by CData Software | January 24, 2023

Why Now is the Time for Data Virtualization and SaaS

cdata virtuality

So many disruptions, political, economic, and social. 2022 is finally over. As we enter 2023, it’s a great time to look ahead. What’s new? What’s different? What needs to change?

Three primary forces are transforming data integration in 2023:

  • Data is a competitive opportunity
  • Business takes control of its data
  • Data’s gravity is now cloud-centric

This blog post explores the reasons behind these transformations and how you can apply data virtualization, delivered in a software-as-a-service (SaaS) mode, to respond successfully.  

Force 1: Data is a competitive opportunity

Everyone’s competitive landscape has changed.  

  • Before, we competed locally; today, it’s a global market
  • Before, we could win with better suppliers and superior distribution. Today, everyone has access to everything.  
  • Before, we could ride a product’s success for many years. Product life cycles are short today, and stickiness has become more challenging

Yet one opportunity remains: Driving competitive business value from your data. 

In a Q3 2022 TDWI survey, respondents stated the three most important business drivers behind data platform, management, and integration modernization were:

  1. Observe and enhance customer experiences across channels and drive more intelligent marketing, sales, engagement, and support 
  2. Increase operational efficiency
  3. Generate new business strategies and models.

Let us explore these three business drivers further.

Superior customer experiences

Will you win as the organization that provides the best customer experiences? Data helps you better understand your customer engagement points, provide compelling experiences, and motivate your customers to buy more. 

A 2022 Gartner survey noted that 84% of customer service and service support leaders cited customer data and analytics as “very or extremely important” for achieving their organizational goals in 2023. 

Armed with properly integrated data, you can draw deliberate distinctions between customer segments, explicitly target those that best align with your offerings, and give those customers exactly what they want.

Operational excellence

Will you compete by using your business processes to out-execute your competitors?  

Optimizing your operations requires a deep understanding of what happened, what is happening now, and what will happen. With this data, you can drive an even better outcome. 

IDC recently predicted that by 2024, 30% of industrial organizations would have become leaner and more agile than their competitors due to making real-time operational insights available anytime, anywhere, to anyone. 

Take supply chain operations as an example. You and your competitors might share suppliers and distributors. But you can still win if you can use real-time data to react faster to inevitable disruptions, become a better partner, and uncover hundreds of minor optimizations that, when combined, create a formidable advantage. 

Game-changing innovation

Will you out-innovate your competitors by bringing compelling new products and services to market?  

Data is the most crucial ingredient in your R&D tool kit as it informs your experiments, project status, trial results, etc. Data can also add value to your offerings. Here is one example:

As revenues were dropping due to price-based competition, a European-based global supplier of compressors changed the game by recognizing that their customers wanted compressed air, not compressors per se.  They started instrumenting their equipment with data-gathering sensors, predictive maintenance algorithms, and other data-driven capabilities, so they operated the compressors remotely themselves and thus provided an innovative new product, compressed air as a service.

Force 2: Business takes control of its data

The second force transforming data integration is the evolving business/IT dynamic where business takes control of their data, with IT providing enablement and support. You can see this shift happening in three ways. 

Accelerated timelines

The first way is in accelerated timelines. Simply put, businesses are no longer willing to wait while long IT SDLCs (software development lifecycle) deliver the integrated data they need. Instead, rapid response is the new baseline.  

This trend is particularly true in 2023. According to IBM’s 5 Trends for 2023 report, “Uncertainty is expected, and complexity is compounding. As threats materialize on multiple fronts, organizations must reduce the time from insight to action. Leaders need precise intelligence to dodge obstacles as they appear—and obstacles will be legion.”  

Data on demand 

The second way business users take control of their data is by teaming with IT to enable data on demand. Let’s face it, business users want the data they want, whenever they want, and how they want it. And with the rise of citizen data analysts and citizen data engineers, the business knows what to do with the data once they get it. 

A TDWI Q3 2022 Survey noted the importance of data democratization and increasing self-service functionality in an organization’s data modernization strategy. Nearly 75% of respondents said such efforts were Extremely or Very Important, with only 5% calling them unimportant.  

Business controls the money 

Funding is the third area where businesses have taken control of their data.

According to Gartner, 74% of technology purchases are funded at least partially by business units outside of IT, leaving only 26% of technology investments funded entirely by the IT organization.  

And where is that money going?  It is funding data investments that drive business insights. 

In their 2022 CIO and Technology Executive Survey, Gartner asked respondents which technology areas would receive the most significant amount of new or additional funding in 2022 compared with 2021. 51% selected business intelligence (BI) and data analytics.

Force 3: Data’s gravity is now cloud-centric

The third major force transforming data integration is data’s gravity is now centered in the cloud. While this is a ten-year trend, according to IDC, 2022 was a turning point. For the first time, the cloud would surpass on-premises infrastructure as the primary location where operational data is stored, managed, and analyzed for 50% of Global 2000 organizations. That’s a transformation! 

Additional sources confirm the cloud’s gravitational pull.

SAP cloud revenue overtakes on-premises 

Business Applications is one of the biggest drivers of cloud data growth. You can see this in SAP’s 2022 earnings reports that show SAP Cloud revenue bypassing on-premises for the first time.

Snowflake doubles once again

In 2022, leading cloud data and analytics vendor Snowflake doubled revenue with 106% growth. And that is on top of 124% and 174% in 2021 and 2020.

Cloud platform mega-vendors thrive 

With over $76.5 billion in revenue in 2022, AWS increased quarterly sales by approximately 34% year over year each quarter. Azure grew even faster, with its cloud services revenue growing 40% last year.

And the trend is accelerating. According to Gartner, in 2023, worldwide end-user spending on public cloud services is forecasted to grow 20.7% to a total of $591.8 billion, up from 18.8% to $490.3 billion in 2022.  That’s just over $100 billion in additional cloud spending. 

How to adapt your data integration infrastructure to better respond to these forces

Against these forces, traditional data integration approaches, designed for simpler, less competitive times, don’t stand a chance. 

Ask yourself, what do you need to change?  And what would the impact be if you made the change? Said another way, what three data integration capabilities would your organization love to have, if only you could provide them? 

Agile data integration 

In today’s ever-evolving business and data landscape, victory goes to the swift.  You need agility in your data integration methods.

Agile data development and deployment methods let you quickly configure new datasets in hours or days, avoiding the complex software development lifecycle (SDLC) and long times-to-solution associated with ETL and data warehousing.  

Metadata-driven, data virtualization does not require you to move and consolidate data physically to integrate it.  You can quickly change models within a semantic middle layer, and voila, you have delivered your business user the exact data set they need.  And on the agility point, look for a data virtualization solution that is easy to use. Your data engineers won’t care. They are used to the hard stuff. But with a clean, simple UI, your citizen data specialists will love you. 

The Research Informatics team at Pfizer uses data virtualization to integrate data faster. Their data virtualization implementation allows them to pull new datasets together in a few hours, much faster than the weeks and months required. With this agility, new product development delivers products to market more quickly, a capability of global significance when developing the Pfizer – BioNTech COVID vaccine.

Adaptive data architecture

Because business needs, technologies, and data architecture design patterns (e.g., Data Fabric, Data Mesh, and whatever will be en vogue next year) continue to change, you need to adapt your data architecture to keep pace. With a more agile, adaptive data architecture, you can deliver business value faster and take advantage of technology advancements. 

Data virtualization lets you create a more adaptive data architecture. It does this by decoupling how you manage data from how you consume it. As a result, you can manage each data type optimally—within the original source, in an on-premises data warehouse, in a cloud data lake, on an edge device—wherever it makes the most sense for your users and use cases.

Data virtualization-enabled data lakehouse, data fabric, and data mesh are typical design patterns that embrace today’s distributed data topology rather than trying to force-fit all your data using traditional data centralization paradigms.

Business-friendly data views and governed self-service access

Everyone wants data-enabled employees empowered to drive data-driven business success. Empowering them requires three capabilities. 

  • Business-friendly data views help you deliver data in a business-relevant way instead of how it is stored. Based on easy-to-learn, consistent business definitions, these views keep everyone on the same page
  • Self-service data access democratizes data for your business users so they can focus on how to apply data to business opportunities
  • Governance and security ensure the right people get the right data, no more, no less, and do so in compliance with all data-related regulations.

Modern data virtualization solutions support all three requirements in a single package. 

Data virtualization’s built-in semantic layer automatically populates a governed catalog of business-friendly data views. When your business users need data sets, they can find them. And if the perfect data set doesn’t exist, the latest point-and-click interfaces allow citizen users to build what they need, often without IT assistance.  

As a result, your users can focus on delivering business value without worrying about IT internals, a win-win for IT and the business.  

Cloud-native data integration platform 

Given all the research that shows how data’s gravitational center has shifted to the cloud, doesn’t it make sense to move your data integration gravitational center to the cloud?  

Such a cloud-native data integration platform must support 

  • Your broad and changing data integration mix, including virtualization, consolidation, replication, migration, and more.
  • Your fast-growing cloud-resident data as well as traditional on-premises sources.  
  • Your most demanding reliability, availability, and scalability service-level agreements.

Moving to the cloud helps your IT team do more.  It frees cycles IT would normally spend optimizing your instances, scaling up for greater loads, resolving issues, and more.  Unleashed from these operational burdens, your IT team can spend more time improving agility, architecture, access, security, and more.  

But buyers, beware! Be sure you are getting a complete SaaS solution that not only resides in the cloud but also frees you from having to set it up, run it, manage it, and upgrade it. Instead, why not let your SaaS data integration provider do that for you?

The market’s first data virtualization SaaS

Discover our CData Virtuality SaaS solution, the first one of its kind on the market. A fully managed cloud service offering with automated set-up, no server management, no maintenance, and no manual updates that allows you to take advantage of your data without worrying about the technical side.