A survey of 450 digital transformation leaders conducted by the market research firm Vanson Bourne, on behalf of Couchbase, a provider of a document database, finds that organizations will spend an average on $30 million on these types of project within the next 12 months.
While each of these projects is intended to modernize one process or another, the biggest challenge these organizations are facing in terms of achieving that goal includes some very old-fashioned data management issues.
Data management proves challenging
A full 80 percent of respondents said their organization had to scale back ambitions for Internet of Things (IoT) or mobile applications and services because of data challenges that mainly arise from reliance on legacy relational databases. Just about every respondent is still employing a relation database (90 percent), with 38 percent describing that usage as “heavy.” Nearly three quarters (72 percent) say that reliance limits their ability to implement digital transformation projects.
As a result, 79 percent of respondents are actively planning to reduce their reliance on relational databases, with 56 percent planning to do so in the next 12 months. Nearly three quarters (74 percent) are moving to newer databases more slowly than they should because they still rely on legacy databases for mission critical applications. Well over half (60 percent) said too much time is wasted dealing with legacy technologies. Another 63 percent saying their organization is using more databases than it should be, with 28 percent saying they would like to consolidate databases.
A recent survey of #DigitalTransformation leaders finds that organizations will spend an average of $30 million on #DigitalBusinessTransformation initiatives within the next 12 months.
A primary reason for not replacing legacy relational databases is the fact the organization’s IT architecture is built around it (39 percent). Just under a third (30 percent) don’t want to retrain their IT staff, while 29 percent believe it would be too complex to rip and replace legacy databases. Only 15 percent don’t trust newer database platforms with business-critical data or applications.
In terms of deployment models, the survey finds the most commonly supported deployment model for database infrastructure is private cloud (50 percent), followed by hybrid cloud (45 percent), on-premises IT environments (39 percent), public clouds (34 percent), and Database-as-a-Service (31 percent).
Digital transformation leaders are under a lot of pressure
More than two-thirds of respondents (68 percent) agree that getting the right technologies in place for digital transformation can seem like an insurmountable task. In terms of investments, a full 80 percent have invested or soon will in mobile applications, followed by artificial intelligence (52 percent), edge computing (50 percent), blockchain (51 percent), and augmented and virtual reality (42 percent).
In terms of bang for the IT investment dollars, AI ranked highest (39 percent), followed by cloud computing (35 percent), and big data analytics (32 percent). However, in terms of total dollars spent, 42 percent said cloud computing will have the most money spent on it in the next five years, followed by AI (38 percent), big data analytics (30 percent), and mobile applications (29 percent).
The single largest issue by far is data security (47 percent), with 42 percent identifying encryption as a major area of focus. Other priorities include analysis of operational data in real-time (40 percent), scalability (39 percent), portability of data between cloud and on-premises (37 percent), and always-on performance (34 percent).
Clearly, digital business transformation is surfacing a treasure trove of opportunities for managed services providers (MSPs) with expertise in the right areas. However, it’s also worth noting that one of the biggest digital transformation opportunities for MSPs is not in the realm of emerging technologies, but rather fundamental data management issues that many MSPs are already well-positioned to address.
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