2018商业智能BI趋势（英文版）_18页_2mb

11 BI TRENDS FOR 2018 Summary

Core Content

This document outlines 11 emerging trends in Business Intelligence (BI) that are expected to shape the analytics landscape in 2018. These trends reflect the evolving needs of organizations in a data-driven world, emphasizing the importance of data literacy, hybrid cloud environments, edge computing, and the integration of advanced technologies like AI and blockchain.

Main Trends and Key Points

1. Data Literacy Gains Priority

• Data literacy is becoming a critical skill for both individuals and organizations.
• Gartner predicts that by 2020, 80% of organizations will develop data literacy programs.
• Only 20% of workers are currently data literate, but those who are show better performance.
• 65% of workers are open to improving their data skills with the right support.

2. Hybrid Multi-Cloud Environments Emerge

• Cloud services are increasing rapidly, but not all data can stay in the cloud.
• Regulatory, security, cost, and performance concerns will push data out of the cloud.
• Edge computing will lead to fragmented data and application domains.
• Organizations will need analytical architectures that support multi-cloud, multi-platform, and hybrid environments.

3. Data Gets Edgy

• More data processing will occur at the edge of the network, especially for IoT, mobile, and immersive analytics.
• Edge computing is beneficial for latency, bandwidth, autonomy, and privacy.
• By 2019, 40% of IoT data will be processed at the edge.
• By 2022, 75% of enterprise data will be created and processed outside traditional data centers.

4. Big Data, Data Discovery, and Data Science Converge

• These areas are becoming more interconnected, enabling broader data exploration.
• Machine intelligence, big data indexing, and engine-to-engine integration are driving this convergence.
• Tools like On Demand App Generation allow users to manage big data more effectively.

5. Data Catalogs Enable Self-Service

• Data catalogs are becoming more accessible and integrated into data preparation and analysis.
• They help users combine corporate data, data lakes, and external data as a service.
• The goal is to empower a broader audience with data governance and discovery capabilities.

6. Interoperability and APIs Take Center Stage

• Organizations are moving away from monolithic solutions and toward modular, interoperable systems.
• APIs are crucial for enabling seamless communication between different software systems.
• Analytics will become more embedded in workflows, leading to data-driven applications.

7. Blockchain Hype Drives Innovation Beyond Cryptocurrencies

• Blockchain and peer-to-peer technologies are influencing data management and analytics.
• These technologies offer new ways to verify data lineage and authenticity.
• 2018 will see experimental applications in analytics and data governance.

8. Analytics Become Conversational

• Conversational analytics simplify data exploration and storytelling.
• Natural language queries, voice, and search will become more prevalent.
• Virtual assistants and chatbots will enhance user interaction through API integration.

9. Reporting Becomes Contextualized

• Reporting will shift from traditional dashboards to more contextual and personalized formats.
• Information will be delivered directly to users in their work environment.
• This trend empowers a wider audience with relevant data at the right time and place.

10. Analytics Become Immersive

• Immersive analytics will use virtual and augmented reality to engage users.
• These experiences can also take other forms, such as sensorial and social interactions.
• Better user interfaces and storytelling techniques will drive adoption.

11. Augmented Intelligence Transforms Users into Participants

• Augmented intelligence combines AI with traditional BI tools to enhance data utility.
• It enables a collaborative ecosystem between humans and machine intelligence.
• The goal is to make data more accessible and useful through human-machine interaction.

Key Takeaways

• Data literacy is a priority for both organizations and individuals.
• Hybrid multi-cloud and edge computing are reshaping data architecture and processing.
• Interoperability through APIs is essential for modern BI platforms.
• Blockchain offers new possibilities for data integrity and governance.
• Conversational and immersive analytics are making data more accessible and engaging.
• Augmented intelligence is the future of data analysis, enabling broader participation and innovation.

Conclusion

The 2018 BI trends highlight the shift toward more open, integrated, and user-centric analytics. Organizations must adapt to these changes by investing in data literacy, leveraging hybrid environments, and adopting new technologies to stay competitive in the analytics economy.