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Factors Accounting For The Evolution Of BI

by Deepak Ghodke, - Senior Director-Strategic Sales, Tableau India February-2019

In 2016, self-service analytics took over the enterprise. IT began leveraging technologies to scale analytics programs as business users collaborated with their data. IT and the business partnered to maximize the impact of their data.

In 2017, this culture of self-service analytics will continue to spread and become a workplace norm. And the tools that support this evolution will become commonplace.

1. Modern BI becomes the norm. Many organizations have already embraced modern BI, moving analytics from the hands of the few to many. We’ve moved past the tipping point toward modern BI, according to Gartner. And we’ll continue to see organizations of all sizes democratize analytics, leverage trusted and scalable platforms to encourage people to uncover insights in their data.

2. Collaborative analytics goes from the fringe to the core. Thanks to easy access to governed data and easy sharing via cloud technology, information no longer flows in one direction. Gone are the days of data-sharing via PDFs or PowerPoints. In 2017, people will share live, interactive workbooks and data sources. They’ll stay connected via email alerts and subscriptions. They’ll share findings, build on each other’s work, and move the business forward.

3. All data becomes equal. In 2017, the value of data will no longer be tied to its rank or size. 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. Business users won’t have to worry about whether their data is stored in Hadoop, Redshift, or an Excel file. They’ll have a full-picture view of their analytics, no matter how many disparate data sources they have.

4. 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. Common data-prep tasks like data parsing, JSON and HTML imports, and cross-database joins will no longer be delegated to specialists. A report from IDC indicated that spending in APAC on self-service visual discovery and data preparation market will grow 250 percent faster than traditional IT-controlled tools for similar functionality.In the near future, non-analysts will be able to tackle these tasks as part of their analytics flow.

5. Analytics is everywhere, thanks to embedded BI. Analytics works best when it’s a natural part of people’s workflow. 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 consumed data, like store clerks, call-center workers, and truck drivers.

6. IT becomes the data hero. 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. IT is providing the flexibility and agility the business needs to innovate all while balancing governance and data security. 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.

7. People start to work with data in more natural ways. 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. A new addition to the BI toolbox, natural language interfaces can make data, charts, and dashboards even more accessible by letting people interact with data using natural text and language. Though there is healthy skepticism surrounding this new field, it will be an exciting space to watch.

8. The transition to the cloud accelerates. In 2017, data gravity will push businesses to deploy their analytics where their data lives. While many organizations will continue to deploy a hybrid architecture of cloud and on-premise solutions, cloud analytics will increasingly represent a faster and more scalable solution.

9. Advanced analytics becomes more accessible. Business users have grown more data-savvy. Advanced analytics has grown more approachable. Business users are already leveraging powerful analytics functions like k-means clustering and forecasting. And in 2017, advanced analytics becomes the standard for the
business user.

10. 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 and ranked statistical analysis and data mining as the Number 5 top skills in India.In 2017, data analytics will become a mandatory core competency for professionals of all types. And people will expect intuitive BI platforms to drive decision-making at every level.