Based on the presentations made at the Gartner Symposium in Barcelona, it’s clear digital transformation will remain the bedrock of IT strategy in the coming year.

There have been many examples of companies transitioning to digital business models to drive competitive advantage.

However, there have been warnings sounded amid the hype, particularly advising CIOs not to become too focused just on customer-facing applications.

Companies have achieved some quick wins by evolving how they interact with customers, but there is a danger that adding new digital applications without proper integration will only add costs and make existing IT infrastructures ever more unwieldy.

Therefore, in the coming year I predict data consolidation will become the watchword for smart CIOs. This will see organisations integrate and streamline information from existing back-end and legacy IT systems to digital, customer facing applications.

Now that companies have achieved their quick wins, it is only through this consolidated view of their organisations and customers that they will be able to move to the next stage of digital transformation.

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The reason is simple. The digital era has spawned entirely new forms of structured and unstructured data for companies to manage across their IT environments.

For example, Gartner claims there will be more than 20 billion connected devices by 2020 if the Internet of Things takes off. This will lead to exponential growth in data.

In their efforts to move online rapidly, many organisations have turned to NoSQL-only solutions like MongoDB and Cloudera or Graph-based databases. This is understandable because of their primary focus on storing and processing huge volumes of data.

However, as the dust of 2016 settles, smart CIOs will be counting the cost of rapid expansion of multiple data management systems, and the difficulty in integrating these systems.

Companies are already feeling the impact of sprawling pools of unstructured data lakes. Aside from the expense of storing all this data, there are a number of practical implications.

For example, unlike the relational SQL model, which aims to normalise data to eliminate redundancy and reduce storage, the NoSQL data type does not encourage this approach.

If ten employees work for the same department and manager, the department name and manager’s name maybe stored 10 times. This introduces data redundancy and a possibility that data gets out of sync.

The manager’s name might be spelled “Johnson” nine times and “Jonson” once. Querying for employees working for Mr. Johnson could now fail to account for all of his employees.

>See also: The ripple effect: acquisitions and the consolidated storage ecosystem

With relational databases, this is not a problem because referential integrity compliance means that data will be matched correctly and duplication avoided.

Data consolidation in the data centre will ensure that different data types are integrated so that information is stored and organised in a way that it can be easily queried and analysed.

This does not mean getting rid of NoSQL-only or Graph databases in favour of relational ones. NoSQL databases perform very valuable functions, but if CIOs are to enable businesses to create an integrated, a single view of customers, market opportunities, and operational efficiencies, consolidation has to be a priority.

Armed with this uniform picture, companies will be able to move to the next phase of digital transformation, building more sophisticated customer relationships, offering more personalised experiences, increasing customer satisfaction; and done in a more efficient manner.

Getting to this point, though, does have potential challenges, and it is critical that customers ask their database vendors the right questions regarding managing their data.

For example, CIOs need to know how easy it is for them to integrate data from different stores into their existing infrastructures. As they seek to use data from disparate applications, CIOs should be wary of hidden costs such as indirect access.

This is the practice, common among very large database vendors, of charging customers for another vendor’s application to access and use data stored in their systems. There is also the the Cloud question.

CIOs are being told of huge cost savings and operational efficiencies in the Cloud, but setting up applications and transferring data to and from the Cloud can have its challenges.

Data consolidation should offer efficiency and greater flexibility to move between on premise, public, private, and hybrid Cloud with ease. Customers need to ask vendors what costs will be attached to such a transition.

CIOs need to know what heavy lifting will be expected of them if they want to have this control over their data and the ability to shift it around in a more dynamic way.

>See also: 10 predictions for the Internet of Things and big data in 2017

Open source solutions can play a critical role in enabling data consolidation in 2017. Open Source will also help to ensure CIOs minimise the potential challenges and hidden costs set forth above.

Using more open source in the data centre is a positive move as open-source tends to leverage standards, and standards-based solutions enable IT environments to be vendor agnostic, simplifying how applications communicate with one another.

This offers the right foundations for data consolidation, easing integration and providing a data fabric that combines structured and unstructured data from disparate solutions.

If CIOs can manage their entire data sets on widely accepted standards, then they will create a single data platform that ensures both information integrity and long-term stability.

This is crucial if digital transformation initiatives are to succeed and avoid the many hidden costs of data management.

Sourced by Marc Linster, SVP products and services, EnterpriseDB