Posted by Karen
February 3, 2016
What does the future hold for BI in 2016 and beyond? Here’s a look at 6 high impact trends that are changing the face of business intelligence and will give you an eye-opening look at what businesses should be leveraging in 2016. Continuing a pattern from previous years, 2016 will see the ongoing evolution of existing trends and usher in new concepts, as well.
1. Proliferation of Self-Service BI
self serve biI have been closely following and blogging about major trends in business intelligence since 2013, and have concluded that the BI trend with the greatest impact over this time has arguably been the increasing prevalence of self-service business intelligence. All signs indicate that this trend will continue in 2016, and we’ll see an even greater shift to businesses leveraging self-service analytics data.
Self- service BI, an approach to data analytics that enables business users to access and work with corporate information with minimal or no IT department involvement, empowers business professionals to make decisions based on their own analyses, instead of forcing them to use only the data and reports available from a larger BI system. That’s why the demand for self-service data preparation tools and even self-service data warehouses will grow as a natural extension of self-service analytics.
Visual-data-discovery tools have become synonymous with self-service BI and are also growing in popularity. Vesset, IDC’s Program Vice President for Business Analytics and Big Data, projects that spending on self-service visual discovery and data preparation tools will grow 2.5x faster in 2016 than traditional IT-controlled tools, and said it will necessitate a fundamental IT culture change.
As the use of self-serve BI evolves, so too will data governance. Contrary to a long held belief, self-service analytics and governance are not at odds.
Organizations are embracing data governance, and business professionals are more likely to dig into their data when they have centralized, clean, and fast data sources, and when they know that someone (IT) is looking out for security and performance.2
Governed data enables users to explore data and discover valuable business insights instead of wondering whether the data is accurate. It facilitates more efficient, accurate and timely decisions.
It’s the age of “Big Data” and companies want agile analytics – they want to get the right data to the right people, and quickly! But this has been difficult for many businesses to deliver because their data is spread across multiple sources, formats, internal and external locations.
Frustrated by their limited ability to fulfill data requirements, businesses will focus their investment and efforts on data integration. Rather than struggling to collect all data in one place, there will be a trend to connect to each data set where it resides and combine, blend, or join different data sets with more agile tools and methods.3
This trend is sometimes referred to as data virtualization – integration of data from disparate sources, locations and formats, without replicating the data, to create a single “virtual” data layer that delivers unified data services to support multiple applications and users. The result is faster access to all data, less replication and cost, more agility to change.4
In 2016 there will be even greater emphasis on data visualization tools that create more powerful graphics and facilitate more advanced analytics such as those that let users apply statistics, ask a series of questions, and stay in the flow of their analysis. As a Tableau partner, we’re pleased that Tableau is leading this trend with expanded visual analytics capability in the current version, Tableau 9.2
“Big data” has become so overwhelming and complex that even data scientists don’t initially know what they are looking for when they begin to analyze it. For this reason, visual data discovery is surging in popularity among analysts as it’s the easiest and fastest way to explore and experiment with the data, to find patterns and relationships that will lead to meaningful business insight.
Explorational visual analytics is based on experimentation, creativity and predefined questions; visualizations are often created ad hoc to check different alternatives.4 Similar to visual data discovery tools, there will be growing interest in explorational visual analytics tools that allow analysts to dig into “big data” with the use of visualizations and best practices in visual perception exploration.
Cloud based BI will gain momentum in 2016 as more companies jump on the bandwagon realizing that they can be more agile and analyze more data, faster with cloud analytics. The proliferation of cloud-based tools available on the market is also driving the move to the cloud. IDC’s Dan Vesset projects that 2016 spending on cloud-based BI technology will grow 4.5x faster than spending for on-premises solutions.1
Rita Sallam, a Research Vice President at Gartner who focuses on BI and analytics, predicts, “Interest in cloud BI deployments for new projects will finally increase due to shift in data gravity, perception of value, as well as the entrance of major players such as Microsoft and Amazon.” Sallam adds, “Until now, cloud adoption has mostly been limited to organizations with most of their data in the cloud and/or to lines of business.”1
Internet of Things (IoT): the interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data (Oxford Dictionaries).
Although Internet of Things data has been available for years, 2016 will see more possibilities to actually make use of the data.
The IoT will create new opportunities for data visualization and real-time analysis, and it will become accessible to a broader group of users.
“The 10 most popular IoT Applications”, a study conducted by IoT Analytics, ranks smart homes, wearables and smart cities as the most popular applications, and includes smart grids, industrial internet, connected car, connected health, smart retail, smart supply chain, and smart farming in the top 10.
Gartner, Inc. forecasts that 6.4 billion connected things will be in use worldwide in 2016, up 30 percent from 2015, and will reach 20.8 billion by 2020. In 2016, 5.5 million new things will get connected every day. The amount of IoT data these connected things will create is mind boggling!
This rapidly expanding volume of IoT data will in turn lead to increased demand for BI tools that enable users to leverage larger sets of unstructured data coming from multiple connected sources, explore the data, and share insights in a secure and collaborative way.Sources:
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