Gazing Into the Data Analytics Crystal Ball

IDC estimates that by 2020, firms will invest more than USD 210 billion in big data and analytics tools and solutions, up from USD 150 billion in 2017. In the same Engines of Insights report, banking followed by healthcare, insurance, securities and investment services, and telecommunications will be the industries that are leading the growth in spending.

Advanced analytics capabilities enable firms to find new growth opportunities, understand customer behaviors and become more agile. What else does the future have in store? To find out, CDOTrends handed Robert Merlicek, Chief Technology Officer of TIBCO Software (Asia Pacific and Japan), a crystal ball.

Citizen Power to Solve Talent Conundrum

More than ever before, data will be spread far and wide across organizations in many different silos and applications. Yet, data scientists are still in high demand and short supply. Also, such people with crucial data insights or business logic continue to leave and take valuable knowledge with them.

The primary challenge for data-driven firms is addressing the lack of necessary vision and talent to lead and implement analytics. Firms need to recognize that organizational transformation is crucial, and the top leadership needs to drive their investments into people and technology. It has to be a cultural change and re-orientation of the organization's values to ensure they imbibe change readiness at the core of everything they do.

Merlicek foretells of firms grooming a select group of employees who are not explicitly trained in math or statistics but who have insightful perspectives on the business problems for which they hope to apply big data solutions.

“These people are being developed into specialists whose expertise sits between that of the data scientists and the business users. We like to call them ‘citizen data scientists,” he said.

The emergence of citizen data scientists will be part of general democratization of data in large organizations. These tools must be broadly available to drive new analytics breakthroughs.

“It is impractical for the analytics to be administered only by a small priesthood of experts. There has to be a role for the kinds of people we used to call ‘power users’ to pose and solve, critical analytics problems,” Merlicek said.

Machine Learning for Predictive Analytics

As data analytics capabilities advance, some firms have started to invest in machine learning. It analyses existing big data stores and derives conclusions that change how the application behaves. Going forward, Merlicek sees that predictive analytics will be the next milestone of machine learning.

“In the early days of big data analytics, organizations were looking back at their data to see what happened and then later they started using their analytics tools to investigate why those things happened. Predictive analytics goes one step further, using the data analytics to predict what will happen in the future,” he said.

Merlicek noted that the combination of advanced analytics, machine learning, and streaming analytics changes how firms integrate, visualize and act on their data and systems “which will bring new differentiated value and opportunities across the business as a whole.”

Prolog: Can We Shape the Future?

The future of analytics is not set. Firms need to look deep within their leadership and IT culture to preempt some of the predictions made above. The secret to success lies in connected intelligence, Merlicek said.

“TIBCO strategy is to Build Digital Business Through Innovation, Integration, and Analytics. A focus has been to fuel digital business by enabling better decisions and faster, smarter actions through the TIBCO Connected Intelligence Cloud. From APIs and systems to devices and people, we interconnect everything, capture data in real time wherever it is, and augment the intelligence of your business through analytical insights.  We are always looking towards the future trends and technologies, some of which include Advanced analytics and Data science, Machine learning, AI and Blockchain.”