As companies seek digital transformation, they’re looking for new ways to integrate and manage data. CIOs understand that data is now the primary currency of business — the raw material that companies transform into greater efficiency and industry-disrupting ideas. That means data logistics and refinement processes have taken on new importance.
Data integration and management techniques have evolved considerably over the past five years. But to get an edge over competitors, company leaders must be prepared to anticipate emerging data integration and management trends. Here are five ways data integration and management are expected to evolve over the next several years:
1. Disappearing data domain boundaries
Data has traditionally been categorised based on integration patterns — not because it makes sense to divide information into separate domains, but because early integration technology couldn’t handle multiple patterns, such as MDM, B2B, social media data, etc. Next-generation integration capabilities can handle structured and unstructured formats with ease, so it’s now more efficient to manage multiple integration uses on a single platform.
This trend is behind the strong growth of the hybrid integration market, which a recent MarketsandMarkets report estimated will almost double by 2022 — reaching $33 billion.
The array of technologies available to handle integration means IT leaders must make careful decisions when choosing a solution, factoring in the various capabilities of hybrid platforms, including pricing considerations, support levels, scalability, flexibility, etc.
2. Leaving legacy integration technologies behind
An Aberdeen Group study conducted last year found that companies will replace 84% of middleware within the next four years. Only 30% of surveyed companies plan to consider an on-premises solution to replace their middleware, a signal of a mass migration to the cloud.
Digital transformation is a key factor in the shift to the cloud, as enterprises seek solutions that are efficient, flexible and scalable. In the supply chain sector, for example, enterprises are looking for technology that allows them to operate as a dynamic value ecosystem, with vendors and suppliers collaborating to provide new digital services in response to customer demand. Creating that level of customer value requires robust data integration and management capabilities.
3. Working with integration services to buffer complexity
As integration needs become more complex, enterprises will need specialised data integration skills to handle the inflow of information. As a stop-gap measure, some organisations are using do-it-yourself “citizen integrator” tools to create workarounds for distributed data networks.
As data proliferates and sources of information increase, enterprises will have to devote a growing amount of in-house resources to integration tasks — talented IT professionals who could otherwise be working on more strategic assignments. This will inspire IT leaders to consider using managed services instead. By taking care of data integration and management needs via managed services, enterprises not only have more resources to devote to innovation, and they can scale services up or down to meet demand.
4. Prioritising data management
Improving integration has been a major focus in IT departments and vendor support groups for the past several years. Improving integration capabilities was a necessary first step before enterprises were able to take advantage of the valuable insights contained in their data. But with better integration capabilities, businesses will increasingly turn their attention to data management, devoting resources to it in recognition of data’s strategic value.
With better data management capabilities, organisations can create value for customers and generate innovation that gives them a marketplace advantage. That’s why the master data management (MDM) market is growing quickly — it is projected to reach nearly $38 billion by 2022, according to a Zion Market Research study. The most forward-thinking enterprises are accessing platforms to support digital transformation.
5. Leveraging advanced platforms to comply with data security and privacy regulations
As privacy concerns grow, regulatory entities and governments are implementing more stringent rules about handling sensitive data. Last year set new records for security breaches, and 2018 is projected to be even more risky for consumers and companies alike. Business leaders recognise the value of data, and so do hackers, who are working on more sophisticated exploits all the time.
It’s a challenge for companies to keep up with changing compliance rules and security best practices. IT professionals must anticipate security threats and prepare systems for compliance with new regulations, like the General Data Protection Regulation (GDPR) standards that will take effect in May 2018. For that reason, many companies are turning to managed services to ensure that their platforms are compliant and that people and processes meet industry security standards as well.
The data integration and management landscape is shifting rapidly as enterprises appreciate the value of the information they collect. Old domain boundaries no longer apply, and outdated middleware is being left behind as businesses migrate to more efficient, flexible and scalable cloud services. As these trends play out, executives will make critical decisions about whether to handle integration, management and compliance in-house or outsource for data expertise and focus on core competencies.
One effect of the shift is that the two disciplines involved — data integration and data management — are converging into a single market: the data platform market. That makes sense as the two components function as a single whole with one objective: to help enterprises generate value from data. IT leaders who understand these trends and respond to the changing data integration and management landscape will be ahead of the curve.
Sourced by Rob Consoli, CRO, Liaison Technologies