{"id":231,"date":"2023-05-02T13:07:44","date_gmt":"2023-05-02T13:07:44","guid":{"rendered":"https:\/\/c-college.tempisr.io\/?p=231"},"modified":"2023-07-20T11:51:28","modified_gmt":"2023-07-20T11:51:28","slug":"data-analyst-sil","status":"publish","type":"post","link":"https:\/\/c-college.co.il\/?p=231","title":{"rendered":"\u05e1\u05d9\u05dc\u05d1\u05d5\u05e1 Data Analyst"},"content":{"rendered":"\n
<\/span>
<\/div>
\n

<\/p>\n\n\n\n

\n
\n
\n Excel <\/summary>\n

\n\nIntroduction\n
\nMatch&Index \/hlookup \/ vLookup \/ xlookup\n
\nFunctions Agg: MAx ,Min,Count ,Sum\u00a0\n
\nStatement If: SumIf ,CountIf ,If\u00a0\n
\nFunctions Scalar: Etc Len ,Split ,Right\n
\nDate Functions\n
\nMath Functions\u00a0\n
\nConcatenating Data\n\n<\/p>\n<\/details>\n<\/div>\n\n\n\n

\n
\n Data Analysis\u00a0 <\/summary>\n

\nPivot Table\n
\nMulti Conditions\n
\nWhat If Analysis\u00a0\n
\nGoal Seek\n
\nVisualizing Data\n
\nSorting And Filtering\n\nGraph and charts\n\nForecast sheets\n\nSummarizing Data\n\nGet Data From Different Sources\n<\/p>\n<\/details>\n<\/div>\n<\/div>\n\n\n\n

Power BI<\/strong><\/strong><\/h2>\n\n\n\n
\n
\n
\n Introduction to Power BI <\/summary>\n

\n\nWhat is that BI Tools and Power BI\n
\nInstall Power BI\n
\nUnderstanding the ETL Process\n
\nOverview in powerbi desktop\n<\/p>\n<\/details>\n\n\n\n

\n Power Query Editor <\/summary>\n

\nConnecting to Different Sources\n
\nData Preparation in Power Query Editor\u00a0\n
\nCleaning\n
\nUnderstanding Row Operations\n
\nFiltering\n
\nAdd Columns\n
\nReplacing Values\n
\nConditional Columns\n\n<\/p>\n<\/details>\n<\/div>\n\n\n\n

\n
\n Data Model <\/summary>\n

\nRelationships: One To One, Many To Many, One to Many\n
\nDax Basics Operators\n
\nUsing Calculated column and Creating Measures\n
\nIf Statement\n<\/p>\n<\/details>\n\n\n\n

\n Create Dashboard <\/summary>\n

\nCreating Visualization With Power BI\n
\nFormatting Charts\n
\nDrill Down and filtering Graphs\n<\/p>\n<\/details>\n<\/div>\n<\/div>\n\n\n\n

SQL<\/strong><\/strong><\/strong><\/h2>\n\n\n\n
\n
\n
\n Introduction <\/summary>\n

\nIntroduction to the role and working environments of the data analyst\n
\nIntroduction to SQL Server Management Studio.\n<\/p>\n<\/details>\n\n\n\n

\n Data Retrieval Language <\/summary>\n

\nBasic Concepts and Datatypes\n
\nSelect Statement\n
\nFilter Data with Where Statement and Logical Operators\n
\nAggregate Functions: Count ,Sum ,Avg ,Max, Min\n
\nOrganize Data With Order By, Group By, Top, Distinct etc\n
\nGrouping Sets \/ Rollup \/ Cube\n\nBuilt In Functions: Use Scalar Functions, Date Functions, Math Functions.\n\nJoin Multiple tables from the database\n\nUse Sub- Queries and Common Table Expression.\n\nUnion Multi Queries Together.\n\nWindows Functions By using Partition By.\n\nDML \u2013 Data Manipulation Language: Insert, Update, Delete.\n\n<\/p>\n<\/details>\n<\/div>\n\n\n\n

\n
\n Relational database management system <\/summary>\n

\nEntity RelationShip Diagrams\n
\nData Types\n
\nKeys ,Tables ,Schemas ,Database, Indexes ,Constraint\n<\/p>\n<\/details>\n\n\n\n

\n Transact-SQL <\/summary>\n

\n Stored Procedure\n
\nFunctions\n
\nViews\n
\nContinue ,Break ,If ,While etc.\n\n<\/p>\n<\/details>\n<\/div>\n<\/div>\n\n\n\n

Python<\/strong><\/strong><\/strong><\/strong><\/h2>\n\n\n\n
\n
\n
\n Introduction <\/summary>\n

\nIntroduction to Data Analysis with Python and Pandas\n
\nInstallation Jupyter Notebook\u00a0\n
\nIntroduction to Jupyter Notebook\n<\/p>\n<\/details>\n\n\n\n

\n Basic Concepts <\/summary>\n

\nComments\u00a0\n
\nTypes Data Basic\n
\nOperators \n
\nVariables\u00a0\n
\nBuilt -In Functions\u00a0\n
\nMethods\u00a0\n
\nDictionaries , List\u00a0\n
\nIndex Positions and Slicing\n<\/p>\n<\/details>\n\n\n\n

\n Pandas Series Pandas <\/summary>\n

\nWorking\u00a0 with Series\u00a0\n
\nIntroduction to Methods\n
\nIntroduction to Attributes\u00a0\n
\nArguments And Parameters\u00a0\n
\nRead Different Sources With Pandas\u00a0\n
\nSort Values, Sort Index, Value counts\n
\nUnique and Nunique\u00a0\n
\nApply Method\n<\/p>\n<\/details>\n<\/div>\n\n\n\n

\n
\n Pandas DataFrame <\/summary>\n

\nWorking With DataFrame\u00a0\n
\nMethods and Attributes\u00a0\n
\nSelect Columns from DataFrame\u00a0\n
\nAdd Columns to DataFrame\u00a0\n
\nFind missing Values\u00a0\n
\nAstype method\u00a0\n\nFilter Data and Using conditions\u00a0\n\nClean Data with drop duplicates method\u00a0\n\nLoc and Iloc\u00a0\n\nQuery Method\u00a0\n\nMulti Indexing\u00a0\n\nPivot and PivotTable\u00a0\n\nGroupBy And Agg Methods\u00a0\n\nMerge, Join and Concat\u00a0\n\nWorking with Times and Dates\u00a0\n\nVisualization with pandas\n<\/p>\n<\/details>\n\n\n\n

\n Seaborn and Matplotlib Visualization <\/summary>\n

\n\nHistograms\u00a0\n
\nBox and Violin Plots\u00a0\n
\nRegressions\u00a0\n
\nHeatMaps Correlation\u00a0\n
\nBar Plot\u00a0\n
\nDistplot\n<\/p>\n<\/details>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n