2018智能企业应当关注的八大分析趋势（英文版）

2018 Analytics Trends for the Intelligent Enterprise Summary

Core Content

The document outlines eight key analytics trends that are expected to shape the future of enterprise analytics in 2018, emphasizing the need for businesses to adopt data-driven strategies and technologies to remain competitive. These trends are presented as insights from leading experts in the field, including Boris Evelson, Michele Goetz, David Menninger, Jen Underwood, Ronald van Loon, and Ray Wang.

Main Trends and Key Insights

Trend 1: AI Will Reshape Analytic and Business Innovation

• Key Viewpoint: AI will transform how enterprises use analytics, enabling real-time decision-making and more sophisticated data processing.
• Key Information:
  • 25% of firms will use conversational user interfaces alongside point-and-click analytics.
  • 20% of firms will have AI making decisions and providing real-time instructions.
  • Data lakes will either evolve or decline, with 1/3 of enterprises taking them off life support.
  • 50% of firms will adopt a cloud-first strategy for big data analytics.
  • The need for creating customer insight centers of excellence and hiring data engineers will rise.

Trend 2: Competition for Data Science and Analytics Talent

• Key Viewpoint: The demand for analytics talent is growing rapidly, and organizations must focus on both recruitment and retention.
• Key Information:
  • By 2020, there will be 2.7 million job postings for data science and analytics roles.
  • 59% of employers expect all finance and accounting managers to require these skills by 2020.
  • Only 23% of graduates in 2021 are expected to have these skills.
  • Organizations must invest in internal training and education to build the required talent pipeline.

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

• Key Viewpoint: The analytics market is moving toward convergence, with real-time and batch analytics becoming integrated.
• Key Information:
  • M&A activity in the analytics space will continue, reducing the number of vendors but fostering innovation.
  • Emerging technologies like AI, IoT, and cloud computing will drive convergence.
  • Organizations will standardize on a single analytics platform to integrate various projects and tools.
  • Next-gen analytics will combine with AI and cloud computing for smart-scaling and real-time data processing.

Trend 4: Voice and Natural Language Interfaces Become Mainstream

• Key Viewpoint: Voice and natural language processing will revolutionize the way users interact with analytics systems.
• Key Information:
  • Voice interfaces will be the most significant enhancement to human-computer interaction since the graphical user interface.
  • Natural language generation (NLG) will help reduce ambiguity in data communication.
  • By 2020, 50% of all searches will be voice searches.
  • These interfaces will enable broader adoption of analytics across organizations.

Trend 5: Convergence of Analytics Tools and Platforms

• Key Viewpoint: Organizations will converge their analytics tools and platforms into a unified ecosystem.
• Key Information:
  • Convergence will occur across vendors, technologies, and internal tools.
  • Powerful enterprise software will replace free or cheap web tools as they become more sophisticated.
  • The goal is to reduce the number of tools used, streamline processes, and improve governance and agility.

Trend 6: Emergence of Augmented Analytics

• Key Viewpoint: Augmented analytics will automate and enhance the analytics process, making it more accessible and actionable.
• Key Information:
  • Augmented analytics combines AI with human insight, automating data preparation, feature engineering, and insight generation.
  • It enables faster insights and improved decision-making by handling complex data streams.
  • Early adopters will gain a competitive advantage through speed and automation.

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

• Key Viewpoint: AI and machine learning will become central to analytics, especially in edge computing and video analytics.
• Key Information:
  • AI and ML will be integrated into major software applications, improving efficiency and automation.
  • Edge analytics will grow due to the rise in connected devices (expected to reach 30 billion by 2020).
  • Video analytics, powered by AI and IoT, will be used in retail, law enforcement, and smart cities to provide real-time insights and improve operations.

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

• Key Viewpoint: Organizations must adapt to the increasing availability of data outside traditional sources.
• Key Information:
  • 60% of mission-critical data is now external to traditional data warehouses.
  • Insight streams will become a key source of monetization, drawing from both obvious and unconventional data sources.
  • Companies should focus on building strong data governance, preparation, and agility to leverage these insights effectively.

Key Takeaways

• The Intelligent Enterprise is defined as one that uses data and analytics to anticipate and respond to challenges.
• AI and machine learning are driving major changes in how analytics is performed and used.
• Talent shortage in data science and analytics is a growing concern, requiring both recruitment and training strategies.
• Real-time and batch analytics are converging, enabling more comprehensive and actionable insights.
• Voice and natural language interfaces are becoming more common, improving accessibility and user engagement.
• Augmented analytics is transforming the analytics landscape by automating complex tasks and enhancing decision-making.
• Edge and video analytics are expanding due to the growth of IoT and connected devices.
• Data access is becoming more critical than ownership, with insight streams from diverse sources enabling new business opportunities.

Conclusion

The 2018 analytics trends highlight the importance of embracing AI, data science, and real-time analytics to stay competitive. Organizations must adapt their strategies, invest in talent, and integrate new technologies to create a data-driven future. The Intelligent Enterprise is not just a vision, but a reality that is rapidly approaching.