more challenging.

However, many of these companies still recognize the need to update their infrastructures. On-prem is harder to maintain and has reduced up-time as glitches or breaks are fixed at the speed of IT teams. What’s more: on-prem solutions can bottleneck your insights and ability to deliver insights at scale.

With this in mind, even companies with more complicated situations can use a hybrid of cloud and on-prem solutions. By doing this, they migrate less sensitive information to the cloud while keeping more regulated files on their own servers.

Real-World Examples:

In marketing, it’s likely that most data will be in the cloud but if you’re working with a client in a highly regulated industry, like government or healthcare, you might have some on-premise data sources.

Healthcare companies have patient privacy regulations like HIPAA about how customer data can be used, including marketing campaigns. In this case, an on-prem solution might be a better alternative to protect patients’ rights.

Customer Data Platform (CDP)

A customer data platform is a software solution that synthesizes customer data from various sources to keep them in sync with each other. CDPs often additionally offer the ability to send this data to a database of your choice for analytics.

Why It Matters for Marketers:

CDPs allow your various tools (such as your CRM, Google Analytics, and e-commerce systems) to stay in sync with each other around customer data. This means if you change a detail about a customer in one system, everyone else sees this update come through automatically without any manual updating.

Real-World Examples:

CDPs make it really easy to create quality account-based marketing (ABM) campaigns. CDPs deliver a persistent, accurate, and unified customer base, making it easy to use data throughout the ABM campaign.

For example, selecting and validating target accounts uses data from across your entire organization. Once pulled into the CDP, you can perform analytics on that data to identify the best accounts to go after. You will have thousands of attributes to better understand which customers are more likely to purchase.

One note: CDPs do not usually tie these customers and their information to other subject areas like products, orders, loyalty, etc. They are also not meant for analytic use cases. If you are doing deeper, company-wide analysis, you might want a data warehouse.

Custom Dev

Custom development, or custom dev, is a term that refers to any application or solution developed to satisfy the requirements of a specific user or business rather than for general use.

Why It Matters for Marketers:

Even the best out-of-the-box software or solutions are designed to overcome the challenges of a broad user base, providing functionality that only satisfies generalized needs. Custom dev solutions address your specific business needs in a way that gives you a competitive advantage or reduces the amount of time spent trying to make a generic software match your unique needs.

Real-World Examples:

One retail company was receiving flat files from a monthly vendor report that were hard to integrate with the rest of their reports. This made it challenging to get the deeper insights their marketing team needed to make informed omni-channel decisions.

As there were no tools available in the market with a connector to their system, a custom dev solution was needed. An application was created to automatically take in these flat files from the vendor so the marketing team could receive new data without the lengthy request and ingest process that relied heavily on IT resources. This enabled the marketing team to easily target the same customer across channels by using personalized campaigns that aligned with purchasing habits and history.

Another example of custom dev is the implementation of automated customer touchpoints. Adding features that trigger events based on business rules is a great way to personalize your customers’ experience. For example, you could create a rule that emails customers a coupon for their most frequently purchased product when they haven’t made a purchase in the past six months.

Throughout this Marketers’ Guide to Data Management and Analytics series, we hope you’ve learned about the different tools to manage, integrate, analyze, and use your data more strategically to get the most out of your investments. Please contact us to learn how we can help build and implement these various solutions, so you can better understand your customer base and target your customers accurately.