Gartner’s BI and Analytics Platforms 2015 Magic Quadrant was released back in February 2015, so it’s hardly “new news” any more…except that our current and prospective clients and partners keep asking us for feedback on how to address the top trends highlighted in the report, especially given that the key players on the report and the trends represented a major change from last year’s quadrant! This blog post addresses what the Performance Architects team believes are the three big trends in the report and how to address these.
Trend #1: Decentralization
According to Gartner, the BI and analytics market has undergone a “fundamental shift” over the past six years from large-scale, highly-governed, centralized BI to a more decentralized and departmental model using focused reporting and analysis tools with demand for more self-guided data discovery in place of standardized reports.
What Gartner’s report leaves out is that IT organizations went through massive downsizing over the past six years, leaving very little in the way of centralized support for business users. Most larger organizations that we have worked with in this time period were stripped down to only “lights-on” support staff on-site, while maintaining a large contingent of off-shore resources for maintenance and enhancement work. In our opinion, this has been the catalyst behind this shift.
Organizations needed to be more competitive over the past six years in order to just survive. The lack of available on-site IT staff for business support staff, in conjunction with this new overwhelming need for competitive and strategic intelligence, is causing lines of business to turn away from central IT. The availability of more powerful, localized BI and analytics systems is now making it easier for business users to gather, consolidate, and report on their own data without the need for IT services.
Trend #2: Data Discovery
Newer software vendors have come to market with strong data discovery capabilities. In reaction to this trend, traditional BI platform vendors are working very hard – but aren’t necessarily succeeding – at providing their own business-user-driven data discovery capabilities. The potential problem with this situation is that these large software packages reside in central IT, while business-focused data discovery tools are gaining a foothold directly within the lines of business.
What is most ironic and interesting about this trend is an issue highlighted by Gartner in the report: “Customers of IT-centric platforms that have a broad range of BI platform capabilities report [that they are] using them narrowly, most often for production reporting. “ In other words these large-scale analytical systems with data discovery capabilities are being used for operational, “lights-on” reporting.
Gartner goes on to state, “On the other hand, business-centric platforms such as Tableau, QlikTech and other emerging vendors have a more narrow set of capabilities, but are used more broadly for a range of BI and analytics functions — including for reporting, for which they are not optimally suited, and for expanding use cases — primarily because they are easy to use and deploy.” This includes the fact that many of these applications cannot scale to the enterprise level.
Trend #3: Cloud and Software-as-a-Service (SaaS)
Gartner states that the overall interest in cloud BI declined slightly during 2014, to 42% compared with last year’s 45%. For those who are interested in cloud, there is a definite leaning toward private and hybrid cloud solutions. Once again, the major impetus for the push to cloud comes primarily from organizations whose lines of business are already in the cloud. Private cloud seems to be winning as the most preferred near-term solution, and I believe this is a result of concerns (in some cases, regulations), over data security.
The main issue for organizations in implementing cloud is the lack of a strategy on how to integrate cloud services and data with their on-premise infrastructure. This is further demonstrated by the fact that most cloud solutions are just coming forth with “hybrid” solutions. So the technology and the vision from cloud vendors themselves is still not very mature at this point.
What You Can Do To Address These Three Big Trends
There are many factors to consider when addressing these trends. As you would imagine there is no “one-size-fits-all” solution. Here are some points to consider when modernizing your IT infrastructure to address these disruptive technologies.
- Review the prevalence of these technologies across your enterprise. Departments in your organization are probably using cloud-based data discovery and/or BI solutions without your knowledge. It is critical to not ignore these systems as they will likely continue to undermine the integrity and security of your organization’s data. These new cloud-based systems present more risk than the shadow IT systems of yesteryear. These are not a “server box” underneath someone’s desk running Microsoft Access – these solutions now transmit, store, and present data and information outside your organization’s firewall.
- Reach out to these groups and discuss ways to partner for the greater success of the organization. Your goal here is to govern data and maintain control of your organization’s information through better integration and management of these technologies.
- Research and present software options to the lines of business and discuss what features are critical for them. Favor software that features a high level of integration and data security. Even if this software doesn’t have every feature the lines of business want, it will ensure that you have the control and flexibility you need for expansion.
- Think “and” – not “or” – when planning your technology roadmap. Long gone are the days of massive, centralized systems. The millennial workforce has become accustomed to the “there’s an app for that” mentality that drives the “and” mindset. The idea is to use the very best tool for a specific task or set of tasks. Tools like Oracle’s BI Cloud Service (BICS) or Tableau can complement your existing business intelligence and reporting systems.
- Consider the fact that the next version of your on-site software may be cloud-based only! All software vendors at this point have added cloud capabilities to their technology stack and they are slowly sunsetting their on-site portfolio. For some vendors like Oracle, IBM, and others, this process may take years, but eventually there may be no such thing as on-premise software.
Performance Architects defines some terms a little differently than Gartner does, so we wanted to provide definitions of these terms to make sure that our recommendations in this post are clear:
- Business Analytics. Develops new insights and understanding of business performance based on data analysis and statistical methods. Provides access to driver-based information based on nearer-to-real time information to make better informed decisions. Offers capabilities around “unstructured” or “big” data (search plus database). Supplies heavy statistical and predictive modeling capabilities to better connect drivers and outcomes. Many vendors tout business analysis as the “marriage” of their BI/EPM capabilities.
- Data Discovery. Data discovery is the process of searching for patterns in structured and unstructured data sets in order to validate or gain new insights. This technology existed for many years but really became popular in the last few years. Improvements in computing power and software now make this possible for business users.
- Public Cloud. Software hosted on a computer that is accessible to the general public. Users of this software use its front-end capabilities and have no control over the application platform and its back-end components. Public cloud vendors take care of the application infrastructure such as backups, migrations, and upgrades. Users typically need to migrate their data to the remote host where the public cloud software is located.
- Private Cloud. An application environment restricted to a particular company and not available to the general public. Typically the software implemented in a private cloud is similar to an on-site deployment. For example, a company might purchase a license to host a virtual Linux environment from Amazon and installs and configures their application software in this environment. The main objective is to host the software outside of the company’s data center to save on infrastructure costs.
- Hybrid Cloud. A solution where some of the application environment is hosted outside of a company’s infrastructure while another portion remains internal. For instance, a company may elect to host non-sensitive data outside the firewall in a private cloud while maintaining a separate database with sensitive information within the firewall. In other cases, certain public cloud tools may be used by departments and then synchronized with data behind the firewall. The definition is still evolving and companies today are still struggling over the best way to effectively deploy to the cloud without exposing them to data-related risk.
Author: John McGale, Performance Architects