For the purposes of this research, midmarket companies were defined as those falling below $1 billion in revenue. There are also larger organizations with business units that act independently in relation to both their initiatives and budgets. In these cases, similar issues are faced in terms of resources, budget and business drivers, making them comparable to their midmarket counterparts.
This article provides an overview of the data warehouse landscape within the midmarket and provides a summary of the survey results.
The Changing BI Landscape
Until the last few years, the business intelligence market targeted large enterprises with strong IT infrastructures. Data warehouses required data modelers, developers, project managers, etc. to design, implement and maintain data marts and historical data to identify trends and look at information in an interactive way. In addition to a large amount of time and effort, costs of data storage, software and support were astronomical. The expansion of solutions downstream, and the increase in storage, solution diversity and decrease in overall costs create an ideal environment for midsized businesses to adopt technologies and solutions that are no longer out of their reach.
A look at the data warehousing market specifically shows that greater diversity leads to more adoption within small and midsized organizations. With midmarket organizations adopting broader BI technologies, data warehouse solutions are becoming more important and relevant to their business. Because data warehouse appliances offer plug-and-play analytics and initial data management, more midmarket companies are developing their own BI infrastructures in the hopes of data consolidation, analytics and better business performance.
The Unique Needs of Midmarket Organizations
Within the past few years, data warehousing has become more accessible to midsized companies due to increases in storage, better performance, lower price points and easy to implement solutions. Overall, midmarket organizations are similar to their enterprise counterparts in relation to the types of issues they encounter within their businesses, with budget availability and internal resources being the main differentiations. Having access to the right data and being able to make informed decisions based on that data are essential within any company to help drive performance – this is specifically the case within midsized organizations. This is one of the key reasons why the role of BI and data warehousing have become more important within midsized companies as solutions have moved downstream and are more accessible to the midmarket.
The data warehousing appliance market, offering data as a service and general technology advancements (e.g., more space, faster processing speeds, lower prices, etc.) have made it easier for midsized companies to take advantage of technology that may have been out of their reach a couple of years ago. Now, the midmarket has a diverse selection of offerings to choose from, enabling broader information insights and better data management and analytics.
What the Midmarket is Saying about Data Warehousing
Figure 1 provides a summary of research results. The most interesting aspect of Figure 1 is that 45 percent of respondents have revenues under $250 million. This shows that smaller organizations have similar business needs as larger companies, even though they may not have the same resources. In addition, due to the increasing diversity in solution offerings and pricing structures, smaller businesses can adopt data warehousing technologies without large initial expenditures. The second largest respondent group has revenues with more than $2 billion. Although these organizations fall outside the traditional view of midmarket, due to the departmental breakdown and adoption of data warehousing, many of these businesses have similar needs as organizations with smaller overall revenues.
Figure 2 shows that for organizations with current data warehouses in-house, more than 50 percent of respondents’ implementations lasted between six months and two years. Most respondents with implementation times of more than two years fall at the higher end of the revenue spectrum. For instance 32 percent of organizations above $2 billion and 20 percent of organizations with revenues between $750 million and $2 billion represent the largest percentages of longer implementation times.
Figure 3 looks at the types of data warehouses being adopted within midsized businesses. Although cloud-based information storage and interaction are becoming a popular trend, actual adoption is still low, as only respondents with less than $500 million in revenue stated that they deployed their data warehouse via the cloud or through a hosted service provider.
Other applications include overall performance and quality improvements, executive dashboards and operations and maintenance.
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