Evolution of Business Intelligence

Summary

The video highlights the evolution of business intelligence and analytics, illustrating how technologies like self-service visualization and data discovery tools (e.g., Tableau, Qlik) have transformed the traditional BI landscape. The traditional method of complex ETL processes and fixed data models has evolved into a more agile, self-service environment. This shift allows business users to directly access and analyze data, reducing IT bottlenecks and fostering collaboration. As a result, both IT and business teams are more productive and innovative, with greater flexibility in addressing analytics needs.

Takeaways

• 😀 Traditional business intelligence relied on a complex ETL process that fed data into a fixed data model and warehouse.
• 😀 In the past, data analysis was static, often leading people to export data to Excel for manual work and reporting.
• 😀 Self-service visualization tools like Tableau and Qlik have revolutionized BI by allowing business users to interact with data directly.
• 😀 IT's role has shifted from managing report creation to focusing on governance, enabling more agile and responsive business operations.
• 😀 The bottleneck in traditional BI was caused by IT needing to fulfill requests for data reports. This has shifted with self-service tools.
• 😀 Self-service data preparation has become a key function, empowering business users to prepare and analyze data on their own.
• 😀 The evolution of BI is creating a more collaborative environment between business users and IT, resulting in a faster decision-making process.
• 😀 Data sources are now exposed directly to business users, enabling them to ask more dynamic and complex questions.
• 😀 Business users now have access to the same data as analysts, making it easier to answer their own analytical questions.
• 😀 Advanced analytics is now becoming more of a self-service function, reducing reliance on IT to answer business questions.

Q & A

What was the traditional technology stack in business intelligence before the evolution described in the script?

The traditional technology stack involved source systems in silos, an ETL layer, a pre-designed fixed data model, and a data warehouse. Advanced analytics were built on top of this, with the end result being static reports and dashboards reflecting KPIs and ad hoc reporting.

How has business intelligence and analytics evolved over time?

The evolution has led to the rise of self-service visualization and data discovery tools like Tableau and Qlik, which allow business users to interact with data independently of IT, creating a more agile and interactive environment.

What was the role of IT in the traditional business intelligence system?

In the traditional system, IT managed the entire data process, from data extraction to report generation. Business users would request specific reports from IT, who would then create them manually.

What is the role of self-service visualization in the modern business intelligence landscape?

Self-service visualization empowers business users to explore data independently using tools like Tableau and Qlik, reducing the reliance on IT and allowing for more dynamic and interactive data analysis.

What caused IT to become overwhelmed in the traditional business intelligence model?

IT became overwhelmed because the business side often made requests for specific reports, which resulted in a bottleneck where IT had to generate custom reports manually, slowing down the process.

What is 'self-service data preparation' and how does it differ from the traditional approach?

Self-service data preparation allows business users to handle their own data transformation and preparation, freeing IT from these tasks. In contrast, the traditional approach required IT to manage the data preparation process for reporting.

What is the significance of exposing all data sources to business users in the modern model?

Exposing all data sources to business users ensures they can access the necessary data directly for their analysis, facilitating a more efficient and governed way of answering business questions.

What impact has the evolution of business intelligence had on IT's role?

The evolution has allowed IT to focus more on innovation and higher-level tasks, rather than getting bogged down with repetitive report generation, which is now handled by business users through self-service tools.

How does the modern approach to analytics enhance agility in business environments?

By enabling self-service data preparation and advanced analytics, business users can quickly adapt to changing needs, explore new data sources, and make decisions faster without waiting for IT intervention.

What is the benefit of having both IT and business users collaborate in the modern analytics environment?

Collaboration between IT and business users leads to greater productivity and agility, as it combines business insights with IT expertise to drive innovation and solve business problems more efficiently.