The article got me thinking about my quest to define the role of
the analyst. Reading the blog "Reporting vs. Analysis: What’s the Difference?", help formalize my thoughts. Check out Brent Dykes's key thoughts on the differences between reporting and analysis:
- Organizing data into informational summaries
- following a push approach, where reports are pushed to users who are then expected to extract meaningful insights and take appropriate actions for themselves (i.e., self-serve)
- Outputs: canned reports, dashboards, and alerts (reports sent to users based on a triggering event)
- providing no or limited context about what’s happening in the data. In some cases, the end users already possess the necessary context to understand and interpret the data correctly.
- not going to answer the “so what?” question on its own
- Exploring data and reports in order to extract meaningful insights
- Following a pull approach, where particular data is pulled by an analyst in order to answer specific business questions.
- Outputs: Ad hoc responses (reports) and Analysis presentations (a comprehensive, deep-dive analysis)
- Providing context which is critical to good analysis. In order to tell a meaningful story with the data to drive specific actions, context becomes an essential component of the story line.
- Emphasizing data points that are significant, unique, or special - and explain why they are important to the business
Upon retrospect, I would add one more style of BI reporting to their list of 5 styles.I call it:
Business Analysis
This style is performed by a business/clinical/health data/data analyst with the purpose of answering a business question that leads to action. The analysis must sniff out the business question through questioning and discovering the appropriate business context. The end user will receive a written analysis with supporting charts and tables. The analyst will need tools that allow to him/her sift through sometimes millions of rows and find a meaningful summaries of this data.
Tool Options to support Business Analysis
MS Excel and Power Pivot for MS Excel
The most versatile tool in Microsoft's arsenal continues to be MS Excel. Excel can consume SQL data extracts, data cubes, and external data from vendors. Utilize various built-in functions and add-ins to perform analysis on the data points. With the Power Pivot add-in installed, Excel merge disparate data sources with relative ease. You can even create your own data cube of the source data.
MS Word
Yes, Word is a tool. One needs to express the end results of analysis in a coherent and organized fashion. Word provides to means to accomplish this.
MS Outlook
I know that it is strange to list Outlook as a BI tool. Here is my thought, rarely is an analysis so compelling that it leads to immediate action. Part of the analsyst's job is to follow-up with the business user. If no action is taken then the analysis was neither useful or needed. Utilizing Tasks and Calendar events to track follow-up conversations is vital to a successful analysis.
Describe impact on an organization
I've heard "we have lots of data but no information". In order to answer a business question, one must transform data into a meaningful story. Given the right data and the appropriate tools, an analyst can create a compelling story that can be understood by many.
I find myself travelling down this path toward insights and actionable data. After walking down the reporting path for many years, this will be a major paradigm shift.
Yes, Word is a tool. One needs to express the end results of analysis in a coherent and organized fashion. Word provides to means to accomplish this.
MS Outlook
I know that it is strange to list Outlook as a BI tool. Here is my thought, rarely is an analysis so compelling that it leads to immediate action. Part of the analsyst's job is to follow-up with the business user. If no action is taken then the analysis was neither useful or needed. Utilizing Tasks and Calendar events to track follow-up conversations is vital to a successful analysis.
Describe impact on an organization
I've heard "we have lots of data but no information". In order to answer a business question, one must transform data into a meaningful story. Given the right data and the appropriate tools, an analyst can create a compelling story that can be understood by many.
I find myself travelling down this path toward insights and actionable data. After walking down the reporting path for many years, this will be a major paradigm shift.
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