DATA science is no longer just about statistics and data analytics. Today, it is an integral part of running a business. While business intelligence (BI) tools traditionally required big investment in technology and human capital, today’s innovations empower even small businesses to access the tools and capabilities that can give their organizations an edge, in terms of making data-driven decisions.
BI is shifting away from IT service providers toward a more user-driven approach, says tech research and advisory company, Gartner, in a 2015 study. By 2017, most businesses around the world will have access to self-service tools that can help prepare, analyze and synthesize data for their BI needs. This means data discovery tools will already incorporate smart capabilities that will enable organizations to access, profile, prepare, integrate, curate, model and enrich data in order to make better decisions.
In the Asia Pacific region, this trend goes beyond private organizations. Government agencies and local government units are also deploying BI and big data initiatives in order to better manage their resources and constituencies. For example, the Smart Nation initiative in Singapore is meant to revitalize the economy with technology-driven practices. The same goes for Microsoft’s CityNext projects, which provides enterprise-grade productivity and BI solutions for governments.
The key trend here is that technology companies are now providing businesses the ability to enhance their BI capabilities through simplified platforms. This involves third party providers or even data science professionals giving way to self-service BI solutions that enable even less-savvy technical users to manage their own data through straightforward interfaces.
In fact, modern BI solutions can provide drag-and-drop interfaces similar to managing documents or spreadsheets, which can dramatically simplify analytics. This means that everyone from analysts to C-level executives can take advantage of data in making crucial decisions.
Single-stack BI platforms
BI traditionally involved various applications, data sources and methodologies, which make up an organization’s BI stack. Modern solutions would involve single-stack capabilities, meaning that a single application will be able to crunch huge amounts of data in and by itself, without the need for complex data preparation and modeling.
In addition, new solutions use innovations like in-memory and in-chip technologies, which make crunching data significantly faster even on consumer-grade computers. This means businesses no longer need to acquire specialized servers or hardware just to crunch their data in-house.
Such innovations enable professionals to accomplish complex analytics even on a laptop computer, even pulling out data from the Internet or from several databases on the fly. Such is the power of modern BI solutions.
Hybrid cloud solutions
BI-as-a-Service is also a growing industry, which means businesses can take advantage of cloud-based solutions that offer plug-and-play capability with their own data or infrastructure. This frees up an organization from having to invest in costly infrastructure.
Cloud-based BI solutions provide the same cost-efficiency of most other cloud computing endeavors, as it reduces the need to invest in software and hardware. Organizations are also freed from having to invest in costly maintenance and updates.
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A few drawbacks include limited control over data modeling capabilities, as well as the need for high bandwidth capabilities to satisfy huge data transfer requirements. However, cloud solutions are most favorable for organizations looking to enhance their capabilities without the cost associated with capital expenditure.
Of course, BI is not a one-size-fits-all concern. Organizations will need to evaluate their needs, in order to find the best approach and execution model. This will highly depend on scale, IT capabilities and budget. With accessible solutions that offer a myriad of options in terms of data source, hosting and management, there is no reason for businesses to be left in the dark with regard to managing their data and data strategy.