Here are the four trends reshaping BI:
Cloud computing has become hugely influential on BI. In fact, BI and analytics are the fastest-growing area of cloud computing, according to Saugatuck Technology, which predicts an 84 percent compound annual growth rate for BI in the cloud over the next two years. Cloud-friendly organizations maintain an edge in their ability to quickly deploy and upgrade services, drive user self-service and more closely align investment with ROI. While many companies have yet to deploy BI in the cloud in a substantive way, it’s clear that cloud has migrated beyond just hype. IT shops previously reluctant to deploy public clouds due to security concerns are now beginning to implement partner or private clouds. Even those with hypersensitive data, such as health care organizations, are integrating cloud architectures and solutions. A recent report from MarketsandMarkets forecasts that cloud adoption among clinical and non-clinical health care organizations will reach $5.4 billion by 2017. Our firm is witnessing this upswing too; health insurer clients are seeing their HIPAA-secure cloud hybrids prove their worth with faster service, dynamic performance and lower cost. The cloud truly has arrived, and if you haven’t opened the door to let it in, your organization may soon be more than a dollar short and a day late.
Big data involves using scale-out parallel data processing and distributed file frameworks to transform and analyze large volumes of structured or unstructured data. Big data is where cloud computing was five years ago – still immature and largely all hype. Case-in-point: While presenting at TDWI’s Cool BI Forum in Chicago earlier this year, I surveyed the 50 people in my session if anyone was doing anything with big data and yielded only one response. Although still immature, big data is arguably a BI game changer. For the past several decades, IT organizations have effectively used data warehousing technologies to create and analyze enterprise views of data, but the time and cost to integrate and manage data has forced organizations to be selective. Consequently, the average data warehouse manages only a fraction of the data required and typically lags business needs. Organizations see big data technologies as a solution to store, transform and analyze data that otherwise would be cost prohibitive to manage in a data warehouse. We now see a growing arsenal of interesting applications of big data in action, such as Rice University’s Storm Risk Calculator, which uses historical and meteorological data to predict the likelihood of a hurricane striking your home (if you live in Houston, that is). The applications for big data are limitless.
NoSQL is cleverly defined for what it is not limited to. For decades, SQL reigned as the most adopted structured programming language for databases. Yet as demand has grown for unstructured data analysis, and as organizations lean toward the cloud IT architectures, NoSQL systems have become the Internet-era database of choice, used by companies such as Amazon, Google and Facebook. What it is: a class of highly scalable, distributed database technologies that move beyond relational database properties and SQL query language prevalent in data warehousing; for this reason, it might be viewed as heretical by some longtime BI/DW practitioners. While big data technologies are oriented to large-scale batch processing, NoSQL has evolved in to support large-scale, real time data access, making NoSQL a solution for backing applications, putting BI results into action.
Mobility. The fundamental shift away from stationary desktop computing to mobile computing is readily seen. In our personal lives, we use smart phones to access information wherever we go. Business users now expect similar ubiquitous network access. Smart phones can provide immediate access to information, but tablets create an even bigger force for change in BI because tablet screen dimensions are so perfectly suited for data visualization and interaction. Gartner asserts mobility to be the most disruptive functionality for BI in 2012, and organizations are designing dashboards with mobile BI in mind, with help from mobile analytics solutions providers.
As these technologies combine and interact with BI, they generate new levels of business utility in many ways. Cloud computing provides the capacity for on-demand compute and storage resources to enable big data, together delivering an unprecedented capability to transform and analyze large volumes of structured and unstructured data. NoSQL provides a platform for real-time access so that Web apps and other applications can use resulting analytic models to enhance customer experience and user productivity. Mobility drives interaction to new scales, reinforcing the demand for real-time business intelligence. Enterprise BI user adoption surveys that fail to take the changing face of BI into account may understate adoption. Cloud computing, mobility and services delivery enables applications to embed and use BI services behind the scenes, so users may not be aware of the extent of BI use. If it hasn’t already happened, over time applications may grow to become the largest enterprise “segment” of BI implementations.
For enterprise architects, the changing face of BI through cloud, big data, NoSQL and mobility innovation may arguably create new coordination challenges. New technologies tend to confuse old boundaries. Nevertheless, these developments present opportunities for BI and information management architects to reimagine BI strategy and increase the visibility and value of BI in the enterprise. While BI continues to be top of mind in executive surveys – and therefore is one of the top areas for IT investments – these revitalizing trends virtually guarantee even greater BI engagement in years to come.