Some companies are born in the Cloud. Others move some or most of their data infrastructure to the Cloud out of desire for modernization, corporate mandate, or simply out of necessity. Others still seem wedded to an on-premise architecture with their data and applications residing behind the firewall. Regardless of the approach, most organizations today recognize the symbiotic relationship between the way they manage data and the effectiveness of the analytical activity their users strive for today.

The legacy approach in the data environment seemed to promote centralization in an effort to reduce heterogeneity, improve visibility, and support better data quality. A side effect to that approach however — at least from an analytical standpoint — was an increasing gulf between the data used to support decisions and the people actually making those decisions. Companies today, recognizing a demonstrable desire on the part of their users to take a more active role in exploring data, seek to create a more cohesive analytics “stack” that ties together the component parts harmoniously. Capabilities like data integration and blending, data catalog, data preparation, data enrichment, governance, discovery, and visualization, are now designed as a modern continuum to support enhanced business decisions.

Moreover, as users start to clamor for more sophisticated capabilities under the umbrella of augmented analytics (e.g., AI, machine learning, natural language processing (NLP), search-based analytics) the stability, accessibility, and usability of the data infrastructure is becoming more important than ever before. Companies invested in cloud-based data, either exclusively or part of a hybrid infrastructure, tend to view this analytical future as more of a reality than a pipe dream (Figure 1).

Figure 1: Cloud Users Mentally Prepared for the Future of Analytics

Aberdeen’s research continuously demonstrates that users in more functional areas are becoming ever more curious about their business. While the questions might be simple, the road to an actionable answer is typically fraught with complexity. The most pertinent business questions may require data inputs from a large number of sources (traditional data warehouses, applications, data stores, spreadsheets) and from a variety of data flavors (structured, unstructured, geospatial, 3rd party). Additionally, many of these sources and data types, stemming from modern applications or web-based architectures, naturally live in the Cloud already.

Because of this prevailing reality, companies are finding more validity in a cloud-based or hybrid approach to their data warehouse environment. For the companies that excel with this approach, the research reveals some interesting defining characteristics. One is that top cloud users tend to operate a more technically sophisticated data warehouse. Fifty-two percent of Best-in-Class cloud users report using a high-performance data warehouse purpose-built for speed, scalability and versatility. Conversely, Average and Laggard companies are much more likely to use a standard or legacy relational database management system (RDBMS) or in some cases a primitive environment that is informally managed and often wrought with quality issues.

The Best-in-Class are also more likely to leverage certain internal capabilities that support their elevated performance, including:

  • Processes to support business users connecting to new data sources on their own
  • Collaborative / cross-functional relationship between IT and the Line-of-Business
  • Corporate mandate or initiative encouraging data-driven decisions
  • Formal efforts to develop data / analytic skill sets in-house.

Empowered by these capabilities and their data sophistication, top cloud users experience real results (Figure 2).

Figure 2: Top Cloud Users Drive Data Efficiency, Business Results

The metrics above provide a few glimpses into this modern data continuum that so many companies strive for. The ultimate objective is to capture data more effectively, improve its quality and usability, deliver it to users in a timely way, and support business execution.

Procrastination or refusal to migrate to a cloud-based environment isn’t necessarily the hallmark of a stodgy company destined for failure. However, the flexibility and accessibility that these platforms can offer make a cloud-based approach enticing for companies that need to rely on data to maintain their competitive position as the technology landscape evolves. Some are able to execute on this promise better than others. Best-in-Class companies that leverage a cloud-based data architecture are more organizationally mature, technically savvy, and reap the benefit of superior business performance as a result.