The practice of data analytics, and thus the applications that facilitate it, is at a critical point. The benefits of data have been observed in spades, as virtually every industry has organizations hopping on the data bandwagon. The pain points and potential for organizational derailment have also been explored and bandied about. In the face of what we know about information analysis, we also know that there is a lot we don't really know. At least, not yet. It would be charitable to call the point that data analysis and enterprise analytics software development diverges a fork in the road - in reality, it's like the "garden of forking paths" explored in legendary Argentinean writer Jorge Luis Borges' story of the same name - a veritable labyrinth of potential highways and byways to travel.
Of course, business still has to get done. While there is time for exploration and experimentation, most of it has to lead, at least indirectly, to the bottom line. Business leaders aren't about to grant ad hoc reporters and data scientists leave to go foraging completely off the map. This can lead to wasted resources, but also contributes to the increased fragmentation of the enterprise - a phenomena contrary to the direction that most innovative companies are moving in. Many organizations have realized that it can be much harder, especially in the age of abundant data, to work productively in silos. They're moving toward collaboration and centralization. Ad hoc reporting tools are one of the best ways for organizations to do this. It puts data and querying responsibilities in the hands of regular employees, who then develop insights from their department's perspective that can be viewed and understood across the whole company by other users versed in the same applications.
Defragmentation Through Development
Software development tools need to reflect the collaborative and centralizing forces at play in today's enterprise. SmartData Collective contributor Julie Hunt discussed the importance of positioning a centralized data discovery and analysis strategy as a cornerstone of defragmented enterprise strategizing.
"Centralizing analytics can eliminate redundant effort to glean intelligence from data sources, while reducing effort and cost," Hunt wrote. "Often departments in midsized organizations rely too much on their own silos of data and don't include a wide variety of data sources. Centralizing advanced analytics should dynamically work to eliminate data silos in the organization and bring different perspective into the formulation of analytical models and a wider breadth of benefit to the overall organization."
Navigating the forks in the road
The labyrinth metaphor for data analysis, querying and ad hoc reporting in the face of the volume and velocity of information is an apt one. Users have to make split-second decisions about the paths they will pursue, especially if the company is aiming to include real-time decision making in their analytics efforts. This reality is driving business investment in report designer applications and informing procurement decisions for programming frameworks that can support their quick deployment. In a recent interview with Forbes, business intelligence expert Marius Moscovici spoke about the current conundrum companies face if they want to develop reporting tools that lead to business growth.
"[N]o human being can consume information at the volume and rate that BI systems spit it out," Moscovici told Forbes. "Users are drowning in dashboards. The vast majority of regular business people give up on BI systems shortly after adoption. We're heading into what I call BI 3.0, the post-hype era, where leaders are scrutinizing the ROI of their business intelligence systems and entrepreneurs are starting to build BI that the majority of users will actually adopt."