Always Modernizing

Key optimization objectives for organizations on their data management journey.

Organizations start data management modernizations for countless reasons. For example, perhaps current data access and reporting are holding back the business in making effective decisions. Or maybe on-premise warehousing costs are too high, and the cloud looks appealing as a method of reducing long-term spending. Often time-to-market is a key driver, as organizations look to deploy new offerings to market quickly but find their data framework can’t support the speed they desire.

Whatever the reason, incentives for data management modernization are vast. Modernizing data management ultimately means organizations position themselves to optimize the information at their disposal to achieve business objectives faster and more effectively.

When formulating a plan for modernizing data management, Concord’s Data Engineering Director, Jeff Rogers, advises organizations to understand where they fit on the Capability Maturity Model Integration (CMMI) framework, a rubric used to assess an organization’s maturity level. By establishing a baseline maturity level, businesses can set more accurate tempos for modernizing their system for data management. 

Jeff explains that organizations at lower CMMI levels would benefit from significant revisions to their digital infrastructure, which may be inadequate or entirely lacking. However, organizations higher on the maturity scale don't need to introduce massive changes to the digital infrastructure. Instead, they typically require refinements to their existing data management technology.

For example, Meta (formerly Facebook) is considered by many to have mastered data management, yet they routinely refine their digital landscape to make improvements. Meta’s data management processes have advanced so much that they now collect data and immediately interpret it, enabling them to make decisions in real-time. This approach provides the organization with unparalleled scopes of information for guiding decisions in line with business objectives and even encourages redefining.

Jeff describes this sophisticated stage in modernization as one where the inroads to improving data management have ensured that “services are strengthened and supported to actualize faster and better business outcomes.” In other words, mature organizations can place less emphasis on how to manage their data. Instead, by instituting adequate systems and technologies for data management, mature organizations can more meaningfully develop strategies for what to do with data.

More data mature organizations often aim to implement better integration systems to optimize their approach. Jeff explains that these businesses may enhance their ETL/ELT capabilities by introducing data integration and application integration models within their data management systems. Data integration solutions work toward expanding and optimizing interactions between diverse data sources.

Data integration lessens the labor involved in traditional modes of integrating information, which emerges from heterogeneous locations. This type of integration allows mature organizations to analyze data efficiently while decreasing the effort required to locate it. In addition, organizations greatly benefit from reducing the speed of identifying areas of improvement. Unearthing opportunities faster inherently means that solutions are applied more quickly while preventing issues from compounding.

A second but related system is application integration. This integration service happens when different applications share data sets. Usually, merging applications simplifies access to all of an organization’s data. Like data integration services, application integration requires collaboration between applications to reduce the redundant gathering and archiving of data. By doing so, organizations can maintain a clean digital infrastructure with greater coherence within their information systems.

Centralizing access to data through integration makes for more efficient business. Data is collected, organized, analyzed, and accessed faster. This process strengthens an organization’s ability to meet its goals efficiently and accurately. And, inevitably, organizations will benefit from the competitive advantage promised by digital infrastructure, which takes modernizing data management seriously. Mature businesses with advanced digital infrastructure are ready to implement more innovative integration services.

While these organizations may be further along in their modernization journey, they still benefit from exploring new ways to innovate and improve their management of data. Asking for external support is one approach that can provide an organization with informed data management refinements. Third-party experts can situate themselves alongside a mature organization’s data modernization journey to offer insights and facilitate areas where an organization can graduate to new heights in establishing digital infrastructure that relies on modernized data management.

This “alongside approach” highlights that modernizing data management is iterative. Every organization, particularly CMMI mature ones, cannot afford to adopt complacent attitudes toward modernization. It’s no secret that data, and a company’s ability to leverage it, defines their success. Achieving real-time results from exceptional data management determines the future trajectory of every enterprise and establishment. Mature organizations thrive by realizing that there is no end to improving data management. Data accumulates exponentially, likewise modernizing management should continue indefinitely.

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