MicroStrategy-2018年智能企业应当关注的八大分析趋势（英文版）-2017-22页

8 Analytics Trends to Watch in 2018 for the Intelligent Enterprise

Core Content

This document outlines eight key analytics trends that enterprise organizations should focus on in 2018 to remain competitive and drive innovation. These trends are based on insights from leading analysts and experts in the field of business intelligence, data analytics, and digital transformation. The goal is to help enterprises adapt to the evolving digital landscape and leverage analytics to transform their operations and customer experiences.

Main Trends and Key Points

Trend 1: AI Will Reshape Analytic and Business Innovation

• AI is expected to significantly enhance analytics and business innovation.
• 25% of firms will use conversational user interfaces alongside point-and-click analytics.
• 20% of firms will use AI for real-time decision-making.
• Big Data environments will evolve or face challenges, with one-third of enterprises moving to a cloud-first strategy.
• Two-thirds of firms will create customer insight centers of excellence, and data engineers will become a highly sought-after role.
• The insights market will become as complex as three-dimensional chess, with 80% of firms relying on insights service providers.

Trend 2: Competition for Data Science and Analytics Talent

• The demand for data science and analytics skills will grow significantly.
• By 2020, there will be 2.7 million job postings for such roles.
• 59% of employers expect data science and analytics skills to be required for finance and accounting managers.
• 51% for marketing and sales managers, 49% for executive leaders, and 48% for operations managers.
• There is a skills gap, with only 23% of graduates in 2021 expected to have these skills.
• Enterprises need to focus on both recruitment and retention of analytics talent.

Trend 3: Convergence of Real-Time and Batch-Based Analytics

• Real-time and batch-based analytics will merge to create more comprehensive insights.
• 80% of retailers believe IoT will drastically change business operations in the next three years.
• 70% of retailers have sensor-related projects underway.
• The analytics market will see vendor convergence, with increased M&A activity.
• Organizations should avoid vendors that are heavily influenced by large tech companies.
• Emerging technologies like AI, IoT, and cloud computing will converge, enabling next-gen analytics and augmented intelligence.

Trend 4: Voice and Natural Language Interfaces Become Mainstream

• Voice and natural language interfaces will be the most significant enhancement to human-computer interaction since the graphical user interface.
• 50% of all searches will be voice searches by 2020.
• Natural language generation will help reduce ambiguity in data interpretation.
• Users will prefer text over maps, making voice and natural language interfaces more valuable.
• These interfaces will enable broader adoption of analytics across the organization.

Trend 5: Convergence in the Analytics Market

• The analytics market will see vendor convergence, emerging technology convergence, and tool convergence.
• M&A activity will reduce the number of vendors, but new ones will emerge.
• Organizations will standardize on a single analytics platform to unify their ecosystem.
• Next-gen analytics will integrate with AI and cloud computing for smart-scaling.
• This will allow for more efficient data governance and fewer tools to manage.

Trend 6: Emergence of Augmented Analytics

• Augmented analytics will transform the analytics landscape by combining AI with human intelligence.
• It will automate data preparation, cleansing, feature engineering, and insight generation.
• Early adopters will benefit from unmatched speed to insight and enhanced competitive advantage.
• Augmented analytics will help in what-if analysis and pattern recognition across large datasets.
• The quality of insights depends on the accuracy and relevance of data.

Trend 7: Machine Learning, AI, and Edge/Video Analytics

• AI and machine learning will be integrated into mainstream software applications.
• Edge analytics will grow due to the rise in connected devices, expected to reach 30 billion by 2020.
• Video analytics will become a key data source, especially with the proliferation of IoT-enabled devices.
• AI-powered video analytics will enable real-time object identification and proactive decision-making.
• Video analytics will be used in retail, law enforcement, and smart city development.

Trend 8: Access vs. Ownership of Analytics and Insight Streams

• 60% of mission-critical data is now outside traditional data warehouses or data lakes.
• Insight streams will become a key monetization opportunity, coming from both obvious and unlikely sources.
• Enterprises should focus on data governance, data preparation, and streaming analytics.
• Infinite ambient orchestration will enable mass personalization and AI-driven smart systems.
• These systems will augment human decisions, predict outcomes, and ensure regulatory compliance.

Key Insights

• The Intelligent Enterprise must be data-driven and agile to stay competitive.
• Digital Darwinism is an ongoing challenge, with only a few years to adapt or risk falling behind.
• AI and machine learning will be central to the future of analytics and business transformation.
• The analytics talent shortage is a growing concern, requiring both recruitment and training strategies.
• Convergence across real-time and batch analytics, as well as technologies and tools, is a defining trend.
• Voice and natural language interfaces will make analytics more accessible and user-friendly.
• Augmented analytics will automate the entire analytics lifecycle, making insights faster and more actionable.
• Edge and video analytics will play a critical role in real-time decision-making and operational efficiency.
• The future of data lies in access rather than ownership, with insight streams becoming a new revenue source.

Summary

These trends highlight the rapid evolution of analytics and its integration with emerging technologies like AI, IoT, and cloud computing. Enterprises must adapt by investing in talent, adopting new tools, and rethinking their data strategies to stay relevant in the digital age. The Intelligent Enterprise will be the one that leverages these trends effectively to drive innovation, improve customer experiences, and achieve sustainable growth.