Slideshow 5 top trends driving analytics and BI strategy

Published
  • May 16 2018, 6:16am EDT
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5 strategic planning assumptions about the next five years

Gartner Research has issued its new study on the top trends driving data analytics and business intelligence, “Predicts 2018: Analytics and BI Strategy – Strategic Planning Assumptions.” The study includes the combined predictions of Gartner analysts Gareth Herschel, Alexander Linden, Rita L. Sallam, Svetlana Sicular, Jim Hare, Jorgen Heizenberg, Erick Brethenoux and Douglas Laney.

Automated ‘Most Needed’ Insights

By 2021, 75% of prebuilt reports will be replaced with or augmented by automated insights delivered on a "most needed" basis, according to Gartner analysts Erick Brethenoux and Rita Sallam.

Their findings:

  • Report stacks and static information delivery are of limited use for decision making in a digital business — competition for management attention and business velocity have rendered traditional reports obsolete.
  • Predetermined report formats are increasingly being replaced by a set of more intuitive interaction mechanisms such as conversational analytics.
  • Citizen data scientists (CDSs) and business users are being equipped with increasingly "smart" discovery techniques and selective warning capabilities, fueling the augmented analytics trend.

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Adaptive Device Interactions

By 2022, every personalized interaction between users and applications or devices will be adaptive, say Gartner analysts Erick Brethenoux and Doug Laney.

Their findings:

· Using data gathered by our devices, the interactions are often personalized to ensure the needs of each specific user are met.

· Users, both professionals and consumers, are getting buzzed, beeped, vibrated and flashed to a point of attention numbness.

· AI techniques are starting to protect users from attention-grabbing abusive analytics capabilities. The adaptability of solutions and devices should adhere to "calm computing" principles, where the technology requires the smallest amount of a user's attention.

Real-time Analysis & Customer Interactions

By 2022, 30% of customer interactions will be influenced by real-time location analysis, up from 4% in 2017, says Gartner analyst Jim Hare.

His findings:

· Organizations are increasingly using more real-time location analytics, because of the pressure to increase the speed and accuracy of business processes as well as to improve customer experiences. Real-time location data is fueling innovation in services such as Uber and Waze, which are particularly location-aware.

· The adoption of smartphones and IoT devices is generating location data that can be used to personalize interactions and improve experience. Penetration of smartphones in the U.S. exceeded 80% in 2016, 2 and is expected to exceed 40% worldwide by 2022. 3

· Today, about 29% of organizations are actively using geospatial and location intelligence capabilities (see "Survey Analysis: BI and Analytics Spending Intentions, 2017" ). However, we estimate that only about 4% are performing location analytics in real time.

Deep Learning Replaces Machine Learning

By 2023, artificial intelligence and deep-learning techniques will replace traditional machine learning techniques as the most common approach for new applications of data science, according to Gartner analysts Gareth Herschel, Alexander Linden and Svetlana Sicular.

Their findings:

· One of the most significant barriers to organizational adoption of analytics is trust in the analysis. The need for trust takes several forms, from statistical accuracy to ethical suitability.

· As business problems become more complicated, the sophistication of the analysis required to solve them continues to increase. Also, the level of knowledge required to understand the analysis becomes more sophisticated (albeit at a lower level), placing a continual brake on the adoption of more sophisticated analysis.

· As a decision maker's personal experience with the use of deep-learning techniques increases, the reluctance to trust analysis that is not understood decreases.

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Data Scientist Shortage No Longer An Obstacle

By 2024, a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations, according to Gartner analysts Gareth Herschel, Rita L. Sallam, Svetlana Sicular, Jim Hare, Jorgen Heizenberg and Doug Laney.

Their findings:

· The role of data scientist is one of the most in-demand jobs in the analytics space.

· The need for data-science-generated insights will continue to grow within organizations and across multiple industries.

· Most organizations are facing a scarcity of data scientists to deliver the business benefits they are expecting.

· Solving the problem of the shortage of data scientists is a significant opportunity that multiple organizations are pursuing from different perspectives.