Pawan P Email and Phone Number

An Data Analyst with foundation in Statistics and passion for Data Analysis. Have hands on experience in Data Cleaning, Visualization and Analysis using Excel, SQL, Power Bi, Python tools. TECHNICAL SKILLS:1) EXCEL: ProficientCombine two tables using V lookup, Index Match, X lookup format.Apply Statistic Concepts (Mean, Median, Mode) & do Data Transformation using Power Query Editor.Use Power Pivot and DAX Measures for creating Business Reports.Use Conditional Formatting to highlight data points that meet certain conditions.2) SQL: Proficient | DBMS Platforms: Microsoft SQL Server, My SQL Use Constraints to create Tables and apply Alter, Update, Delete commands for modification.Retrieve Data using Aggregations, JOIN Operations & Sub Queries, Order By, Group By clauses, Date, String functions, Set Operations.3) POWER BI: ProficientLoad Data from DBMS database and validate against benchmark numbers. Perform Data Transformation. Connect dimension tables and fact tables to create star schema.Create calculated columns using Power Query Editor and DAX Measures.List and Create Required Metrics using DAX Measures for Report Views. Use Slicers to filter data.Use charts(Line, Waterfall, Ribbon) in visuals to show parameters performance over time.Generate required client dashboards and Receive Stakeholder feedback update dashboards by adding toggle button to switch between two visuals, tool tip to show trends, Key Performance Indicator Visuals to compare Revenue & Dynamic Targets(BM Nos).h) Add Real time market data to setup automatic data refresh through SQL DB, Excel.4) PYTHON: V3.10 | Proficient.Create Data Structures (List, Tuple, Dict, Set, other built-in functions).Write List, Set, Dict Comprehensions & Lambda functions using loops concept.Handle Exceptions in Programs using try and except method, to load data files and fetch sub data. 5) NUMPY | BeginnerCreate Arrays from Scratch, Python lists containing int, float, string, etc. standard data types with required Attributes i.e. Shape, Size. perform Array Concatenation and Splitting, Indexing, Slicing Ops to access Sub arrays, Reshape Arrays,Computation on Arrays like Aggregate Ops (like Min, Max, etc.),Broadcasting, Comparisons, Fancy indexing on Structured Arrays. 6) Python Libraries: PANDAS | Beginnercreate Pandas Series, Data frame Objects and select required data using Indexing, loc, iloc, Slicing features.perform Ufunc Operations on Data to handle Null Values and combine datasets using Concat, Merge, Join, Group By features (i.e., Split, Apply, Continue).