Modern BI becomes the new normal. In 2016, organizations began the shift to modern BI, the power to perform analytics from the hands of the few to many. We’ve moved “past the tipping point of a more than 10- to 11-year transition away from IT-centric reporting platforms to modern BI and analytics platforms,” according to Gartner’s 2016 Business Intelligence Magic Quadrant. With trusted and scalable platforms, organizations are empowering even non-analysts to explore governed data and collaborate with their findings. In 2017, modern BI will become the top priority for global enterprises, early-stage startups, and everything in between.
FURTHER READING: Modernize using the BI & Analytics Magic Quadrant 1 Collaborative analytics goes from the fringe to the core. Like many things in life, many heads are better than one when it comes to business analytics. And in 2017, collaborative analytics will take center stage as governed data becomes more accessible and cloud technology enables easy sharing. This signals the end of an era in which information flowed in one direction. Gone are the days of sharing data via static PDFs or PowerPoint decks. People will share live, interactive workbooks and data sources to drive business decisions. They’ll build on each other’s work and iterate to answer their own questions. They’ll leverage the cloud and other sharing functionalities like email alerts and subscriptions to stay in touch. And they’ll embed their dashboards within other enterprise applications to reach people where they are. People, regardless of their role, will be empowered to wear many hats, from consuming data on dashboards to performing their own ad hoc analysis, to sharing their findings with others.
FURTHER READING: Tech ‘democratization’ seen fueling analytics boom 2 All data becomes equal. In 2017, the value of data will no longer be tied to its rank or size. It won’t matter whether we’re talking about big data or a simple Excel spreadsheet. What will count is that people can quickly and easily access the data and explore it alongside other types of data to answer business questions and improve outcomes. Over the coming year, BI will shift toward an environment in which people can explore data of all types, shapes, and sizes, and share insights to impact decision-making. Business users won’t have to worry about whether their data is stored in Hadoop, Redshift, or an Excel file. They’ll be able to harness the power of data, no matter how many disparate data sources they have.
FURTHER READING: ‘Big data’ is no longer enough: It’s now all about ‘fast data’ 3 Self-service analytics extends to data prep . While self-service data discovery has become the standard, data prep has remained in the realm of IT and data experts. This will change in 2017. According to Gartner, “The trend toward ease of use and agility that has disrupted the BI and analytics markets is also occurring for data integration.” Common dataprep tasks like data parsing, JSON and HTML imports, and data wrangling will no longer be delegated to specialists. In the near future, everyone will be able to tackle these tasks as part of their analytics flow. This will raise new considerations surrounding data governance, but successful IT groups are already embracing the opportunity. By guiding the transition to self-service data prep, IT can make sure data is accessible to the entire organization and people are working in a safe data environment.
FURTHER READING: Self-service data prep is the next big thing for BI 4 Analytics are everywhere, thanks to embedded BI. Analytics works best when it’s a natural part of people’s workflow. Increasingly, businesses will put analytics where their people work, often in the context of another business application like Salesforce instead of in an app of its own. In 2017, analytics will become pervasive and the market will expect analytics to enrich every business process. This will often put analytics into the hands of people who’ve never before explored data, like store clerks, call-center workers, and truck drivers. Embedded BI will extend the reach of analytics to the point that people may not even realize they’re experiencing it—not unlike the use of predictive analytics to recommend a film on Netflix or music on Pandora.
FURTHER READING: Embedded BI tools need to be put in their proper place 5 IT becomes the data hero. For decades, IT departments remained mired in the endless churn of building reports to support data requests from the business. Now, it’s finally IT’s time to break the cycle and evolve from producer to enabler. IT is at the helm of the transformation to self-service analytics at scale. In high-performing organizations, analytics teams are “working as a trusted partner with the business,” according to Gartner. IT is providing the flexibility and agility the business needs to innovate all while balancing governance, data security, and compliance. And by empowering the organization to make data-driven decisions at the speed of business, IT will emerge as the data hero who helps shape the future of the business.
FURTHER READING: Gartner makes it official: The age of self-service is upon us 6 People start to work with data in more natural ways. The window into our data has come a long way. Technology has replaced scripting and pivot tables with intuitive drag-and-drop interfaces. In 2017, the interface to data will start to feel even more natural, thanks in part to improvements in areas like natural language processing and generation. Natural language interfaces are a new addition to the BI toolbox. They can make data, charts, and dashboards even more accessible by letting people interact with data using natural text and language. This is the “next phase in the evolution from standard reporting to storytelling,” according to Gartner. Though there is healthy skepticism surrounding this new field, it will be an exciting space to watch.
FURTHER READING: Natural language generation: A revolution in business insight 7 The transition to the cloud accelerates. With organizations moving their data to the cloud, the realization that analytics should also live in the cloud will become mainstream. In 2017, data gravity will push businesses to deploy their analytics where their data lives. Cloud data warehouses like Amazon Redshift will continue to be massively popular data destinations, and cloud analytics will become more prevalent as a result. While many organizations will continue to deploy a hybrid architecture of cloud and on-premises solutions, cloud analytics will increasingly represent a faster and more scalable solution.
FURTHER READING: Data gravity pulls to the cloud 8 Advanced analytics becomes more accessible. Business users have grown more data-savvy. Advanced analytics has grown more approachable. In 2017, these two phenomena will converge as advanced analytics becomes the standard for the business user. Advanced analytics will no longer be reserved for data scientists and experts. Business users are already leveraging powerful analytics functions like k-means clustering and forecasting. And in 2017, they’ll continue to expand their analytics skill set.
FURTHER READING: 2016 Advanced and Predictive Analytics Market Study 9 Data literacy becomes a fundamental skill of the future. In 2016, LinkedIn listed business intelligence as one of the hottest skills to get you hired. In 2017, data analytics will become a mandatory core competency for professionals of all types. Much like proficiency in Microsoft Word, Excel, and PowerPoint, competency in analytics will become a staple in the workplace. To meet this need, we’ll see analytics and data programs permeate higher education and K-12 programs. In the workforce, people will expect intuitive BI platforms to drive decision-making at every level.
FURTHER READING: Step aside, coding: Time for analytical thinking in big data 10 About Tableau Tableau helps people transform data into actionable insights. Explore with limitless visual analytics. Build dashboards and perform ad hoc analyses in just a few clicks. Share your work with anyone and make an impact on your business. From global enterprises to early-stage startups and small businesses, people every
