Data analytic process by bn reddy
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This document provides guidance on using Tableau to conduct advanced data analysis in three steps: 1) Define the objective and identify required data, metrics, sources and resources for the analysis. 2) Collect and validate data, normalize it, analyze it, draw preliminary conclusions and review with stakeholders. 3) Present results considering the audience, getting to the point quickly without detailing steps, and determining the format, cadence and ongoing nature of presentations.
Data analytic process by bn reddy
- 1. To get trained on Advanced Tableau ©BNReddy eMail:bnagireddy100@gmail.com call me 09396725649 Production. Start by defining the objective of the analysis (e.g. measuring the impact of a sales training program, identifying sales performance issues, improving forecast accuracy). Identify the types of data to be collected, the metrics that will be used, and the data sources and the resources required to conduct the analysis. Interpretation. Collect the data, and validate that the quantity and quality is sufficient to support decisionmaking. For example, is data available on a broad enough base of sales reps to support conclusions? Has data been collected over a time period long enough to identify behavioral changes? Normalize the data to correct for external factors (e.g. rep tenure, territory size, competitive differences, pipeline maturity). Analyze the data, draw preliminary conclusions and review these with key stakeholders before making final recommendations. Presentation. Your understanding of the audience should inform how you present the results. Take into account audience members’ roles, responsibilities, level in the organization and preferred method of consuming information. The key is to get to the point quickly, not educate the audience on the steps involved in the analysis. Consider the cadence, frequency and format for presenting results. Is this a one-time analysis or an ongoing effort that will become part of the standard operating procedure?