2018商业智能BI趋势（英文版）-2mb

2018 BI Trends Summary

Core Content

The document outlines 11 key trends in Business Intelligence (BI) for 2018, focusing on the concept of de-silofication — the process of breaking down data, people, and ideas from their silos to create a more connected and agile analytics environment. These trends are designed to help organizations adapt to the analytics economy while addressing challenges such as privacy, data governance, and the need for broader data literacy.

Main Trends and Key Points

1. Data Literacy Gains Priority

• Changing BI: Data literacy is becoming a critical competency across organizations and society.
• Key Insight: Gartner predicts 80% of organizations will invest in data literacy by 2020.
• Action: Companies will offer structured programs to enhance data literacy, and employees are willing to invest more time in improving their skills.

2. Hybrid Multi-Cloud Environments

• Changing BI: Cloud services are expanding rapidly, but data may need to be moved out of the cloud for compliance, security, and performance.
• Key Insight: Hybrid and multi-cloud architectures will become the standard.
• Action: Learn to evaluate cloud analytics vendors by asking key questions about their support for hybrid environments.

3. Data Gets Edgy

• Changing BI: More data processing will occur at the edge, especially with IoT and mobile applications.
• Key Insight: By 2019, 40% of IoT data will be processed at the edge; by 2022, 75% of enterprise data will be processed outside traditional data centers.
• Action: Understand the value of edge computing and how it enables faster, more secure data analysis.

4. Convergence of Big Data, Data Discovery, and Data Science

• Changing BI: These areas will increasingly overlap, allowing broader access to insights.
• Key Insight: Machine intelligence and engine-to-engine integration will help users explore complex data sets.
• Action: Explore tools like On Demand App Generation to manage Big Data effectively.

5. Data Catalogs for Self-Service

• Changing BI: Data catalogs will evolve to support self-service data preparation and analysis.
• Key Insight: Integration with data preparation and analysis tools will make data catalogs accessible to a wider audience.
• Action: Learn about the benefits of self-service models and how to implement them.

6. Interoperability and APIs Take Center Stage

• Changing BI: APIs will be essential for connecting distributed systems and enabling seamless data flow.
• Key Insight: Analytics platforms must be open and interoperable to support modern workflows.
• Action: Explore how open APIs can enhance your BI platform's capabilities.

7. Blockchain Drives Experimental Applications

• Changing BI: Blockchain technology will expand beyond cryptocurrencies into data management and analytics.
• Key Insight: Blockchain can help verify data lineage and authenticity.
• Action: Encourage developers to experiment with blockchain-based data solutions.

8. Analytics Become Conversational

• Changing BI: Conversational analytics will simplify data interaction through natural language and voice.
• Key Insight: Integration with virtual assistants and chatbots will enable more intuitive data exploration.
• Action: Try conversational analytics tools like Qlik® Bot to experience the shift.

9. Reporting Gets Contextualized

• Changing BI: Reports will be more context-aware, delivering insights directly to users in their work environment.
• Key Insight: This approach empowers non-analysts with relevant, timely information.
• Action: Learn how search-based interfaces can improve productivity and efficiency.

10. Analytics Become Immersive

• Changing BI: Immersive analytics, including VR and AR, will enhance user engagement.
• Key Insight: Immersive experiences will drive more users to interact with data through storytelling and collaboration.
• Action: Discover how immersive analytics can transform data visualization and user interaction.

11. Augmented Intelligence Transforms Users

• Changing BI: Augmented intelligence will blend AI with traditional BI tools, making data more accessible and useful.
• Key Insight: It shifts users from passive consumers to active participants and facilitators in the data ecosystem.
• Action: Learn how to implement augmented intelligence in your organization.

Key Information

• Data Literacy: A major priority, with 50% of workers struggling to distinguish data truths from manipulations.
• Privacy and Governance: Increasingly important as data becomes more fragmented and accessible.
• Technology Integration: The need for open platforms, APIs, and interoperability is growing.
• Edge Computing: Enables faster, more secure data processing, especially for IoT and mobile use cases.
• Conversational and Immersive Analytics: Will make data more accessible and engaging for a broader audience.

Conclusion

The 2018 BI trends emphasize the importance of breaking down silos, enhancing data literacy, and leveraging new technologies to create a more connected, secure, and innovative analytics environment. Organizations that adapt to these trends will be better positioned to thrive in the analytics economy.