Top 10 BI trends for 2016
By JY Pook December 28, 2015
- Greater use of self-service tools, cloud analytics, and visualisation
- More centres will be set up to inculcate the data-driven culture
WE saw a year of significant transformation in the world of business intelligence (BI) in 2015. More organisations opened up to the idea of leveraging data to make discoveries, and many began to put the power of data analytics into the hands of their rank-and-file employees.
In Singapore, the Smart Nation initiative took on momentum, and so did the Infocomm Media 2025 plan, which is designed to bring about a new economy that is now more fuelled by technology than ever before.
BI norms are evolving, leading to a cultural change at some workplaces. This change is driven not only by fast-moving technology, but also by new (and easier to learn) tools that can help us get more value out of our data.
In 2016, we expect to see an even deeper cultural shift in this regard as data will increasingly stand at the core of decision making, not just for businesses, but also for the community at large.
At the beginning of each year, we start a conversation about what we expect to see in the industry. That discussion drives our list of the top BI trends. The following is our list for 2016.
2 become 1: Governance and self-service analytics
Data governance and self-service analytics used to be considered natural enemies to each other. You either have one or the other, never together.
In 2016, we believe the war will be over, and the cultural gap between business and technology is going to close up even more.
Earlier this year, Gartner noted that the rise of data discovery, access to multi-structured data, data preparation tools and smart capabilities will further democratise access to analytics and stress the need for governance.
Gartner also predicted that by 2017, most business users and analysts in organisations will have access to self-service tools to prepare data for analysis.
Despite the trend of data analytics, people are more likely to dig into their data when they have centralised, clean, and fast data sources, and when they know that someone (IT) is looking out for security and performance.
As such, organisations are learning that data governance, when done right and supported by IT, can help nurture a culture of analytics and meet the needs of the business.
Visual analytics as the common language
Data is changing the conversation in boardrooms, the shop floor and beyond. People are visualising their data to explore questions, uncover insights, and share stories with both data experts and non-experts alike.
As data usage grows, even more people will turn to data with both professional and personal questions.
We have seen a variety of users incorporating visual analytics tools in their daily lives, from business users, to students and homemakers.
For example, Ngee Ann Polytechnic, one of Singapore’s leading institutions of higher learning, has embedded data analytics into its curriculum for both teachers and students. In fact, lecturers have also started using visual analytics tools in their classrooms, encouraging students to be more comfortable and familiar with working with data.
More and more, visual analytics will serve as the common language, empowering people to reach insights quickly, collaborate meaningfully, and build a data-smart community.
The data product chain is a democracy
Self-service analytics tools have changed people’s expectations for good. In 2016, people will seek empowerment across the data continuum.
Driving a large part of this change will be the millennials who are at the age of entering into the workforce – millennials are predicted to make up 50% of the global workforce by 2020, according to PwC (PDF).
Millennial workers will expect to have easy access to data whether they are in the office or on the road. They will want to explore the data themselves to make their own discoveries on the fly.
That is 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.
This democratisation will allow people to respond quickly to shifting priorities.
Data integration gets exciting
These days, many companies want agile analytics. They want to get the right data to the right people, and quickly.
This is no small challenge, because that data normally lives in many different places.
Working across data sources can be tedious, impossible, or both. In 2016, we will see a lot of new players in the data integration space. Companies will stop trying to gather every byte of data to have them stored in the same place as more sophisticated tools for data integration emerge.
Data explorers will connect to each data set where it lives and combine, blend, or join with more agile tools and methods.
Advanced analytics not just for analysts
Non-analysts across the organisation are becoming more sophisticated. They have come to expect more than a chart on top of their data.
In a recent study, Gartner noted that business and IT leaders are boosting investment in advanced analytics that address business problems and provide business benefits far beyond conventional BI.
Business users now want a deeper, more meaningful analytics experience. Organisations will adopt platforms that let users apply statistics, ask a series of questions, and stay in the flow of their analysis.
Data and analytics will fly to the cloud
In 2015, people who work with data began embracing the cloud. They realised that putting data in the cloud is easy and highly scalable. They also saw that cloud analytics allows them to be agile.
We expect more people to transition to the cloud in the coming year thanks, in part, to tools that help them consume web data.
Early adopters are already learning from this data, and others are realising they should.
And more companies will use cloud analytics to analyse more data, faster. They will come to rely on it just like any other critical enterprise system.
‘Schooled’ in data analytics
One main focus of Singapore’s Smart Nation initiative is to provide more open data to the public. With this, an increasing number of organisations will establish a Centre of Excellence to foster the adoption of self-service analytics.
These centres will play a critical role in implementing a data-driven culture. Through enablement programmes like online forums and one-on-one training, the centres will empower even non-experts to incorporate data into their decision-making.
Singapore’s IDA Hive is a good public sector example of this. This government facility is focused on ensuring that the digital experiences delivered to citizens are useful, relevant and easy to use.
Aimed at leveraging on data analytics to gain better insights into the needs of users to improve their digital government transaction experiences, the unit also doubles up as a consultancy, assisting agencies on the development of new services or enhancement of existing ones.
The independence of mobile analytics
Mobile analytics has grown up and moved out. It is no longer just an interface to legacy business intelligence products.
In 2015, products with a fluid, mobile-first experience began to emerge. Working with data out on the road will be less of a chore and a more dynamic part of the analytics process.
Digging deeper into IoT data
The Internet of Things (IoT) is poised to become even more prevalent in 2016. It seems that everything will have sensors that send information back to the mothership, be it fitness tracking wearables, home security systems or industrial machines.
Just think of all the data that mobile devices are already generating around the clock. As the volume of IoT data grows, so does the potential for insights.
Companies will look for tools that allow users to explore the data, then share their findings in a secure, governed, and interactive way.
The rise of new technologies
New technologies designed for the BI ecosystem are constantly emerging. As these go to market, we will see gaps that need to be filled.
Hadoop accelerators, NoSQL data integration, IoT data integration, improved social media: Each of these present an opportunity for businesses.
In 2016, we will see the rise of the gap fillers, leading to a market consolidation. Organisations will continue to shift away from single solutions and embrace an open and flexible stack that includes these new technologies.
JY Pook is Asia Pacific vice president at Tableau Software.
Data stories … at home, in school, and within the enterprise
Singapore’s Hive to bring data science goodness to the people
Seven facts about data-driven cultures in APAC
For more technology news and the latest updates, follow us on Twitter, LinkedIn or Like us on Facebook.