Data Analyst Vs Business Analyst Vs Data Engineer Vs BI Specialist

 


Data Science - Complete Track

• Step 1 - Identify the business problem/value addition/question – (Data Insights) this has to be the starting point.

• Step 2- Data availability (Data Governance) - Have the structure of your data set defined – The real challenge starts here-

            o Do we have the data?

            o Do we have access to the required data?

• Step 3 -Getting Data (Data Mining / Data Pipeline) – How to collect the data from different sources in the system

• Step 4 -Data preparation (ETL / ELT) – Once you have data there will be lot of cleaning and preparation required, reduce/increase/combine/split the predictors, determine and eliminate outliers, populate missing values convert few categorical variables into numerical etc.

• Step 5 –Exploratory Data Analysis (EDA) – In this step we do descriptive and diagnostic analysis of the existing data. We build multiple graphs that give us direction towards the next steps of predictive analytics. We might also consider clustering the data and checking patterns.

• Step 6- In this step, we would apply one or more algorithms/calculations to get the Predictive / Forecasting / Simulation Model.

• Step 7 -Reporting / Visualization / Dashboards– Graphical representation of the insights/results wherever possible and make it easy for business to interpret.

• Step 8 -Interpreting results (Story Telling) - working with business in decision making and appropriately implementing the decisions taken.

Steps 1 and 8 – Should be done by a Business Analyst

Steps 2, 3 and 4 – For Data experts/Data engineers

Steps 5 and 6 – Data Analyst

Step 7 – Reporting Expert (BI Specialist)







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