REPORTING AND ANALYTICS || How To Make Data-Driven Business Decisions

Summary

This video script explores the key differences between reporting and analytics in business. Reporting focuses on summarizing data to monitor performance, offering factual insights into 'what is happening.' Analytics, on the other hand, digs deeper into data to uncover the reasons behind trends and offer actionable insights, answering 'why it is happening.' The video highlights tools for both reporting (e.g., Fine Report, What A Graph) and analytics (e.g., Apache Spark, R), and explains the importance of maintaining separate data repositories for each function to ensure efficiency and minimize risks.

Takeaways

• 😀 Reporting is the process of compiling data into factual summaries to monitor business performance, while analytics goes deeper, extracting insights to improve performance.
• 😀 Reporting focuses on presenting 'what is happening,' while analytics explains 'why it is happening' through detailed analysis.
• 😀 Reporting tasks involve building, organizing, formatting, and summarizing data, whereas analytics tasks include questioning, examining, interpreting, and predicting data.
• 😀 Reporting delivers data through a push approach, providing static reports, dashboards, and alerts to users, whereas analytics follows a pull approach, extracting data to answer specific questions.
• 😀 Reporting outputs include canned reports, dashboards, and alerts, all with predefined metrics and limited interactivity, while analytics results in complex presentations with key findings and recommendations.
• 😀 The primary goal of reporting is to monitor business performance and alert users about expected performance ranges, while analytics is aimed at answering questions and providing actionable insights.
• 😀 Reporting uses automation tools to generate and deliver reports to large audiences periodically, whereas analytics requires manual work and deep reasoning by analysts to derive insights.
• 😀 Reporting tools like Fine Report, Whatagraph, and Splenty help connect to data sources, generate reports, and track business performance, often using automated processes.
• 😀 Analytics tools like Apache Spark, R, Microsoft Power BI, and Apache Storm are used for handling large data sets, conducting in-depth analysis, and providing real-time analytics and insights.
• 😀 Maintaining separate data repositories for reporting and analytics helps protect data from damage, reduce costs, differentiate data sources, and improve performance by preventing system slowdowns.

Q & A

What is the primary difference between reporting and analytics?

The primary difference is that reporting focuses on summarizing data to monitor business performance, while analytics involves extracting insights from data to understand and improve business performance.

What tasks are involved in reporting?

Tasks in reporting include building, configuring, organizing, consolidating, formatting, and summarizing data into factual summaries.

How does analytics differ in terms of tasks compared to reporting?

Analytics involves questioning, examining, interpreting, comparing, and predicting data, as opposed to reporting tasks which focus on organizing and summarizing data.

What types of reports are included in reporting outputs?

Reporting outputs include canned reports (static reports with set metrics), dashboards (high-level views of business performance with KPIs), and alerts (notifications triggered when data falls outside expected ranges).

How does the approach to delivering data differ between reporting and analytics?

Reporting uses a push approach, where data is delivered to users automatically, whereas analytics uses a pull approach, where analysts actively extract data to answer specific questions.

What is the role of automation in reporting?

Automation in reporting is essential for building and delivering reports periodically, often to large audiences, using automated tools to generate and send reports.

Why is manual work more important in analytics compared to reporting?

Manual work in analytics is crucial because it requires human expertise to interpret data, draw insights, and offer recommendations, while reporting is more focused on summarizing and automating data delivery.

What are some of the best tools for reporting?

Some of the best reporting tools include FineReport, Whatagraph, Splenty, and AnswerRocket. These tools help create and automate reports, offering features like integration with data sources and easy-to-use interfaces.

Which analytics tools are popular for handling large data sets?

Popular analytics tools for large datasets include Apache Spark (an open-source processing engine) and R (a versatile tool with many packages for big data integration).

Why is it important for firms to create separate data repositories for reporting and analytics?

Separate data repositories are important for protecting data, managing costs, differentiating between data types, and ensuring that analytics does not slow down transactional systems. Reporting and analytics each require distinct data formats and management strategies.